This week’s reports highlight how financial services are entering a new phase of transformation driven by AI, stablecoins, and payment modernization. Banks are investing heavily in fraud prevention, data quality, and instant payment infrastructure, while regulators are developing frameworks to support the safe growth of stablecoins. The reports also explore how digital money is reshaping credit unions, why the UAE is becoming a leader in regulated stablecoin payments, how AI could transform retail financial services by 2030, why payments are becoming a strategic priority for treasury teams, and how robust reconciliation systems are essential for fintechs operating at scale.

Video of the Week

Deep Dive of the Week

Revolut’s Compounding Growth Strategy

Did you read the “Algorithm That Keeps Compounding” case study by Andreessen Horowitz (a16z)? If not, do not worry; I did it for you. In this deep dive, I take analysis by a16z as the core, share my comments on what they got right, what was too optimistic, and what was missing. We have to admit the global consumer fintech market has transitioned from the loose capital era of customer acquisition at all costs to a mature phase defined by structural monetization, regulatory validation, and balance sheet efficiency. While many first generation neobanks struggle under margin compression, the performance metrics of Revolut stands different.

To understand how the compounding engine of Revolut works, we must look past the consumer-facing marketing and dissect the underlying growth algorithm:

This formula is supported by a highly diversified six-segment revenue matrix, an asset-light core architecture, and an operating structure that decouples scale from operational headcount. This deep dive deconstructs these mechanisms, providing a strategic blueprint for fintech founders, product managers, and payments strategists operating in 2026.

This week’s reports

1️⃣2026 KPMG Banking Technology Survey

2️⃣Stablecoins and Macroeconomic Stability

3️⃣How Digital Money Is Impacting Credit Unions

4️⃣The UAE Stablecoin Payments Playbook

5️⃣AI and the future of retail financial services

6️⃣HSBC’s Global Payment Trends Report 2026

7️⃣Account Reconciliation Patterns for High-Volume Fintech

2026 KPMG Banking Technology Survey

KPMG just surveyed 200 banking executives for its 2026 Banking Technology Survey. A few numbers stood out.

91% of banks are prioritizing security and fraud prevention over the next 12 months. Nearly unanimous, and the AI arms race is why. 90% are already using or piloting GenAI for fraud detection, but the same technology is scaling the threat on the other side.

Technology is now an M&A driver, not just a cost center. 33% of banks say tech is directly shaping their acquisition strategy, chasing data/AI capabilities (67%) and cybersecurity (65%).

Data remains the unresolved bottleneck. 100% of respondents cite data quality as a top modernization challenge. You can’t run agentic AI on bad data, and most banks know it.

Payments are moving fast. 72% are modernizing for FedNow, 70% for RTP. Instant payments and ISO 20022 are forcing banks to rebuild rails they’ve patched for decades.

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Did you read the “Algorithm That Keeps Compounding” case study by Andreessen Horowitz (a16z)? If not, do not worry; I did it for you. In this deep dive, I take analysis by a16z as the core, share my comments on what they got right, what was too optimistic, and what was missing. We have to admit the global consumer fintech market has transitioned from the loose capital era of customer acquisition at all costs to a mature phase defined by structural monetization, regulatory validation, and balance sheet efficiency. While many first generation neobanks struggle under margin compression, the performance metrics of Revolut stands different.

To understand how the compounding engine of Revolut works, we must look past the consumer-facing marketing and dissect the underlying growth algorithm:

This formula is supported by a highly diversified six-segment revenue matrix, an asset-light core architecture, and an operating structure that decouples scale from operational headcount. This deep dive deconstructs these mechanisms, providing a strategic blueprint for fintech founders, product managers, and payments strategists operating in 2026.

Deconstructing the “Users × ARPU” formula

At the heart of the scaling model lies a dual-engine architecture designed to expand customer reach while simultaneously driving multi-product penetration. During the fiscal year ending December 31, 2025, group revenue grew 46% year-on-year to £4.5 billion, while profit before tax surged 57% to £1.7 billion, representing an elite profit before tax margin of 38%.

In software and technology investing, the Rule of 40 serves as the benchmark for elite operational efficiency. In our analysis of this compounding model, we observe a performance that operates on a completely different scale: the Rule of 75%. Calculated by combining the 46% revenue growth rate with a 29% net profit margin (derived from a net profit of £1.3 billion on £4.5 billion in revenue), the compounding speed places it in the highest tier of global financial institutions.

This compounding velocity is reflected in a Return on Equity of 35%.¹ This capital efficiency is achieved despite massive overcapitalization, as total CET1 capital resources reached £2.6 billion.¹ Traditional retail banks struggle to generate an ROE above 12% due to legacy physical branches, heavy human operational layers, and localized capital constraints. The company achieves its premium ROE by maintaining a completely branchless digital footprint and utilizing a viral peer-to-peer transaction network.

With 16 million new retail customers added in 2025 alone, bringing the total base to 68.3 million, approximately 70% of new sign-ups were acquired organically or through peer-to-peer referral loops. This referral system lowers customer acquisition costs to near-zero levels.

This organic reach provides the customer volume required to execute the average revenue per user expansion engine. Since 2022, overall ARPU has compounded at an 18% CAGR. This expansion is not dependent on a single asset class or lending product. Instead, it is driven by a highly diversified product matrix that distributes monetization across payments, interest, subscriptions, wealth, and foreign exchange.

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In this episode of WRAP UP podcast, I sit down with Amir Sarhangi, CEO of Skyfire, to explore what the rise of the machine economy means for payments, banking, and e-commerce. As AI agents become capable of searching, comparing, negotiating, and completing purchases aut…

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The latest reports highlight how digital financial infrastructure is evolving across payments, identity, and blockchain technology. The World Bank’s Digital Wallets: A New Paradigm positions digital wallets as foundational infrastructure for securely storing verifiable credentials while enhancing privacy through selective disclosure. Meanwhile, Public Blockchains and Regulated Financial Institutions from Kinexys by J.P. Morgan and the MIT Digital Currency Initiative examines the key regulatory and technical barriers preventing banks from fully adopting public blockchains, emphasizing that long-term solutions will require collaboration between financial institutions, protocol developers, and regulators. Complementing these trends, Australia’s The Vision for Account-to-Account Payments outlines a national framework for building a secure, interoperable, and inclusive A2A payments ecosystem, with expanded infrastructure access and rich ISO 20022 payment data serving as key enablers of future innovation.

Video of the Week

Deep Dive of the Week

How to Add Data Intelligence to a Multi-PSP Payment Stack

For the past decade, the global e-commerce and fintech sectors have operated under a singular directive: maximize payment optionality. Merchants have been instructed to expand their payment stacks by integrating multiple Payment Service Providers (PSPs), deploying redundant local acquirers, supporting diverse regional payment methods, and configuring dynamic routing paths. On the surface, this architecture of optionality has delivered significant operational value. It provides structural resilience against single-point-of-failure gateway downtime, secures broader geographic coverage across emerging markets, and optimizes baseline transaction approval rates.

However, this diversified payment stack introduces a major operational challenge: the fragmentation of transactional data. When an enterprise expands its processor footprint, it inevitably decentralizes its reporting architecture. Each integrated provider operates within its own closed ecosystem, generating isolated telemetry data characterized by proprietary APIs, unique database schemas, non-standardized decline reason codes, and distinct monthly settlement formats. Attempting to consolidate these disparate data streams into a single source of truth requires significant data engineering effort and often obscures clear data lineage and transformation logic.

This is the multi-PSP paradox: while adding payment gateways increases processing flexibility, it simultaneously degrades transaction visibility. In a multi-PSP environment, payment, finance, risk, and data teams must spend significant time and capital trying to reconcile inconsistent reporting formats manually. Without a unified mechanism to harmonize these data streams, merchants struggle to identify systemic processing errors, leaving them exposed to hidden margin erosion, elevated transaction costs, and transaction routing inefficiencies.

This week’s reports

1️⃣The AI Playbook for Financial Services

2️⃣The State Of Payment Tokenization

3️⃣Q1 2026 Quarterly FinTech Insights

4️⃣Public Blockchains and Regulated Financial Institutions

5️⃣The vision for account-to-account payments in Australia

6️⃣Digital Wallets: A New Paradigm

7️⃣Crypto Regime

The AI Playbook for Financial Services

I have a question for fintechs and financial institutions: what is your AI strategy?

AI represents a structural disruption, and its impact on financial services goes far beyond efficiency gains. It is reshaping how work is organized, how decisions are made, how value is created and how institutions compete and collaborate.

As the industry moves from experimentation to scaled deployment, the central challenge for organizations is fully integrating AI quickly and securely. The decisions involved, from data management to governance structures, are numerous and varied. This report aims to help financial services firms across all geographies and sectors work through the complexity.

The report’s key findings are as follows:

AI must be a strategic leadership issue.

The priority has shifted from running pilots to embedding AI across the enterprise, quickly, responsibly and in ways that deliver lasting value. Leaders must define where to focus, what to automate and where human judgement remains essential, and how to weave AI into day-to-day operations to deliver better outcomes for customers.

Differentiation will increasingly come from customer relationships amplified by AI.

With analytical and generative capabilities now widely accessible, organizations that use AI to intentionally strengthen customer relationships will be better positioned to deliver superior experiences, deepen retention and drive growth. Central to this is ensuring customers trust how the technology is being used.

The biggest benefits will come from redesigning holistically.

Read more

For the past decade, the global e-commerce and fintech sectors have operated under a singular directive: maximize payment optionality. Merchants have been instructed to expand their payment stacks by integrating multiple Payment Service Providers (PSPs), deploying redundant local acquirers, supporting diverse regional payment methods, and configuring dynamic routing paths. On the surface, this architecture of optionality has delivered significant operational value. It provides structural resilience against single-point-of-failure gateway downtime, secures broader geographic coverage across emerging markets, and optimizes baseline transaction approval rates.

However, this diversified payment stack introduces a major operational challenge: the fragmentation of transactional data. When an enterprise expands its processor footprint, it inevitably decentralizes its reporting architecture. Each integrated provider operates within its own closed ecosystem, generating isolated telemetry data characterized by proprietary APIs, unique database schemas, non-standardized decline reason codes, and distinct monthly settlement formats. Attempting to consolidate these disparate data streams into a single source of truth requires significant data engineering effort and often obscures clear data lineage and transformation logic.

This is the multi-PSP paradox: while adding payment gateways increases processing flexibility, it simultaneously degrades transaction visibility. In a multi-PSP environment, payment, finance, risk, and data teams must spend significant time and capital trying to reconcile inconsistent reporting formats manually. Without a unified mechanism to harmonize these data streams, merchants struggle to identify systemic processing errors, leaving them exposed to hidden margin erosion, elevated transaction costs, and transaction routing inefficiencies.

The scale of modern payment infrastructure highlights the necessity of resolving this paradox. Enterprise payment platforms, such as IXOPAY, orchestrated over $171 billion in transaction volume in 2025 alone, analyzing more than 850 million payment events using advanced machine learning models. Managing transactions at this scale requires a transition from basic payment routing to automated, centralized payments intelligence.

Deconstructing the technical gaps of decentralized stacks

The core issue of data fragmentation across a multi-PSP stack lies in how financial data is structured. When a merchant initiates direct integrations with independent processors, they ingest non-standardized raw telemetry streams. Each provider translates transaction events into its own schema, meaning a single decline event or settlement fee is classified differently depending on the gateway used. The resulting visibility gaps impact performance across several operational areas:

1. Authorization and Decline Telemetry

When transaction authorization rates fall, pinpointing the cause is difficult without unified data. A decline may stem from an issuer-side issue, a gateway timeout, an authentication failure within the 3D Secure (3DS) flow, or a misconfigured fraud ruleset.

