Reports: Building an AI Stack for Banking on AWS; Stablecoins and the Future of Onchain Finance; The Complete Guide to Mobile Wallets 2025;

Let’s dive into this week’s curated collection of fintech reports, whitepapers, and expert guidelines in the latest edition of Fintech Wrap Up. Every resource featured is available for download

Insights & Reports:

1️⃣ Building an AI Stack for Banking on AWS

2️⃣ 2nd Global Cryptoasset Regulatory Landscape Study

3️⃣ The Complete Guide to Mobile Wallets 2025

4️⃣ Stablecoins and the Future of Onchain Finance

5️⃣ Digital commerce payment preferences by region 2025

6️⃣ Crypto Asset Risk Report 2025

7️⃣ Diverse Fraud Attack Vectors

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TL;DR:

Welcome to this edition of the Fintech Wrap Up, where we unpack the latest in AI, crypto, digital wallets, and global payments.

Banks are embracing AI but often struggle to scale beyond pilots. AWS outlines how to build production-ready stacks by starting small, focusing on governance, and aligning teams across tech and finance.

Crypto regulation remains patchy—less than half of jurisdictions have rules in place. Advanced economies lead on stablecoins, while EMDEs often opt for bans. Tokenisation, staking, and advertising continue to see fragmented oversight.

Digital wallets are going mainstream, expected to reach 4 billion users by 2029. They’re transforming payments for merchants and consumers alike, while also serving the underbanked in emerging markets.

Stablecoins are reshaping cross-border payments, B2C payouts, and corporate treasury. With faster, cheaper, and more transparent dollar flows, they’re becoming essential in inflation-prone regions.

Payment trends vary by region: APAC leads in wallet adoption, LatAm in A2A growth, and Europe in diversity. Meanwhile, fraud is getting more sophisticated, with AI-powered scams and multi-channel attacks raising the stakes for detection and defense.

Thanks for reading the Fintech Wrap Up—see you next time!

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Insights

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Reports

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Building an AI Stack for Banking on AWS

Banks are experimenting with generative AI (gen AI) and machine learning (ML), but many struggle to operationalize these technologies at scale. The key challenge is not identifying use cases but implementing a reliable, well-governed, and scalable AI stack that delivers business value while complying with strict regulatory requirements.

👉 Key Challenges

- Many banks are stuck in proof-of-concept (POC) cycles without transitioning to production.

- Concerns about regulatory compliance, model transparency, and risk management make adoption harder.

- The rapid pace of gen AI evolution adds further complexity.

👉 Strategic Focus Areas

AWS identifies six core components banks should consider when building an AI stack:

1. Technology

Divided into:

- Foundational components: model gateways, evaluation tools, guardrails, monitoring, observability, CI/CD pipelines, agent builders, RAG systems, prompt managers, fine-tuning tools.

- Blueprints/templates: ready frameworks for common tasks like search, summarization, translation, and content generation.

- Ready-to-use applications: enhanced tools for ESG analysis, customer onboarding, mortgage processing, etc.

2. Organizational Structure

- Models include centralized, decentralized, and mixed.