Making and moving stablecoins; Process of Network Tokenisation: Key Actors; Q4 2024 FinTech Partnerships Summary;
In this edition of Fintech Wrap Up, we’re diving into AI innovations in banking and the rapid evolution of stablecoins are redefining the future of finance
Insights & Reports:
TL;DR:
In this edition of Fintech Wrap-Up, we’re diving into some exciting shifts in banking, payments, and crypto. Banks are making serious strides with AI, achieving up to a 10% revenue boost by scaling over 50 machine learning models and embedding smarter risk management. One major bank is already using AI-driven tools to consolidate customer leads and optimize sales strategies across 150+ use cases. Stablecoins are evolving rapidly—from fiat-backed giants like USDT (with 6% over-collateralization) to over-collateralized options like MakerDAO’s DAI and risk-hedged models like Ethena Lab’s USDe. Algorithmic stablecoins, however, remain risky—as TerraUSD's $40 billion collapse showed.
Fraud continues to challenge the industry, especially in crypto and banking, with APAC leading global fraud rates at 6.8%. Biometric authentication with liveness detection is proving more effective than traditional document checks in fighting fraud. On the payments front, network tokenization is securing digital wallets, with Mastercard’s Payment Passkey expanding across Latin America and the UAE, enabling safer, biometric-authenticated transactions.
Looking into 2025, stablecoins and blockchain are set to lead cross-border payments, with generative AI driving operational efficiencies. The account-to-account (A2A) payment space is projected to grow 161% between 2024 and 2028, but it comes with rising fraud risks like authorized push payment (APP) scams. Meanwhile, fintech partnerships are booming—128 deals were sealed last quarter! Key moves include Revolut entering private banking to compete with UBS and Morgan Stanley, Brex securing a $235M credit facility to expand its card products, and Klarna teaming up with Stripe to bring BNPL services to 26 countries—a strategic step ahead of its U.S. IPO.
Exciting times for fintech! Let’s keep exploring what’s next.
Insights & Reports?
2 Weeks, 7 Interviews, and 3 Hypotheses: My AI Agent Customer Development Journey in Fintech and Payments?
I’ve spent the last two weeks diving deeper into how AI agents can truly add value to fintech and payment companies. I’m sharing a summary of my journey in the attached image, and I’m now ready to move to the next stage—and I need your help.
?? How You Can Help
I’m looking to validate or invalidate these hypotheses through more conversations. If you’re in fintech, payments, or even tangentially involved in financial operations, I’d love to hear your experiences:
?? What challenges are you seeing in financial infrastructure, reconciliation, or AP/AR?
?? How have you tackled them—or wished you could tackle them with AI/automation?
Your insights will help shape potential solutions. So if you’re up for a 15-30 minute chat, please reach out or comment below and let’s connect. I’m excited to see where this journey takes us—and how we might transform fintech workflows together.
Thank you to everyone who has already shared their perspectives.
Feel free to like, comment, or DM me if you’re interested in a quick conversation.
Banking: Sustaining and scaling value from AI
领英推荐
A successful AI transformation of a bank balances delivering a positive financial impact in the near term with building lasting AI capabilities for the enterprise.
After setting a business strategy with AI at its core and choosing the domains and subdomains to be transformed with AI, banks should focus on executing that transformation at scale, delivering value from the reusable components that can be created for one domain and then plugged into other domains as needed.
For example, a large bank is going through a multiyear transformation focused on improving performance and delivering analytics at scale with use cases including hyperpersonalization to target new customers and cross-sell to existing customers. The bank built reusable assets and an end-to-end analytics pipeline powering more than 50 machine learning models, developed a tool to consolidate customer leads from different sources and optimize them based on various factors, and built a fit-for-purpose, data-driven business operating model. Early results are promising, with projected revenue increases of 10 percent and usage of the resulting assets and framework in more than 150 use cases.
A transformation begins with one subdomain and the development of various use cases in that subdomain, moving through several phases, from minimal viable product to more sophisticated stages. As the transformation proceeds, reusable components from use cases in the first subdomain can be used in other subdomains. This process necessitates building and improving the AI stack in phases, as opposed to trying to create it all at once.
Implementing an AI stack alone isn’t enough; banks must address key organizational and strategic imperatives to scale AI effectively:
Four major types of stablecoins
Stablecoins can be categorised into four different types by their reserve composition, reserve maintenance, and pegging mechanism:
?? Fiat-referenced stablecoins
Fiat-referenced stablecoins are linked to a fiat currency by maintaining reserves in traditional, highly liquid assets.
To purchase fiat-backed stablecoins, buyers request the purchase and deposit fiat off-chain before receiving the newly-issued coins on-chain. These stablecoins can be traded on the secondary market. Sellers follow a similar route to return fiat-backed stablecoins and withdraw fiat.
One example of fiat-backed stablecoins is Tether USDT, whose reserve is over-collateralised by 6%, with only ~0.1% of the cash-equivalent reserve composed of cash and bank deposits.
?? Crypto-backed (over-collateralised) stablecoins
Crypto-backed stablecoins can over-collateralise to ensure higher stability.
Instead of “buying” stablecoins, buyers receive stablecoins as crypto-backed loans from the issuer and stake cryptoassets as the collateral in the reserve. To redeem the stablecoin, buyers repay the principal asset with relevant interests to receive the collateral. As no fiat is involved in the collateralisation, the whole process is completely on-chain.
One example of a crypto-backed stablecoin that is over-collateralised is MakerDAO’s DAI.?
Curated News
Brex Secures $235 Million Credit Facility with Citi and TPG Angelo Gordon to Accelerate Card Product Growth
This credit facility, combined with Brex's existing warehouse facilities and master securitization trust—through which the company has closed three securitization issuances to date— will act to further support Brex's recent growth acceleration and expand its ability to provide industry-leading global corporate cards, coupled with expense management, travel, banking, and bill pay solutions, to customers ranging from startups to global enterprises.
Related Articles
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. For questions or concerns, please contact us at [email protected].
Founder & Board Advisor | Fintechs | Emerging Tech | Payments | Financial Inclusion G20 GPFI | Open Banking & Finance | Public Policy | Keynote Speaker | Investor | Former HSBC, VISA, Maersk
1 个月Finance is being redefined by AI and stablecoins. Growth will favor not the fastest, but those who scale smartly, secure trust, and turn disruption into lasting impact!
civil Engineer
1 个月U need sites for guest posting