Because different gateways categorize error codes differently (for example, one provider might label a transaction as a generic gateway error while another classifies it as an issuer-side card decline), payment operations teams often struggle to isolate the root cause. This classification mismatch leads to delayed troubleshooting and prolonged checkout abandonment.

2. Interchange, Scheme, and Acquirer Fee Complexity

To evaluate processing costs, merchants must track several distinct fee components: network interchange rates, scheme fees, gateway transaction charges, acquirer markup margins, and cross-border currency conversion (FX) rates.

These fees are often buried inside complex, inconsistent monthly settlement reports. Without a unified mechanism to normalize these variables across providers, merchants cannot easily determine their total cost of acceptance (TC A) at a transaction level.

To evaluate these costs systematically, the total cost of acceptance across N transaction events and M active processors can be modeled mathematically as:

where Ii is the variable interchange fee rate, Si is the card scheme fee rate, Mi is the acquirer markup, Gi is the gateway fee for transaction i, Vi represents the individual transaction volume, and Ffixed,j represents fixed monthly recurring fees across the active providers.

In a fragmented data environment, calculating this metric becomes highly inefficient, masking cost spikes and preventing data-driven provider negotiations.

3. Retry Mechanisms and Involuntary Churn

For subscription and recurring billing businesses, transaction recovery is critical to protecting revenue. When an initial subscription payment fails, merchants use automated retry chains to recover the transaction.

However, if these retry cascades are executed across multiple processors without a centralized tracking system, merchants cannot identify which retry chains successfully recover customer accounts and which simply generate redundant processing fees. This lack of coordinate-level tracking turns a recovery tool into an unexpected cost driver.

4. Fraud Risk, Disputes, and Network Compliance

Siloed fraud and risk monitoring systems make it difficult to detect emerging attack patterns. Indicators like first and second chargebacks, dispute win rates, and Visa Abuse Prevention Program (VAMP) exposure ratios are often tracked independently across distinct provider portals.

Consequently, risk teams struggle to build a unified view of fraud trends, delaying their response to vulnerabilities until after significant losses have occurred.

5. Post-Processing, Reconciliation, and Settlement Overhead

Because different payment methods generate data at varying frequencies and in different formats, manual financial reconciliation becomes a major operational bottleneck.

Finance and accounting teams are forced to manually cross-check transaction records with raw bank statements and gateway invoices to identify processing discrepancies, rounding errors, and unexpected conversion fees. This manual overhead consumes significant developer time and operational resources.

The limits of static gateway interfaces and internal BI engineering

To resolve these fragmentation issues, many organizations attempt to build custom payment dashboards using standard business intelligence (BI) systems. However, traditional BI systems and standard gateway interfaces have notable limitations.

Gateway-provided dashboards only display transactional activity within their own environment. They do not support multi-PSP data aggregation, automated anomaly detection, or direct API integration with external risk tools.

While in-house BI tools (such as Tableau, Looker, or Power BI) can ingest data from multiple sources, they lack native support for payment-specific schemas. They do not naturally parse complex transaction attributes like card BIN ranges, decline reason distributions, or Durbin-regulated transaction statuses.

Consequently, building and maintaining custom internal ETL (Extract, Transform, Load) pipelines to normalize payments data requires continuous engineering effort. Every time an integrated PSP updates its API version, changes its settlement file layout, or modifies a decline code, the internal data pipeline breaks.

This continuous maintenance diverts engineering resources away from the core product. Ultimately, manual database tracking remains retrospective. It tells the organization what failed yesterday, but it cannot actively identify or resolve processing errors as they occur.

Designing a unified payments intelligence layer

To bridge the gap between fragmented transaction data and actionable operations, payment architectures require a dedicated payments intelligence layer. Slipped between the payment routing engine and downstream analytical applications, this layer acts as an automated control center. It ingests raw transaction metadata, normalizes it into a consistent schema, and applies machine learning models to optimize processing decisions in real time.

According to the design principles defined by IXOPAY, a modern payments intelligence infrastructure is built around five core functional pillars:

1. Payments Analytics and Multi-PSP Normalization

The foundation of a payments intelligence strategy is the consolidation of scattered data points from gateways, acquirers, internal databases, and fraud engines into a single analytical environment.

This platform allows operations teams to slice performance metrics across multiple dimensions, including specific gateway accounts, card brands, BIN countries, and merchant identification numbers (MIDs) to track exactly how every transaction performs across different processing paths.

2. Conversational AI and Natural-Language Diagnostics (IXONav)

To reduce reliance on manual database queries, payments intelligence platforms integrate conversational AI assistants. For instance, IXOPAY’s IXONav functions as an automated payment analyst.

Using natural language, teams can query their transaction data directly (such as asking: “Did decline rates spike in the last 24 hours on credit card transactions in Europe?”), and the assistant will instantly return formatted visualizations, diagnostic breakdowns, and routing recommendations.

This interface is integrated directly into active team workspaces and communications channels like Slack, sending automated notifications when anomalies are detected.

3. Real-Time Anomaly Detection and Baseline Forecasting

Human analysts cannot manually monitor millions of transaction events for micro-shifts in processing performance.

Payments intelligence platforms resolve this by employing machine learning models that continuously scan transaction flows across more than 50 data dimensions. These systems evaluate the probability of transaction authorization based on a multi-dimensional feature vector:

where x is a feature vector containing variables like card brand, BIN country, issuer ID, transaction currency, time of day, and risk score, and w represents the model weights optimized across millions of historical payment events.

By comparing actual performance against predicted baselines, the anomaly detection engine identifies sudden temporal spikes (such as gateway-side timeouts) as well as gradual baseline drifts (where approval rates slowly degrade over several weeks).

When a deviation is flagged, the system estimates its financial impact in real terms (for example, identifying a 4% drop in Brazilian debit approvals costing $18,000 daily), allowing operations teams to act immediately.

4. Seamless Data Sharing and Warehouse Pipelines

To prevent transaction data from living in silos, the payments intelligence layer must integrate with downstream business environments.

By standardizing telemetry data across providers, the system pushes formatted transaction records directly to internal databases and data warehouses, featuring direct support for Snowflake integration.

This automated pipeline eliminates reporting discrepancies across departments and simplifies the ingestion of clean transaction data into internal ERP and BI environments.

5. Centralized Risk Monitoring and Pre-Chargeback Interception

A unified intelligence layer also serves to protect processing margins by centralizing dispute and risk management.

Through no-code integrations with early warning networks like Ethoca and Verifi (RDR/CDRN), the platform routes pre-chargeback alerts directly to a single dashboard.

This allows merchants to intercept disputes and issue refunds before formal chargebacks are filed, protecting their merchant processing history and avoiding network fines.

Merchant-owned tokenization and agnostic orchestration

A multi-PSP strategy cannot succeed without independent, merchant-owned tokenization. In a traditional gateway-locked setup, the processing provider generates proprietary payment tokens that are only functional within their own ecosystem.

This proprietary lock-in prevents the merchant from routing customer payment details to alternative gateways or acquirers, leaving them vulnerable to unilateral price increases and restricted geographic flexibility.

Decoupling tokenization from the processing layer resolves this architectural bottleneck. By storing card credentials in a secure, provider-agnostic token vault, merchants generate portable tokens that can be securely processed across any connected acquirer.

Once tokenization is centralized, payment orchestration platforms can optimize the entire transaction lifecycle:

Smart Routing Mechanics

Transactions are dynamically directed to the optimal processor based on real-time criteria like card brand, transaction value, geolocation, and risk scoring.

By routing transactions to localized regional acquirers, merchants consistently improve approval rates while minimizing cross-border processing fees.

Automatic Smart Retries (Fallback Routing)

If a primary payment provider experiences technical downtime or routes an unexpected decline, the smart routing engine automatically reroutes the transaction payload to a secondary processor.

This automatic fallback retry prevents checkout failures, protects transaction volume, and maintains high availability.

Load Balancing

Payment volumes can be distributed across multiple processors based on custom operational rules.

This load balancing optimizes processing commitments across vendor contracts, prevents merchants from exceeding transaction caps, and helps manage high-risk transaction volumes.

Post-Processing Reconciliation Engine

To simplify accounting workflows, the post-processing engine automatically retrieves and standardizes settlement statements across all connected gateways.

It compares this raw processor data with values in the internal transaction database, flags discrepancies (such as incorrectly calculated transaction fees or currency rounding errors), and exports formatted reconciliation logs directly to ERP systems like SAP or Microsoft Navision.

Trust orchestration in agentic commerce

The rapid development of autonomous systems is driving the next significant shift in payment processing. E-commerce is transitioning from standard, screen-based checkouts to machine-driven transaction execution.

In this agentic commerce landscape, AI-driven software agents act as autonomous delegators evaluating products, negotiating purchase terms, and completing checkouts on behalf of human users.

This evolution breaks the traditional four-party risk model (consumer, merchant, issuer, and acquirer), which was designed under the assumption of human-initiated transaction consent. When autonomous machines execute payments, merchants encounter unique technical and operational challenges:

1. Breakdown of Standard Fraud Detection

Traditional fraud prevention systems analyze human behavioral signals (such as mouse movements, browsing history, and device fingerprints) to verify transaction legitimacy.

Automated agent sessions, which are executed through virtual environments with automated metadata, mimic fraudulent patterns. According to an Accenture study, 78% of financial institution chief technology officers and payments heads expect fraud to increase significantly as agentic commerce scales, while 87% identify trust as the primary barrier to adoption.

2. Increased Dispute Exposure and Liability Shift

Without biometric human verification or standardized authentication patterns, proving transaction consent is difficult.

If a user claims their AI agent exceeded its spending limit or placed an incorrect order, the merchant bears the burden of proof. Without verified transaction trails, disputes can quickly lead to high chargeback rates.

3. High Protocol Fragmentation

As major technology ecosystems introduce proprietary transaction frameworks, payment platforms must remain protocol-agnostic.

Merchants need infrastructure capable of coordinating identity, intent, and value across competing AI protocols without building separate integrations for each system.

To manage these operational risks, tokenization must evolve from a security tool for card numbers into a programmable trust infrastructure.

Securing machine-driven transactions requires compiling multiple tokenized signals to establish a reliable transaction record:

• Identity Tokens: Verify the specific AI agent, system, or machine initiating the transaction.

• Intent Tokens: Preserve the user’s instructions (such as category constraints or maximum spending limits) directly within the transaction payload.

• Consent Tokens: Store a signed digital record of the customer’s authorization of the purchase.

• Payment Tokens: Represent the secure, portable account credentials used to execute the final transaction.

By combining these tokenized components, payment infrastructure can verify both payment details and authorization context, protecting the business against emerging chargeback risks.

This need for verifiable transaction context has led to industry initiatives like the Unified Trust Layer framework, co-developed by IXOPAY and Zip US. This open framework is designed to collect, evaluate, and route multidimensional trust signals across networks and protocols, preparing payment architectures for the requirements of automated commerce.

Strategic blueprint and executive recommendations

For fintech founders, product managers, and payments strategists, resolving the multi-PSP paradox requires implementing several key structural practices:

Consolidate Payment Telemetry

Deploy a provider-agnostic payments intelligence layer to unify transaction metadata across all active processors into a consistent schema.

Avoid relying on siloed gateway dashboards, and establish direct pipelines to downstream data platforms like Snowflake to support automated financial planning and operational oversight.

Establish Merchant Data Ownership

Separate token storage from the processing layer by utilizing a centralized, universal token vault.

This ensures complete portability of stored payment credentials, removes technical barriers to gateway migration, and reduces PCI compliance scope by up to 90%.

Deploy Automated Diagnostics

Implement machine learning-driven anomaly detection alongside automated pre-chargeback interception networks.

Configure custom alerts to monitor core performance metrics such as transaction approval rates, routing latency, and fee variances to resolve processing errors before they impact overall revenue.

Transition Payment Flows to Support Trust Architecture

Design the transaction environment to support programmable token structures that can capture identity, intent, and consent metadata alongside traditional card credentials.

Preparing the payment stack to verify and record machine-initiated checkouts will help secure transaction volume as agent-driven commerce scales.

Disclaimer:

Fintech Wrap Up aggregates publicly available information for informational purposes only. Portions of the content may be reproduced verbatim from the original source, and full credit is provided with a “Source: [Name]” attribution. All copyrights and trademarks remain the property of their respective owners. Fintech Wrap Up does not guarantee the accuracy, completeness, or reliability of the aggregated content; these are the responsibility of the original source providers. Links to the original sources may not always be included. AI is used to produce some pieces of this article. For questions or concerns, please contact us at sam.boboev@fintechwrapup.com.

So what is really happening?

In this episode of the WRAP UP podcast, I sit down with Charbel Safadi, CEO of Zafin, to discuss the future of AI in banking, why most AI initiatives fail, and how banks can move beyond experimentation into production.

We cover:

• Whether AI is hype or a genuine transformation
• Why banks are struggling to achieve ROI from AI
• The prediction that 200,000 banking jobs could disappear
• How AI changes jobs rather than simply replacing them
• Zafin’s new AI Operating System (AIOS)
• Why banks need an “airport” for AI agents, not just more AI tools
• AI governance, compliance, and accountability in regulated industries
• How banks should think about OpenAI, Anthropic, Gemini, and open-source models
• The future of autonomous AI agents inside financial institutions
• Why proof of work may become critical for enterprise AI adoption

One of the most interesting takeaways was Charbel’s argument that AI is not primarily a technology challenge. It is an operating model challenge. Organizations that redesign how work gets done will benefit. Those that simply add AI tools to existing processes may struggle to see meaningful results.

What do you think?

Will AI create more opportunities in banking, or are the predictions about job losses correct?

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This week’s reports explore how AI, blockchain, and evolving financial infrastructure are reshaping commerce and banking. A major theme is the rise of agentic commerce, with multiple reports highlighting the need for stronger identity standards, liability frameworks, interoperable payment rails, and programmable credentials before AI agents can transact at scale. Other reports examine how AI-first banks are driving growth through personalized services and automation, why blockchain is emerging as the foundation for machine-native payments and digital identity, and how treasury functions are adapting to AI, regulatory complexity, stablecoins, and multi-rail payments. The roundup also covers the Bank of England’s finalized systemic stablecoin regime and a framework for fostering competition in digital financial services through better regulation and market infrastructure.

Video of the Week

Deep Dive of the Week

A Definitive Strategic Guide to MiCA Compliance and Institutional Market Architecture

The transitional grandfathering window under Article 143(3) of the Markets in Crypto-Assets Regulation (MiCA) has officially expired across all 27 European Union (EU) and 30 European Economic Area (EEA) member states. This milestone marks the definitive end of the highly fragmented national Virtual Asset Service Provider (VASP) registries and establishes a single, harmonized authorization framework for Crypto-Asset Service Providers (CASPs). For fintech founders, payments strategists, and venture capitalists, this shift represents a hard boundary: any entity providing crypto-asset services to EU clients without full MiCA authorization is now operating in direct breach of EU law.

This week’s reports

1️⃣How Acquirers Prepare for Agentic Commerce

2️⃣How AI-First Banks Are Rewriting the Rules of Retail Banking

3️⃣The Convergence of AI and Blockchain

4️⃣Agentic commerce: The rise of the delegated buyer

5️⃣UK: BoE finalises systemic stablecoin regime

6️⃣Treasury 2.0: Built for a new era

7️⃣Competition in Digital Financial Services

How Acquirers Prepare for Agentic Commerce

56% say the #1 barrier to scaling agentic commerce is redesigning liability frameworks

43% say identity and credential-binding standards must be established before scaling

23% plan to proactively accelerate agentic commerce in the next 3 years

🔹 What do Acquirers need to do?

Identity rules create trust

As transactions shift from human to AI initiated, identity must evolve for agents to operate safely and securely on behalf of consumers. Acquirers say they need clearer standards for binding identity, credentials, and intent, which helps ensure every agent led transaction is authenticated, authorized, and transparent.

Interoperability is top of mind

Agentic commerce introduces new expectations for how acquirers, merchants, networks, issuers, and AI platforms coordinate. To navigate these challenges, acquirers are prioritizing interoperability and shared standards so merchants don’t face fragmented experiences across channels or platforms.

Read more

The transitional grandfathering window under Article 143(3) of the Markets in Crypto-Assets Regulation (MiCA) has officially expired across all 27 European Union (EU) and 30 European Economic Area (EEA) member states. This milestone marks the definitive end of the highly fragmented national Virtual Asset Service Provider (VASP) registries and establishes a single, harmonized authorization framework for Crypto-Asset Service Providers (CASPs). For fintech founders, payments strategists, and venture capitalists, this shift represents a hard boundary: any entity providing crypto-asset services to EU clients without full MiCA authorization is now operating in direct breach of EU law.

Prior to this enforcement milestone, the European digital asset landscape resembled a patchwork of disparate national standards. Member states exercised discretion over the duration and terms of their transitional timelines, leading to non-uniform grandfathering periods across the continent. While jurisdictions such as France, Malta, and Luxembourg elected the maximum 18-month transitional window expiring on July 1, 2026, others enforced significantly tighter timelines.

This chronological asymmetry created severe cross-border compliance mismatches. Entities passporting services from a jurisdiction with a longer transitional window into a state where the window had already closed found themselves in immediate technical breach, resulting in localized enforcement actions and platform geofencing. The regulatory consequences of operating without authorization are severe. Under MiCA Article 111, National Competent Authorities (NCAs) are empowered to levy administrative fines of up to €5 million or up to 12.5% of total annual turnover for legal entities. In tandem, regulators are executing mandatory wind-down protocols. Unauthorized platforms must immediately halt new user onboarding, cease all marketing and customer solicitation, and restrict their operational interfaces exclusively to asset liquidations, transfers, and account closures.

The transition has exposed a vast compliance deficit. Out of more than 1,200 legacy VASP entities registered nationally before MiCA, only approximately 200 to 213 platforms successfully transitioned to full CASP status by the close of the grandfathering window a successful conversion rate of less than 18%. This structural contraction is re-routing the competitive dynamics of the entire European fintech sector, separating fully compliant market players from those forced to execute orderly exits.

For clients and counterparties, remaining on unauthorized platforms introduces significant operational and financial risks. Unlicensed entities provide no guaranteed asset segregation, leaving customer funds vulnerable to pooling and loss within a bankruptcy estate. Clients face sudden asset freezes, withdrawal delays, and localized tax or legal complications as regulators coordinate cross-border enforcement. To mitigate these exposures, corporate treasurers and institutional allocators are actively auditing their transaction counterparty chains, verifying entries against the European Securities and Markets Authority (ESMA) register to ensure seamless liquidity routing.

Technical architecture for the unified European market

For digital asset development teams, payments strategists, and software engineers, compliance is no longer a localized legal review; it is a system-level architectural requirement. In the EU, MiCA does not operate in isolation but is tightly integrated with the recast Transfer of Funds Regulation (TFR - Regulation 2023/1113) and the Digital Operational Resilience Act (DORA - Regulation 2022/2554).

Read more

In this episode of the WRAP UP podcast, I sit down with David Rosa, General Manager at Rapyd, to discuss one of the biggest transformations happening across financial services today.

We explore the launch of OpenUSD and what it means for the stablecoin market, why Rapyd believes stablecoins are solving real-world payment problems, and how AI is already reshaping the economics of payments businesses.

David also explains how Rapyd uses AI to onboard merchants, automate internal operations, improve decision-making, and why he believes many traditional jobs will inevitably change as AI adoption accelerates.

We also discuss:

• OpenUSD and the future of stablecoins
• Whether stablecoins can challenge traditional payment rails
• AI agents and autonomous payments
• Why Visa and Mastercard are paying attention
• MiCA regulation and its impact on crypto businesses
• Real-time payments and cross-border infrastructure
• Why emerging markets may be affected most by AI disruption
• How Rapyd is rebuilding operations around AI
• The biggest mistakes businesses make in payments today

David oversees AI Transformation, FX, Payouts, and Platform Solutions at Rapyd, one of the world’s leading fintech companies powering global commerce and payments.

Subscribe for more conversations with CEOs, founders, regulators, and executives shaping the future of fintech, payments, banking, crypto, AI, and financial infrastructure.

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This week’s reports highlight the rapid institutional adoption of blockchain-enabled finance, with stablecoins, tokenized deposits, and real-world asset tokenization emerging as key drivers of modern payment and banking infrastructure. Major initiatives such as Open USD, Project Agorá, and tokenized banking networks demonstrate how programmable, blockchain-based settlement can improve cross-border payments, operational efficiency, and financial inclusion. The reports also emphasize that regulatory clarity, effective governance, data quality, and trust are becoming as important as technological innovation. Beyond digital assets, insights from Africa’s instant payment systems, European banks’ regulatory reporting, and J.P. Morgan’s fintech outlook show that the future of financial services will be shaped by scalable payment infrastructure, automation, AI, and embedded finance, with stablecoins and tokenization playing an increasingly central role in the global financial ecosystem.

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Deep Dive of the Week

Open USD vs Tether and Circle, and Bank Tokenized Deposits

The global payments landscape is undergoing a structural transition as on-chain fiat instruments move from speculative retail instruments to institutional settlement rails. This shift is marked by two major infrastructure initiatives: the June 30, 2026, announcement of Open USD, denoted as OUSD, a shared stablecoin network backed by a consortium of over 140 corporate signatories, and the planned launch in the first half of 2027 of a tokenized deposit network operated by The Clearing House, which is co-owned by the largest commercial banks in the United States.

Led by Open Standard, an independent company, OUSD presents a collaborative, partner-governed model that directly challenges the traditional single-issuer structures of Tether and Circle. Led by founding Chief Executive Officer Zach Abrams, who previously co-founded the stablecoin infrastructure provider Bridge (acquired by Stripe for 1.1 billion dollars in 2025), Open Standard aims to realign the underlying economics of the stablecoin float. This analysis evaluates the architectural design of Open USD, compares its regulatory posture with Facebook’s defunct Libra project, assesses its competitive positioning against the USDC-USDT duopoly, and contrasts its utility against the banking sector’s emerging tokenized deposit networks.

This week’s reports

1️⃣The Stablecoin

2️⃣Scaling Instant Payments in Africa

3️⃣Project Agorá

4️⃣Blockchain-Enabled & Stablecoin Banking

5️⃣The strategic role of stablecoins and tokenization for Canadian institutions

6️⃣The Glass Bank

7️⃣Sector spotlight: Fintech

The Stablecoin

Viktor Yaromin published Issue 02 of The Stablecoin Monthly Review and it’s one of the better-curated resources on stablecoin infrastructure I’ve seen.

42 reports collected, distilled, and contextualized. Not summaries for the sake of summaries actual structural takeaways from papers by Deutsche Bank, BlackRock, the Federal Reserve, McKinsey, BIS, Bessemer, and more. All in one place.

The issue also covers the full May deal flow ($8.7B+ in disclosed transactions), a stablecoin data hub with market structure breakdowns, and a deep-dive partnership piece on privacy infrastructure with Hinkal.

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The global payments landscape is undergoing a structural transition as on-chain fiat instruments move from speculative retail instruments to institutional settlement rails. This shift is marked by two major infrastructure initiatives: the June 30, 2026, announcement of Open USD, denoted as OUSD, a shared stablecoin network backed by a consortium of over 140 corporate signatories, and the planned launch in the first half of 2027 of a tokenized deposit network operated by The Clearing House, which is co-owned by the largest commercial banks in the United States.

Led by Open Standard, an independent company, OUSD presents a collaborative, partner-governed model that directly challenges the traditional single-issuer structures of Tether and Circle. Led by founding Chief Executive Officer Zach Abrams, who previously co-founded the stablecoin infrastructure provider Bridge (acquired by Stripe for 1.1 billion dollars in 2025), Open Standard aims to realign the underlying economics of the stablecoin float. This analysis evaluates the architectural design of Open USD, compares its regulatory posture with Facebook’s defunct Libra project, assesses its competitive positioning against the USDC-USDT duopoly, and contrasts its utility against the banking sector’s emerging tokenized deposit networks.

The Genesis and Mechanics of Open USD

Open USD is engineered as shared payment infrastructure rather than a proprietary commercial product. The initial signatory roster spans payments networks including Visa, Mastercard, American Express, and Discover; financial institutions such as BNY, BlackRock, Standard Chartered, and DBS; tech giants Google, IBM, and Samsung Electronics; and crypto platforms Coinbase, Solana, Base, and Aave. The breadth of this alliance reflects a consensus that scaling stablecoins for global workloads requires open, low-cost, and aligned infrastructure. Stripe’s corporate leadership has indicated that OUSD will serve as the default stablecoin for businesses running on Stripe, while BNY executives project that the stablecoin market could scale to 1.5 trillion dollars by 2030.

The protocol operates on three primary operational mechanics: zero-cost transactional paths, partner-level reserve distribution, and consortium governance.

Traditional stablecoin models restrict minting and redemption to select institutional partners, often applying tiered fees, volume limits, or clearing delays through proprietary banking networks. Open USD eliminates these transaction-level costs. Under the Open Standard model, participating businesses can deposit fiat dollars and receive OUSD tokens onchain, or redeem tokens back to physical fiat at par, with zero minting or burning fees and no artificial volume caps. By removing transaction friction, Open Standard seeks to incentivize high-volume corporate treasury operations, merchant settlement, and cross-border routing.

The second mechanical departure is the distribution of reserve earnings. Traditional issuers manage backing assets (cash and short-duration Treasury bills) and retain 100 % of the interest income. At high interest rates, this model generates exceptional profitability for the issuer, while the distributors and integrations that drive token adoption receive no direct financial upside.

Open USD inverts this model: all interest income generated by the underlying reserves is pooled by Open Standard. After deducting a small management fee to fund compliance, technical operations, and custody fees, the remaining yield is distributed back to the partner network. This structure transforms onchain dollars into a productive asset for payment processors, exchanges, and merchant acquirers.

The distribution of yield to consortium partners can be represented as:

In this equation, Rpartner represents the net yield routed back to the participating partner network, Rgross is the gross yield earned on the underlying reserve assets, and Cmanagement is the operational cost deduction retained by Open Standard.

The third mechanic is the collaborative governance model. Open Standard operates as an independent company whose board is drawn directly from its partner base. Material decisions, such as reserve policies, custodian and auditor selection, chain expansions, and blocklisting, are decided by a partner-led board rather than a single corporate issuer. This collaborative oversight provides the operational neutrality necessary for competing financial institutions to settle on a single shared rail.

OUSD is engineered as an onchain token. The platform will launch natively on Solana and Base, with subsequent rollouts planned for Polygon, Stellar, Aptos, and Stripe’s Tempo infrastructure. Furthermore, its integration with Aave (the largest onchain lending market) and institutional custody networks like Fireblocks ensures immediate ecosystem utility upon deployment.

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While most companies in crypto and stablecoins are focused on infrastructure, Raagulan believes the biggest opportunity lies elsewhere: building products for end users.

We discuss why he left Circle to launch Kast, a stablecoi…

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This week’s reports underscore the rapid convergence of digital assets, AI, and traditional finance. Stablecoins, tokenized deposits, and central bank digital currencies are emerging as complementary forms of digital money, supported by improving regulation and institutional adoption. Digital assets are moving beyond crypto speculation into mainstream banking, with tokenized real-world assets, programmable money, and blockchain-based settlement creating new revenue opportunities and operational efficiencies. AI-driven machine-to-machine payments are also gaining traction, enabled by protocols such as x402 that allow autonomous agents to transact without human intervention. Meanwhile, e-commerce continues to reshape banking, as traditional lenders seek to close credit gaps by leveraging richer merchant data and alternative underwriting models. Financial institutions are being urged to capitalize on strong profitability by investing in AI, digital assets, and scalable operating models to drive long-term growth. However, regulatory uncertainty remains a key obstacle, particularly for stablecoins, where differing frameworks across jurisdictions could influence where innovation and capital flow. Collectively, the reports suggest the financial industry is transitioning toward a more programmable, interoperable, and AI-enabled ecosystem, with success depending on modern infrastructure, regulatory clarity, and the ability to integrate digital assets into core financial services.

Video of the Week

Deep Dive of the Week

The Directory of US Card Issuing and Program Management Platforms

I mapped 19 of the platforms that issue and process cards in the US market, because from the outside they all describe themselves the same way and the differences that matter are buried in license structure, network access, and who actually holds the BIN. This guide sorts them into five categories and profiles each one across license type, networks, card types, features, and regional coverage. It ships with a companion Excel file so you can compare every platform side by side and filter on the dimensions you care about. I built it for anyone choosing an issuing partner, migrating a live program, or running competitive diligence on this market. Every data point comes from official sources and public disclosures as of June 2026, and where something is not disclosed I mark it that way instead of guessing.

This week’s reports

1️⃣Banking on e-commerce

2️⃣Digital Money – a perspective on stablecoins, tokenised deposits, and CBDCs

3️⃣How Digital Assets Are Reshaping the Foundations of Finance

4️⃣Mapping the top 100 stablecoins and their future

5️⃣Time to Shift Gears?

6️⃣Digital Assets

7️⃣Stablecoins: waiting for regulation

Banking on e-commerce

E-commerce has fundamentally changed the way both consumers and businesses shop, with global B2B and B2C e-commerce Gross Merchandise Value (“GMV”) reaching a staggering USD 13.2 trillion in 2025. Capitalising on numerous structural growth tailwinds, the industry has seen the rise of a plethora of third-party e-commerce merchants, numbering over 31 million in 2025 and accounting for the lion’s share of global e-commerce GMV, with an especially outsized GMV contribution in Asia.

Key takeaways:

· E-commerce has fundamentally changed the way both consumers and businesses shop, with global B2B and B2C e-commerce GMV reaching a staggering USD 13.2tn in 2025

· The industry has seen the rise of a plethora of third-party e-commerce merchants, numbering over 31m in 2025 and accounting for the lion’s share of global e-commerce GMV, with an especially outsized GMV contribution in Asia

· Compared to traditional retail, e-commerce platforms generate rich, standardised, and contextualised data by capturing both fund flows and fulfilment, materially enhancing underwriting potential. While this should, in principle, improve access to credit for e-commerce sellers, most banks remain structurally disconnected from the e-commerce ecosystem and lack access to real-time financial and operational data.

· This separation limits visibility into merchant performance and creates several key challenges, including (1) inaccurate credit profiling, (2) incompatible product offerings, and (3) an inability to control platform funds. Coupled with persistent operational frictions and prohibitive onboarding costs, most banks, especially in Asia, have remained on the sidelines, resulting in an estimated APAC e-commerce credit gap of USD 1.2tn in 2025

· Various FinTech lenders have emerged over the past decade to address the MSME e-commerce lending whitespace left by incumbent banks. While a growing number of incumbent banks are providing warehouse financing facilities to these FinTechs, this indirect participation model has seen them surrender ~USD 100bn in annual revenue potential to frenemies. And in the process of funding their digital-native challengers, they have given up owning the client relationship

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I mapped 19 of the platforms that issue and process cards in the US market, because from the outside they all describe themselves the same way and the differences that matter are buried in license structure, network access, and who actually holds the BIN. This guide sorts them into five categories and profiles each one across license type, networks, card types, features, and regional coverage. It ships with a companion Excel file so you can compare every platform side by side and filter on the dimensions you care about. I built it for anyone choosing an issuing partner, migrating a live program, or running competitive diligence on this market. Every data point comes from official sources and public disclosures as of June 2026, and where something is not disclosed I mark it that way instead of guessing.

What this guide covers

This deep dive profiles 19 card issuing processors, BaaS providers, sponsor banks, and full-stack platforms operating in the US, each across six structured dimensions: license type and issuing jurisdiction, card network membership, card types supported, key platform features, and geographic coverage. Every profile is built from publicly available information and official company documentation as of June 2026. Where data is not publicly disclosed, I mark it as Not disclosed.

The accompanying Excel file has seven tabs: Overview, Licenses, Card Networks, Card Types, Features, Regions, and a Master Table with every dimension combined and filterable in one sheet.

The 19 companies by category

Pure-play card issuing processors

Built primarily to issue and process cards for fintechs and financial institutions:

Marqeta: API-first issuer processor for debit, credit, prepaid, and virtual cards with just-in-time funding and dynamic spend controls

Lithic: Developer-first issuer processor for debit, prepaid, charge, and credit across consumer and commercial programs

Highnote: Unified embedded finance platform spanning issuing, acquiring, credit, and ledger on all major networks including Amex

Qolo: Natively unified card issuing and processing platform with an embedded ledger for banks and fintechs

Galileo: Established issuer processor (SoFi-owned) powering debit, credit, and prepaid for North American and Latin American fintechs

BaaS with issuing

Banking-as-a-service platforms where card issuance is one layer of a broader product:

Unit: Embedded finance platform offering accounts, debit, and charge cards to vertical SaaS via bank partners

Treasury Prime: Bank-direct BaaS connecting fintechs to a network of partner banks for accounts and card programs

Synctera: BaaS orchestrator pairing fintechs with community bank sponsors for card issuance across the US and Canada

Lead Bank: Missouri state-chartered bank running a national BaaS partner platform for accounts, cards, and lending

Global infrastructure with issuing

Banks and infrastructure providers that hold the license and offer issuing as a core product line:

Column: Nationally chartered bank built for developers, owning its BINs and offering direct card issuance

Cross River: New Jersey bank with API-driven card issuing, BIN sponsorship, and full program management

Increase: Banking infrastructure with direct Visa connectivity and a developer-first issuer processing core

Green Dot: Bank holding company and BaaS provider issuing debit and prepaid cards at consumer scale

Pathward: National bank and one of the largest US prepaid and DDA issuers via BIN sponsorship

Enterprise and legacy processors

Established, configuration-heavy platforms serving banks and large program managers:

i2c: Global issuer processor with a highly configurable platform spanning credit, debit, prepaid, and commercial

CoreCard: Enterprise card management and issuer processing software deployed across the US and internationally

Fiserv: Large-scale payments and core banking company with a full issuing and processing stack for financial institutions

Q2: Digital banking software with card management and issuance inside its consumer and commercial platforms

Full-stack PSP plus issuing

Payment service providers that bolt issuing onto acceptance and treasury:

Stripe: Payments platform whose Issuing product lets businesses create virtual and physical cards on Visa and Mastercard

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What’s behind the Subscribe button

Subscribers get the full structured profile for all 19 platforms:

What each platform actually does, in plain terms. License type and issuing jurisdiction, including the regulators behind the chartered banks. Card network membership across Visa, Mastercard, Amex, UnionPay, and others. Card types supported, from debit and credit to prepaid, virtual, physical, commercial, consumer, and white-label. The specific feature set: spend controls, real-time authorization, multi-currency, FX, API access, tokenization, 3DS, webhooks, instant issuance, BIN sponsorship, and program management. Regional coverage across Europe, UK, US, APAC, LATAM, and the Middle East. Plus the companion Excel file with seven filterable tabs and a master comparison table.

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Upgrade to read the full directory of all 19 platforms and download the companion Excel file.

SUBSCRIBERS ONLY · THE FULL DIRECTORY CONTINUES BELOW

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Modulr made a deliberate call two years ago to stop being a horizontal BaaS provider and go deep on specific verticals. They hold an EMI licence, settle at the Bank of England, and have direct scheme access and Myles argues that gives them everything they need without the overhead of a banking licence. The business model is flow, not storage, which means transaction revenue drives profitability, not interest margin.

We get into:

• Why Modulr walked away from the embedded finance land grab to double down on payments automation

• How their EMI licence gives them everything they need (and why they don’t want a banking licence)

• The US expansion with FIS and what real-time payment adoption actually looks like across markets

• Why the US is behind on real-time payments and what it will actually take to change behaviour

• Commercial VRP and whether open banking can ever dent direct debit

• Stablecoins vs. tokenized deposits — and how a non-bank positions for both

• How Modulr built a compliance hub with Sardine and where AI fits into fraud and operations

• How Modulr reached profitability, and why the answer is flow, not interest margin

• What’s on the roadmap: ACH in the US, foreign currency, and commercial VRP as a collections layer

Modulr’s bet is simple: own the infrastructure, stay focused on payments, and let the applications follow. Whether that thesis holds in the US is the real test.

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This week’s reports highlight two dominant themes in fintech: the rise of agentic commerce and the continued transformation of financial infrastructure. Multiple reports suggest AI agents are moving from experimentation to deployment, with businesses increasingly exploring autonomous purchasing, agent-managed transactions, and programmable money systems. While forecasts of multi-trillion-dollar markets should be viewed cautiously, the underlying trend is clear: commerce is becoming more autonomous, requiring new frameworks for trust, governance, identity, and payment execution. At the same time, embedded finance continues to mature, with SaaS platforms generating substantial revenue from payments, lending, and banking services, while cross-border payments remain constrained by poor interoperability despite advances in domestic instant payment networks. The reports also emphasize the growing role of AI in financial institutions, where productivity gains, new revenue opportunities, and autonomous financial services are reshaping business models. Regionally, challenges persist—from the UK’s declining competitiveness due to regulatory burden and underinvestment in technology to interoperability gaps across global payment ecosystems. Across all reports, success increasingly depends on scalable infrastructure, strong risk management, real-time payment capabilities, and governance systems that balance innovation with security and compliance.

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Deep Dive of the Week

Adyen’s Agentic a universal translator for agentic commerce

The evolution of digital commerce has arrived at a critical structural pivot. Previous major channel transitions, such as the shifts to mobile interfaces, social commerce, and multi-tenant marketplaces, redefined front-end customer experiences but left the underlying transactional architecture largely intact. In those conventional models, browsing sessions remained stateless, inventory validation was deferred until checkout, and risk engines examined single, synchronous authorization actions initiated by human telemetry. Agentic commerce represents a fundamental inversion of this legacy paradigm: software agents act autonomously on behalf of users, sessions become highly stateful and persist over days or weeks, and identity, trust, and payment authorization must be managed over highly fragmented, asynchronous networks.

The primary bottleneck stalling this transition is not Large Language Model capability, but the lack of scalable transaction infrastructure. Modern enterprise systems face severe operational bottlenecks: protocol fragmentation, obsolete product data structures, rigid legacy checkout stacks, the trust paradox of distinguishing legitimate agents from malicious automation, and the high engineering overhead of bespoke onboarding. McKinsey and Bain project that the global agentic commerce market will reach between 3 trillion and 5 trillion dollars by 2030, highlighting the massive scale of the economic opportunity. Accenture estimates that by 2030, over 30% of online commerce will run through AI agents, representing close to 3.1 trillion dollars in transactions. To prevent a fragmented ecosystem of closed gardens, Adyen launched Adyen Agentic on June 16, 2026. Acting as an open abstraction layer, this product operates as a universal translator, enabling merchants to integrate once and transact across multiple conversational AI platforms without rewriting core commerce databases.

This week’s reports

1️⃣Navigating the Agentic Commerce Era On Your Terms

2️⃣The B2B Embedded Finance Landscape

3️⃣The Thunes Cross-Border Payments Interoperability Index

4️⃣The UK Financial Services Sector Has Lost Its Edge—Here’s How to Win It Back

5️⃣Agentic Commerce: Market Insights & Outlook

6️⃣Time to Shift Gears?

7️⃣Unlocking Agentic Money Movement

Navigating the Agentic Commerce Era On Your Terms

This white paper effectively balances forward-looking tech evangelism with practical software architecture guidelines. It serves as a credible roadmap for transitioning from traditional e-commerce to AI-driven agentic transactions.

1. Data & Market Claims

The report relies on a mix of verified industry data and highly speculative long-term economic forecasting.

Verified Predictions: The claim of a 25% drop in traditional search engine volume aligns directly with official Gartner projections predicting a shift toward conversational interfaces.

The “Look Closer” Metrics: The 805% YoY increase in AI-driven retail traffic reflects a low-baseline statistical bias—early traffic was virtually zero, making any growth look explosive. Furthermore, Morgan Stanley’s $115 billion market addition by 2030 is a directional economic model, not a guaranteed reality.

2. Technical Frameworks & Protocols

The technical foundation laid out in Navigating the Agentic Commerce Era On Your Terms is highly authentic and architecturally sound.

Real Engineering Standards: The paper references MCP (Model Context Protocol), ACP, and UCP. MCP is a legitimate open framework (championed by Anthropic) designed to secure context exchange between LLMs and external data layers.

Grounded Realism: The document remains trustworthy by admitting that 49% of enterprise workflows still rely on manual spreadsheets. It accurately acknowledges that while brands have high AI ambitions, their data foundations remain messy.

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The evolution of digital commerce has arrived at a critical structural pivot. Previous major channel transitions, such as the shifts to mobile interfaces, social commerce, and multi-tenant marketplaces, redefined front-end customer experiences but left the underlying transactional architecture largely intact. In those conventional models, browsing sessions remained stateless, inventory validation was deferred until checkout, and risk engines examined single, synchronous authorization actions initiated by human telemetry. Agentic commerce represents a fundamental inversion of this legacy paradigm: software agents act autonomously on behalf of users, sessions become highly stateful and persist over days or weeks, and identity, trust, and payment authorization must be managed over highly fragmented, asynchronous networks.

The primary bottleneck stalling this transition is not Large Language Model capability, but the lack of scalable transaction infrastructure. Modern enterprise systems face severe operational bottlenecks: protocol fragmentation, obsolete product data structures, rigid legacy checkout stacks, the trust paradox of distinguishing legitimate agents from malicious automation, and the high engineering overhead of bespoke onboarding. McKinsey and Bain project that the global agentic commerce market will reach between 3 trillion and 5 trillion dollars by 2030, highlighting the massive scale of the economic opportunity. Accenture estimates that by 2030, over 30% of online commerce will run through AI agents, representing close to 3.1 trillion dollars in transactions. To prevent a fragmented ecosystem of closed gardens, Adyen launched Adyen Agentic on June 16, 2026. Acting as an open abstraction layer, this product operates as a universal translator, enabling merchants to integrate once and transact across multiple conversational AI platforms without rewriting core commerce databases.

The developer documentation pivot

In the early phase of agentic development, integrating a merchant with an AI agent platform was a bespoke, multi-month engineering effort. Each connection required coordinating mismatched data formats, custom backend systems, and fragmented security protocols across separate teams and timelines. This point-to-point scaling model proved fragile and unsustainable. If a merchant updated a single component of their core stack, such as an inventory management tool or a tax calculation engine, the direct connections to external AI platforms would break, introducing systemic fragility and locking out smaller retailers without dedicated engineering resources.

Traditional developer documentation websites, designed primarily for human readability on web browsers, aggravate this integration barrier. To navigate conventional documentation, AI agents must crawl pages over the internet, traverse complex reference chains, and frequently trigger rate-limiting security controls. This friction severely limits the speed and accuracy of agentic workflows.

To resolve this bottleneck, Adyen updated its developer documentation on June 2, 2026, making its entire resource stack natively agent-ready. By publishing its documentation as a dedicated markdown repository, including the implementation of the llms.txt standard synced directly with the active site, Adyen eliminated static-page crawling barriers. AI agents can now retrieve high-context, structured markdown files, rich metadata, and complete code samples across multiple programming languages (including .NET, Java, Python, TypeScript, Ruby, PHP, and Go) directly into their Retrieval-Augmented Generation pipelines.

This developer advocacy update was driven by measurable shifts in web traffic telemetry. Automated crawlers and machine-driven retrieval represent 11.6% of Adyen’s total documentation traffic volume, and user-directed AI assistant agents account for 78% of generative AI traffic, fetching content dynamically to answer active developer prompts during coding sessions. Traditional web layouts act as a significant bottleneck for machine runtimes: 29 % of AI requests land on homepages and 12 % hit robots.txt files because crawler bots spend processing cycles attempting to reverse-engineer site hierarchies. Standardizing documentation context acts as a critical prerequisite for building an open, interoperable transactional layer.

Technical architecture of Adyen Agentic

Adyen Agentic is architected as a suite of modular APIs natively integrated into the parent financial technology platform. Rather than forcing a complete system overhaul, this middleware layer translates transaction parameters between legacy databases and diverse agent protocols. The product is structured into three specialized architectural layers, mapping to the discovery, validation, and settlement phases of the buyer journey.

Agentic Feed

Traditional product feeds, such as those optimized for search engine marketing or social media advertisements, are designed as digital brochures. They typically carry around ten basic attributes (including name, price, image URL, and category) and rely on the human reader to infer details or navigate ambiguities. If a description lacks physical specifications or if inventory levels are slightly out of sync, a human customer can wait, refresh, or ask a question.

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We covered a lot of ground: why Stripe doesn’t have its own stablecoin, what Stripe Treasury actually means for global startups, how AI agents are starting to transact at scale, a…

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This week’s reports highlight three major themes shaping financial services: the rise of tokenized assets, the growing role of AI, and the increasing burden of compliance. Research suggests tokenized assets could expand from a niche market into a multi-trillion-dollar ecosystem by 2030, supported by improving liquidity, infrastructure, and regulatory clarity. Meanwhile, stablecoins are challenging traditional payment economics by offering cheaper, programmable settlement rails that could pressure interchange-based revenue models. AI continues to deliver significant efficiency gains across fintech, particularly in compliance, underwriting, and fraud prevention, though rising AI infrastructure costs are offsetting some productivity benefits. Across the industry, compliance remains both a major operational challenge and a growing opportunity for automation, while blockchain adoption is increasingly shifting from experimentation toward practical applications in money, contracts, and financial markets.

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Deep Dive of the Week

Tokenized Money Validates the Need for Unified Bank OS Infrastructure

The transition from traditional fiat messaging to tokenized asset execution represents the most significant architectural shift in the history of financial services. This evolution marks the end of the era of the ledger as a passive database and the beginning of the ledger as an active, programmable operating system.

The key insight driving this shift is simple but profound: tokenized money is not a replacement for fiat it is a natural extension of it. Just as banks extended from paper ledgers to digital core systems, the modern bank must now extend from fiat-only infrastructure to infrastructure that natively supports stablecoins, tokenized deposits, and future forms of digital currency. The institutions that thrive will not be those that treat each new form of money as a separate initiative. They will be those that build a unified operating system capable of treating every new innovation as a natural extension of what already exists.

The current global financial infrastructure is built on a series of fragmented, message-based systems that rely on bilateral reconciliation a model that is fundamentally incompatible with the instant, 24/7, and programmable nature of tokenized money. To survive the next decade, financial institutions must abandon the strategy of bolting on point solutions and instead adopt a unified operating system (OS) infrastructure that can orchestrate fiat, stablecoins, and tokenized deposits through a single, composable platform.

This week’s reports

1️⃣Who Pays for Payments?

2️⃣The $400T Future of Tokenised Assets

3️⃣Everything, Everywhere is Compliance

4️⃣State of AI in FinTech

5️⃣Can Blockchain Decentralise Money, Contracts, and Finance?

6️⃣Mapping the Top 100 Stablecoins and Their Future

7️⃣The State of Tokenization

Who Pays for Payments?

The payment system was never just a transaction layer. It became one of the largest hidden redistribution systems in finance.

A new Harvard Business School paper built on merchant-level data from roughly 1 million U.S. merchants and 800,000 Clover POS businesses shows how interchange fees quietly move purchasing power across consumers depending on how they pay.

The headline number is massive.

Researchers estimate around $30 billion annually flows from cash and debit users toward credit card users through interchange economics and rewards structures. Higher-income households capture a disproportionate share because premium credit card usage rises with income.

What makes this interesting is that the mechanism is more complex than the standard “merchants pay fees, consumers get rewards” narrative.

The paper argues redistribution depends on where people shop and what payment methods dominate inside those merchants. Grocery stores, gas stations, travel merchants, premium retail, large chains, and small businesses all face different interchange economics. Some large merchants negotiate materially lower fees while smaller merchants absorb higher costs.

That changes how the burden spreads across the economy.

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The transition from traditional fiat messaging to tokenized asset execution represents the most significant architectural shift in the history of financial services. This evolution marks the end of the era of the ledger as a passive database and the beginning of the ledger as an active, programmable operating system.

The key insight driving this shift is simple but profound: tokenized money is not a replacement for fiat it is a natural extension of it. Just as banks extended from paper ledgers to digital core systems, the modern bank must now extend from fiat-only infrastructure to infrastructure that natively supports stablecoins, tokenized deposits, and future forms of digital currency. The institutions that thrive will not be those that treat each new form of money as a separate initiative. They will be those that build a unified operating system capable of treating every new innovation as a natural extension of what already exists.

The current global financial infrastructure is built on a series of fragmented, message-based systems that rely on bilateral reconciliation a model that is fundamentally incompatible with the instant, 24/7, and programmable nature of tokenized money. To survive the next decade, financial institutions must abandon the strategy of bolting on point solutions and instead adopt a unified operating system (OS) infrastructure that can orchestrate fiat, stablecoins, and tokenized deposits through a single, composable platform.

The structural failure of legacy banking cores

The legacy core banking system is the primary obstacle to the adoption of tokenized money. These systems, many of which were architected in the 1970s and 1980s, were designed for an era of physical branches, paper checks, and overnight batch processing. They operate on the principle of ‘delayed state,’ where the record of a transaction is updated long after the payment instruction is initiated. This architecture is inherently flawed in a tokenized environment where the asset and the ledger are one and the same.

The problem of batch processing

Batch-oriented systems create a ‘liquidity lag’ that increases counterparty risk and operational friction. In a traditional system, a transaction must pass through a sequence of messages, reconciliations, and legal confirmations across multiple institutions before finality is achieved. This process is not only slow but also opaque, as participants often have incomplete information about the end-to-end transaction state.

The technical debt associated with these systems is staggering. Research indicates that approximately 90% to 95% of bank IT spending is consumed by the maintenance of legacy infrastructure rather than innovation. This resource drain prevents institutions from developing the high-speed data pipelines required for digital money. Furthermore, the lack of native API support in legacy cores necessitates the creation of complex middleware wrappers that add latency and create new points of failure.

The integration debt

Integrating blockchains with legacy systems is not a simple matter of cabling two databases together. Blockchains are deterministic and operate in a closed loop to ensure consensus. They cannot natively make API calls to a bank’s server to confirm a payment without reintroducing the single point of failure that the blockchain was designed to eliminate. This is known as the ‘Oracle Problem’.

When banks attempt to solve this by adding isolated tokenization modules, they create ‘integration debt.’ These point solutions often rely on asynchronous data ingestion and manual bridging mechanisms that are structurally insufficient in synchronous, real-time markets. The result is a proliferation of siloed tools and brittle pipelines that collapse under the weight of real-world complexity.

How banks are approaching tokenized money

As tokenized money moves from experimentation to production, banks are taking markedly different approaches. Understanding this landscape is essential because the infrastructure challenge each approach creates is converging on the same bottleneck.

The first group is doing nothing. These institutions are in a wait-and-see mode, sticking to the status quo while monitoring how the regulatory and competitive environment evolves. For now, this is a defensible position. It will not remain one for long.

The second group is moving to stablecoins alone. These banks recognize that stablecoins particularly USDC represent the path of least resistance. They are already established, widely accepted, and enable 24/7 programmable dollar transfers. For cross-border payments in particular, stablecoins eliminate costly intermediaries and foreign exchange friction.

The third group consists of the largest institutions JPMorgan, Citi, and a handful of others that have the scale and balance sheet to issue their own proprietary tokenized deposits. JPMorgan’s evolution from JPM Coin (a private-chain token for internal transfers) to JPMD (a tokenized deposit issued on public Layer 2 networks) illustrates the strategic direction: moving from liquidity islands toward institutional DeFi on public rails.

The fourth and largest group is forming consortia. Across the United States, banks are clustering by size to issue tokenized deposits collectively. The Clearing House (TCH) has brought together the largest names JPMorgan, Citi, Wells Fargo, and others to form a shared issuance network. Smaller banks have coalesced around the Hazel Network. Mid-sized institutions are forming the Cari Network. A similar dynamic is playing out in the United Kingdom, where major banks and the central bank are coordinating on interoperability standards.

The fragmentation problem

Here is the challenge every consortium creates: tokenized deposits issued within one network only function within that network. If a corporate treasurer’s bank is on Cari Network and their counterparty’s bank is on TCH, the tokenized deposit still does not work across that boundary. Each consortium solves the problem for its members while creating a new version of the same problem at the network edge.

The result is an increasingly fragmented ecosystem multiple networks, multiple issuers, multiple asset types, each operating according to different standards and settlement models. This fragmentation mirrors a pattern banking has seen before: when new payment networks emerged, many institutions rushed to connect, only to find that participation did not automatically translate into operational readiness. Access to a network is not the same as the ability to operate effectively within it.

What banks actually need is not a choice between consortia it is infrastructure capable of operating across all of them simultaneously. This requires two things: multi-issuer support (the ability to receive, hold, and settle tokenized deposits issued by different networks) and multi-asset support (the ability to manage fiat, stablecoins, and tokenized deposits within a single operational model). Without this, every new consortium a bank joins adds complexity rather than capability. Banks should keep these factors in mind as they prepare for the inevitable challenge of coexisting in a consortium-driven ecosystem.

The unified ledger

The Bank for International Settlements (BIS) has proposed the ‘Unified Ledger’ as the foundational infrastructure for the future monetary system. This concept represents a shift from fragmented networks to a shared programmable platform where tokenized central bank money, commercial bank deposits, and real-world assets reside on the same network.

The mechanics of executable objects

The unified ledger replaces passive records with ‘executable objects’ or tokens. These tokens integrate the record of the underlying asset with the specific rules and logic governing its transfer. This dual nature allows for ‘composability,’ where multiple transactions can be bundled together and executed automatically based on predefined conditions.

Atomic settlement is the core mechanic of this system. In a unified ledger, the exchange of assets and payments happens simultaneously. If any part of the transaction fails, the entire operation is canceled, ensuring that neither party is left without their funds or their asset. This eliminates the need for manual intervention and the message-passing processes that characterize modern banking.

The three aspects of tokenized assets

The BIS vision centers on a ‘trilogy’ of tokenized assets that together provide the stability, elasticity, and integrity required for a functional monetary system:

• Wholesale Central Bank Digital Currency (wCBDC): Acts as the ultimate settlement asset, providing a direct claim on the central bank to ensure interbank settlements occur with zero credit risk.

• Tokenized Commercial Bank Deposits: Represent the primary means of payment for the digital economy, retaining the traditional two-tier banking system while adding programmability and real-time settlement.

• Tokenized Real-World Assets (RWA): Include digitized versions of bonds, real estate, and commodities that can interact directly with tokenized money on the shared ledger.

The integration of these three components on a single platform allows for the creation of new economic arrangements that were previously impossible due to information and incentive frictions. For example, a smart contract could automatically disburse a dividend payment to thousands of token holders the instant a company’s earnings are verified, or a trade finance transaction could be settled automatically when a digital bill of lading is recorded on-chain.

The bank operating system (BankOS) paradigm

To bridge the gap between legacy cores and the unified ledger, financial institutions must adopt a modern ‘Bank Operating System’ (BankOS). A BankOS is a composable, cloud-native infrastructure that surrounds the legacy core with modern capabilities, allowing banks to modernize journey-by-journey without a ‘rip and replace’ of their system of record.

The defining feature of a modern BankOS is simple: every new innovation is absorbed as an extension of the infrastructure already in place. When real-time payments emerged, BankOS evolved to support them as another layer within existing payment rails. Now, as on-chain rails enter the equation, they slot into the very same payment architecture that already processes fiat today. For banks, this changes everything. New innovation no longer means building a new operating model from scratch — the operating system is designed to evolve ahead of change.

Composable infrastructure

Modern platforms like Finzly’s BankOS organize banking functions into specialized modules that deliver specific services independently. This modular approach is essential for preventing the creation of new silos as the bank adopts new payment rails and asset types:

• Payment: A unified payment hub that orchestrates all payment rails including ACH, Fedwire, RTP, FedNow, and SWIFT from a single platform, with centralized controls and real-time monitoring.

• Account: A real-time virtual account and ledger platform designed to support embedded finance, specialty deposits through virtual accounts including tokenized deposits. It functions as a ‘sidecar core’ or 24/7 shadow ledger, maintaining sub-second balance updates that the legacy core cannot handle.

• Token: Specifically designed for the tokenized economy, this suite unifies traditional and tokenized rails managing fiat, stablecoins, and tokenized deposits on a single platform with the flexibility to connect to multiple blockchains, issuers, and consortia simultaneously. It means new asset classes seamlessly integrate into existing account infrastructure, while on-chain connectivity becomes just another extension of the payment systems banks already rely on today.

The logic of the sidecar core

The ‘sidecar core’ strategy allows a bank to launch new products such as instant payments or tokenized deposits in weeks rather than years. By running a modern ledger (Account) alongside the legacy core, the bank can handle high-volume, real-time operational workloads while the legacy core remains the ultimate system of record for accounting and regulatory purposes.

This architecture provides a path for ‘progressive modernization.’ Over time, more functionality is strangled off the legacy core and provided by modern modules, until the legacy system can eventually be retired without disrupting business continuity.

Tokenized assets: Deposits, Stablecoins, and the On/Off ramp

The landscape of tokenized money is evolving into a spectrum of assets with varying degrees of trust, regulation, and utility. A unified OS must be capable of managing all these assets within a single operational environment and critically, providing intelligent movement between them.

Tokenized Deposits vs. Stablecoins

Tokenized deposits are the digital extension of a bank’s existing liabilities. They preserve the two-tier monetary system and benefit from existing regulatory frameworks, such as deposit insurance and central bank liquidity. Crucially, tokenized deposits earn interest making them attractive to corporate treasurers who need yield alongside speed.

Stablecoins, conversely, are typically issued by private entities and backed by reserves of cash or short-term securities. They have proven the demand for 24/7 programmable dollars, particularly for cross-border payments. A corporate treasurer moving funds to a counterparty in China, for example, can use USDC to avoid cross-border fees and correspondent banking friction entirely. However, under the U.S. GENIUS Act, stablecoin deposits cannot earn interest a meaningful limitation for treasury operations where yield matters.

The practical reality is that neither asset wins outright. Treasurers will hold stablecoins for cross-border payment velocity and hold tokenized deposits for yield and speed within the domestic banking system. Banks need infrastructure that can operate across both.

The intelligent On/Off ramp

This is where the infrastructure challenge becomes concrete. Banks need the ability to move fluidly between fiat, stablecoins, and tokenized deposits automatically and intelligently. When a client needs to convert fiat to stablecoins for a cross-border transfer, the platform must coordinate the fiat debit in the legacy ledger and the on-chain minting of the token in a single, synchronized workflow. When conditions favor tokenized deposits (for yield), the system should be able to sweep funds between asset types automatically.

Finzly’s Token Galaxy platform addresses this by coordinating the bridging between traditional and tokenized money automatically. But the key architectural requirement goes beyond any single bridge: the platform must support on-ramp and off-ramp between multiple asset types simultaneously, route intelligently based on cost, speed, and yield, and handle multiple issuers across multiple consortia all from a single operational model.

The programmability of JPMD

JPMorgan’s evolution from JPM Coin to JPMD illustrates the strategic shift toward public-rail interoperability. JPM Coin was a digital deposit token used for moving funds faster than traditional rails allowed, but it was limited to the bank’s internal, private blockchain (Onyx/Kinexys). This created a ‘liquidity island’ where assets could not interact with the broader $4 trillion daily repo market.

The launch of JPMD a tokenized version of a bank deposit issued on public Layer 2 networks like Base marks a shift toward ‘Institutional DeFi.’ JPMD allows the dollar on-chain to behave exactly like a dollar in the bank, providing the protection expected by institutions while enabling the speed and programmability of public blockchains.

Programmable treasury

Much of today’s discussion focuses on payments. Treasury may ultimately be the larger opportunity.

Once money becomes programmable, liquidity becomes programmable. Treasury becomes programmable. Consider what becomes possible when a bank operates across fiat, stablecoins, and tokenized deposits through a unified infrastructure:

• Automatic movement between operating accounts and yield-bearing tokenized deposits based on real-time balance thresholds

• Real-time liquidity optimization across multiple entities and currencies

• Instant cross-border liquidity movement using stablecoins, without correspondent banking delays or fees

• Dynamic funding decisions that respond to market events rather than scheduled windows

• Continuous cash positioning rather than end-of-day reconciliation

For corporate clients, this is far more compelling than simply moving money faster. It changes how cash is managed. And banks that can offer programmable treasury backed by multi-asset, multi-rail infrastructure are uniquely positioned to capture this opportunity.

The Architectural Blueprint: Two Foundational Capabilities

To treat tokenized deposits or stablecoins as isolated payment rails is an architectural failure. Digital assets must be treated as a natural, seamless extension of existing fiat assets. A modern Bank Operating System (BankOS) must deliver two foundational, non-negotiable capabilities to achieve this integration :

1. A Unified Ledger

As the variety of asset types expands, maintaining separate databases for fiat and digital liabilities becomes operationally impossible. The future bank requires a unified ledger, a single, real-time source of truth capable of managing fiat deposits, tokenized deposits, stablecoins, treasury positions, and liquidity balances.

This is not merely an accounting exercise. A unified ledger simplifies reconciliation, strengthens compliance controls, improves audit readiness, and ensures the bank can adopt new forms of money without rebuilding its core infrastructure every time a new asset emerges.

2. A Unified Money Movement Engine

While the unified ledger serves as the system of record, the money movement engine acts as the system of execution. Its purpose is to move value across any network through a common framework. Whether money travels through legacy rails (ACH, Wire), instant rails (RTP, FedNow), or digital rails (stablecoins, tokenized deposit networks, and blockchain settlement layers), the bank must manage routing, compliance, liquidity, and reporting from a single operational console.

When these two capabilities are unified, the real opportunity of programmable money shifts from basic payments to advanced treasury orchestration. Corporate clients gain access to automated cash positioning, real-time cross-border liquidity optimization, and dynamic funding decisions that respond automatically to events rather than rigid banking schedules.

Platform vs. Point Solutions

The current technology market remains highly fragmented. Most vendors focus on a single piece of the architecture, forcing banks to act as systems integrators.

Payments platforms solve routing, ledger platforms solve balance replication, and digital asset providers solve token minting. This piecemeal approach increases integration debt and operational risk.

The following matrix evaluates the primary technology providers against the requirements of a unified money operating system:

The data indicates that banks must move away from point solutions toward a comprehensive platform strategy. Point systems cannot handle the orchestration requirements of a multi-rail, multi-asset financial environment.

The adoption of a unified OS for tokenized money is not merely a technical upgrade; it is a strategic mandate driven by clear economic incentives.

Capital efficiency and liquidity optimization

The move from T+1 or T+2 settlement to T+0 or instant settlement has a massive impact on capital efficiency. Traditional settlement windows tie up billions of dollars in liquidity to manage settlement risk. By utilizing tokenization, institutions can free up capital nearly instantaneously. JPMorgan’s Kinexys platform has demonstrated a 30% reduction in intraday liquidity needs for its participants.

Operational cost reduction

A unified platform reduces operational complexity by removing messaging silos and the need for manual reconciliation between separate databases. In 2023, Goldman Sachs reported that 20% of their repo operations staff were solely dedicated to handling trade breaks and mismatches. On a blockchain ledger, where all parties view the same source of truth, these discrepancies are eliminated entirely.

Finzly reports that its unified payment hub can achieve a 60% cost reduction in payment processing operations with a Straight Through Processing (STP) rate of more than 99%. Furthermore, tokenization can automate regulatory reporting, which JPMorgan estimated could reduce compliance reporting costs for repo transactions by up to 70%.

Revenue growth through embedded finance

Legacy cores were never designed for the emerging embedded banking segment, where fintechs and non-bank platforms embed banking services directly into their customer journeys. A modern BankOS, such as Account, allows banks to generate unlimited virtual accounts programmatically, enabling them to compete for corporate and small-business customers who expect integrated financial services.

By using tokenization to fractionalize assets like private credit or real estate, banks can also unlock new revenue opportunities in traditionally illiquid markets. Fractionalization lowers the minimum investment size, allowing a broader pool of investors to access institutional-grade assets, thereby increasing market liquidity and transaction volume.

Escaping ‘Pilot Loop’

Despite the clear benefits of tokenized money, many banks are stuck in ‘pilot loop’ running dozens of isolated experiments that never scale into production. An MIT study from August 2025 found that 95% of enterprise AI and digital asset pilots fail to deliver measurable financial impact.

The failure of efficiency-only portfolios

Most institutions approach innovation through a narrow efficiency lens, focusing on cost reduction rather than growth or resilience. This results in an unbalanced portfolio of use cases that cannot justify the high upfront cost of new infrastructure. The banks seeing the greatest returns are those that have built balanced portfolios spanning growth (embedded finance), efficiency (automated reconciliation), and resilience (real-time risk monitoring).

The ‘Tractable Wedge’ strategy

Rather than a full core replacement, successful banks are using ‘tractable wedges’ small, contained deployments that run alongside existing systems:

• Shadow Mode Decisioning: The new OS runs in parallel with the legacy core, receiving the same live production data and logging its decisions without executing them. This allows the bank to build the empirical record required for regulatory approval with zero production risk.

• Progressive Migration: Once the new system consistently outperforms the legacy core, the bank can gradually ramp traffic via canary deployments.

The transition to tokenized money requires a shift in governance models. Traditional systems rely on institutional buffers and legal processes to manage failure. Tokenized systems rely on the correctness, resilience, and governance of code. This necessitates the creation of ‘AI and DLT Control Towers’ that provide explainability, human-in-the-loop controls, and immutable audit trails.

Multi-rail money movement

The future of payments is not the replacement of traditional rails with blockchain, but the coordination of multiple rails within a unified system. Modern fintech founders should view payment rails as evolutionary layers:

• Traditional Rails (ACH/SWIFT): Function like domestic road networks or global shipping routes reliable but slow and complex.

• Modern Rails (RTP/FedNow): Focus on real-time availability and open connectivity.

• Emerging Rails (Blockchain/Stablecoin/Tokenized Deposit Networks): Resemble autonomous air corridors decentralized, borderless, and continuously available.

A multi-rail strategy provides redundancy, cost optimization, and speed flexibility. Instead of building custom integrations for each rail, banks can publish a ‘standardized intent’ and let the OS infrastructure route it optimally across fiat rails, stablecoin networks, and tokenized deposit consortia simultaneously.

Risk mitigation in the tokenized economy

The rapid growth of digital assets introduces substantial risks that a unified OS must be equipped to handle.

Banks’ heavy reliance on technology makes them vulnerable to coding bugs in smart contracts and the potential compromise of digital wallets or private keys. A unified OS must implement robust security measures, including Multi-Party Computation (MPC) for key management, Hardware Security Modules (HSM), and 256-bit encryption.

MPC is particularly critical for institutional custody, as it ensures that the private key is never assembled in a single location. Instead, key shares are distributed across multiple parties, and signatures are computed collaboratively, eliminating any single point of compromise.

The inclusion of crypto into traditional finance introduces potential volatility and contagion. As on-chain transactional activity increases in size and complexity, stablecoins may pose risks to monetary policy and credit intermediation if they are not adequately regulated. By using tokenized deposits which are subject to existing bank capital and liquidity requirements institutions can mitigate these stability risks. The GENIUS Act’s restriction on stablecoin interest-bearing accounts reflects this regulatory concern, reinforcing why tokenized deposits represent the more durable long-term form of bank money in the digital economy.

The mandate for a unified Banking OS

Tokenized money is not a separate innovation silo. It is the next logical extension of digital recordkeeping and value transfer as natural a progression as the move from paper ledgers to core banking systems, or from batch payments to real-time rails.

The banking industry is converging on a world where traditional deposits, real-time payments, tokenized deposits, stablecoins, and future central bank digital currencies all coexist. The challenge is not deciding which form of money wins. The challenge is building infrastructure capable of operating across all of them simultaneously.

Banks that approach each new form of money as a separate project, a separate technology, a separate operating model will find themselves overwhelmed by complexity as the ecosystem fragments further. Banks that build a unified operating system will find that every new consortium, every new asset type, and every new regulation becomes a natural extension of infrastructure they already have.

A modern Bank Operating System, characterized by composable infrastructure, real-time ledgering, multi-issuer and multi-asset support, and intelligent on/off ramp capabilities, provides the only viable path to modernize without disruption. The era of the point solution is over. The era of the unified banking OS has begun.

Sources

1. III. Blueprint for the future monetary system: improving the old ..., accessed May 10, 2026, https://www.bis.org/publ/arpdf/ar2023e3.htm

2. Understanding the BIS Unified Ledger | Chainlink, accessed May 10, 2026, https://chain.link/article/bis-unified-ledger

3. What are Legacy Core Banking Systems? The Complex Nightmare - Baseella, accessed May 10, 2026, https://baseella.com/kb/what-are-legacy-core-banking-systems/

4. Multi-Rail Payments Infrastructure: Unifying Fiat and Stablecoins - Modern Treasury, accessed May 10, 2026, https://www.moderntreasury.com/journal/fiat-stablecoins-multi-rail-infrastructure

5. Finzly Unveils Token Galaxy: Unifying Money Movement for Traditional and Tokenized Banking - PR Newswire, accessed May 10, 2026, https://www.prnewswire.com/news-releases/finzly-unveils-token-galaxy-unifying-money-movement-for-traditional-and-tokenized-banking-302710960.html

6. Finzly Unveils Token Galaxy: Unifying Money Movement for Traditional and Tokenized Banking, accessed May 10, 2026, https://finzly.com/resources/press-releases/finzly-unveils-token-galaxy-unifying-money-movement-for-traditional-and-tokenized-banking/

7. Tokenized Deposits & Stablecoins Platform for Banks - Finzly, accessed May 10, 2026, https://finzly.com/solutions/tokenized-deposits/

8. Why Your Legacy Banking System is Holding You Back (And How to Fix It), accessed May 10, 2026, https://www.abbacustechnologies.com/why-your-legacy-banking-system-is-holding-you-back-and-how-to-fix-it/

9. The Future of Core Banking Systems: Architecture & Modernization - KMS Technology, accessed May 10, 2026, https://kms-technology.com/blog/core-banking-system/

10. SoK of RWA Tokenization: A Systematization of Concepts, Architectures, and Legal Interoperability - arXiv, accessed May 10, 2026, https://arxiv.org/html/2604.06608v1

11. JP Morgan made a huge deal with tokenized repos...so how did it go? - Substack, accessed May 10, 2026,

12. Tokenized Finance; IMF Notes No. 26/01; April 2026, accessed May 10, 2026, https://www.imf.org/-/media/files/publications/imf-notes/2026/english/insea2026001.pdf

13. Tokenized cash: A regulatory view of unlocking a digital financial market | State Street, accessed May 10, 2026, https://www.statestreet.com/pl/en/insights/digital-digest-december-2024-regulatory-update-tokenization

14. Legacy Systems vs. Modern Systems in Banking - KITRUM, accessed May 10, 2026, https://kitrum.com/blog/legacy-vs-modern-systems/

15. Virtual Account Management Platform | Real-Time Ledger System ..., accessed May 10, 2026, https://finzly.com/account-galaxy/

16. Three strategic mistakes that keep banks stuck in AI pilot mode - The Wealth Mosaic, accessed May 10, 2026, https://www.thewealthmosaic.com/vendors/backbase/blogs/three-strategic-mistakes-that-keep-banks-stuck-in-/

17. # AI Core Banking Integration: Strategies That Scale - Backbase, accessed May 10, 2026, https://www.backbase.com/blog/core-banking-integration

18. Blockchain Legacy System Integration Guide - Chainlink, accessed May 10, 2026, https://chain.link/article/blockchain-legacy-system-integration

19. Point Solutions or an Integrated Platform? - LexisNexis Risk Solutions, accessed May 10, 2026, https://risk.lexisnexis.com/insights-resources/article/point-solutions-or-an-integrated-platform

20. Digital Assets and Digital Market Infrastructure – A Structural Shift in Treasury and Capital Markets - Banking.Vision, accessed May 10, 2026, https://banking.vision/en/digital-assets-and-digital-market-infrastructure/

21. Legacy Payment Systems : 4 Important Bridging Strategies - Host Merchant Services, accessed May 10, 2026, https://hostmerchantservices.com/articles/legacy-payment-systems/

22. From Pilots to Production: How Banks Are Building With AI - Oscilar, accessed May 10, 2026, https://oscilar.com/blog/aibank

23. Next-generation monetary and financial system takes shape, based on a tokenised unified ledger: BIS - Bank for International Settlements, accessed May 10, 2026, https://www.bis.org/press/p250624.htm

24. Tokenization and Unified Ledger: Building the Future Monetary System | Gate Learn, accessed May 10, 2026, https://www.gate.com/learn/articles/from-digitization-to-tokenization-the-unified-ledger-is-building-a-grand-blueprint-for-future-currency/1311

25. Tokenization architecture: Components, patterns, and integration decisions - Nextrope, accessed May 10, 2026, https://nextrope.com/tokenization-architecture-components-patterns-and-integration-decisions

26. Digital Banking System | Business & Consumer Banking - Finzly, accessed May 10, 2026, https://finzly.com/digital-galaxy/

27. Award-winning banking solutions for BaaS, Payments, Treasury & FX, accessed May 10, 2026, https://finzly.com/

28. Finzly Launches Account Galaxy: Embedded Banking Solution with Virtual Account and Virtual Ledger Capabilities, accessed May 10, 2026, https://finzly.com/resources/press-releases/finzly-launches-account-galaxy-embedded-banking-solution-with-virtual-account-and-virtual-ledger-capabilities/

29. How to Identify the Payment Hub That’s Right for Your Financial ..., accessed May 10, 2026, https://finzly.com/resources/blogs/how-to-identify-the-payment-hub-thats-right-for-you/

30. Payment Rails Explained: The Infrastructure Powering Money Movement - SDK.finance, accessed May 10, 2026, https://sdk.finance/blog/payment-rails-explained-the-infrastructure-powering-money-movement/

31. Tokenized Payments Platform for Banks | Deposits & Stablecoins - Finzly, accessed May 10, 2026, https://finzly.com/token-galaxy/

32. Banks ditching point solutions: 5 reasons to unify platforms - Backbase, accessed May 10, 2026, https://www.backbase.com/blog/unified-banking-platform-benefits

33. AI-native banking OS vs AI-powered platform - Backbase, accessed May 10, 2026, https://www.backbase.com/blog/ai-native-vs-ai-powered-banking-platform

34. Core Banking Platforms Compared: Features, Pricing, and Integration Ease | Gemba, accessed May 10, 2026, https://ge.mba/research/core-banking-platforms-compared-features-pricing-and-integration-ease

35. Tokenized Deposits: Models, Use Cases & Infrastructure - Kaleido, accessed May 10, 2026, https://www.kaleido.io/blockchain-blog/tokenized-deposits-models-use-cases-infrastructure

36. A foundation for stable digital money - J.P. Morgan, accessed May 10, 2026, https://www.jpmorgan.com/kinexys/documents/deposit-tokens.pdf

37. Chiara Scotti: Digital money and the architecture of trust - Bank for International Settlements, accessed May 10, 2026, https://www.bis.org/review/r260505d.pdf

38. III. The next-generation monetary and financial system - Bank for International Settlements, accessed May 10, 2026, https://www.bis.org/publ/arpdf/ar2025e3.htm

39. Breaking Down JPMD, JPM Coin, and Stablecoins - WhiteSight, accessed May 10, 2026, https://whitesight.net/infographics/breaking-down-jpmd-jpm-coin-and-stablecoins/

40. It’s Time to Explore Institutional DeFi - Oliver Wyman Forum, accessed May 10, 2026, https://www.oliverwymanforum.com/future-of-money/2022/Nov/institutional-defi.html

41. Compliance Automation in Blockchain Markets - Chainlink, accessed May 10, 2026, https://chain.link/article/blockchain-compliance-automation

42. Compliance is the new payments rail - Lisk - The Growth Platform for EM Founders, accessed May 10, 2026, https://lisk.com/blog/posts/compliance-is-the-new-payments-rail/

43. Compliance-Aware Agentic Payments on Stablecoin Rails - arXiv, accessed May 10, 2026, https://arxiv.org/html/2605.00071v1

44. Onchain KYC: Identity and Compliance for Smart Contracts - Chainlink, accessed May 10, 2026, https://chain.link/article/onchain-kyc

45. Blockchain KYC: How It Works and Use Cases - Chainlink, accessed May 10, 2026, https://chain.link/article/blockchain-kyc

46. Advanced Digital Identity Orchestration Engine for Privacy-Preserving KYC Verification | Request PDF - ResearchGate, accessed May 10, 2026, https://www.researchgate.net/publication/400289457_Advanced_Digital_Identity_Orchestration_Engine_for_Privacy-Preserving_KYC_Verification

47. Why JPMorgan Started Kinexys: The Case for Blockchain in Institutional Settlements, accessed May 10, 2026, https://www.bastion.com/blog/why-jpmorgan-started-kinexys-the-case-for-blockchain-in-institutional-settlements

48. Tokenization in financial services: Delivering value and transformation - PwC, accessed May 10, 2026, https://www.pwc.com/us/en/tech-effect/emerging-tech/tokenization-in-financial-services.html

49. Debt Tokenization: A Guide to Onchain Credit | Chainlink, accessed May 10, 2026, https://chain.link/article/debt-tokenization

50. Key differences between tokenized real-world assets vs traditional securities - MetaMask, accessed May 10, 2026, https://metamask.io/news/tokenized-real-world-assets-vs-traditional-securities

51. Decoding Tokenization Costs: Converting Real World Assets To RWA Tokens - InvestaX, accessed May 10, 2026, https://investax.io/blog/asset-tokenization-costs

52. Builder’s Guide to Multi-Rail Money Movement - Modern Treasury, accessed May 10, 2026, https://www.moderntreasury.com/journal/a-builder-s-guide-to-multi-rail-money-movement

53. Payment Rails in Smart Contract as a Service (SCaaS) Solutions from BPMN Models - MDPI, accessed May 10, 2026, https://www.mdpi.com/1999-5903/18/2/110

54. Stablecoin Payment Rails in 2026: Why Enterprises Are Choosing Multi-Rail Over Vendor Lock-In | Support, accessed May 10, 2026, https://eco.com/support/en/articles/14465844-stablecoin-payment-rails-in-2026-why-enterprises-are-choosing-multi-rail-over-vendor-lock-in

55. American Banker Report: Setting the Stage for Tokenized Money - Finzly, accessed May 10, 2026, https://finzly.com/resources/industry-insights/american-banker-report-setting-the-stage-for-tokenized-money/

56. What Is a Unified Treasury Platform? Why a Fiat-Only TMS Is Now a Strategic Liability, accessed May 10, 2026, https://treasury.ripple.com/de/posts/what-is-a-unified-treasury-platform

57. Digital assets: risks, regulations, mitigation - PMC - NIH, accessed May 10, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC12883517/

58. How Banks Can Mitigate Risks Across the Digital Asset Value Chain - ISG, accessed May 10, 2026, https://isg-one.com/articles/how-banks-can-mitigate-risks-across-the-digital-asset-value-chain

59. Digital assets and banks: A shifting regulatory and risk landscape - WTW, accessed May 10, 2026, https://www.wtwco.com/en-ca/insights/2025/11/digital-assets-and-banks-a-shifting-regulatory-and-risk-landscape

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