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When an AI agent buys something on your behalf, how does the merchant know you authorised it? And who takes responsibility when the purchase goes wrong?
In this episode of WRAP UP, I sit down with Ajoy Krishnamoorthy, CEO of IXOPAY, to explore how payment infrastructure needs to evolve for agentic commerce. Ajoy describes the shift from “card not present” to “human not present”, where verifying an agent’s identity, permissions and intent becomes central to trusting a transaction.
We also discuss why AI could make payment orchestration more valuable, even as it makes integrations easier to build. Drawing on IXOPAY’s experience processing over $200 billion in payments in the preceding 12 months, Ajoy explains how transaction data can help merchants identify better payment routes and test changes before applying them more widely.
Our conversation covers:
A practical conversation about the infrastructure behind autonomous shopping and the work still needed before consumers trust agents to spend independently.
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Stablecoins are often presented as a new way for consumers to pay. Daniel Lev believes their bigger opportunity lies behind the payment experience, connecting cards, bank accounts, wallets and local payment networks.
In this episode of the WRAP UP podcast, I sit down with Daniel, Co-founder and CEO of Coinflow, to discuss how stablecoins can work as invisible payment infrastructure.
Daniel explains how a US customer can pay a UK merchant by card while Coinflow uses stablecoins to settle the transaction across borders. The merchant receives the money in around five seconds and can convert it into pounds without managing stablecoins directly.
Coinflow processes billions of dollars annually for marketplaces, remittance providers, gaming companies, e-commerce merchants and other businesses with complex flows of funds. We discuss the economics of faster settlement, including its impact on FX, payouts and reconciliation.
Daniel also compares Coinflow with Stripe. While Stripe added stablecoins to infrastructure built on traditional financial rails, Coinflow uses stablecoins and public blockchains as its core settlement layer. Daniel argues that this enables businesses to receive money in seconds rather than waiting one to three days.
We also explore why merchants and consumers may never need to know stablecoins are involved. They can simply see, withdraw and use their balance while the underlying infrastructure remains invisible.
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LinkedIn: https://www.linkedin.com/in/sirojboboev/
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Software companies have spent years embedding payments, yet many still earn nothing from transactions flowing through their existing customer base. Could that be their biggest missed opportunity?
In this episode of the WRAP UP podcast, I sit down with Ben Weiner, Global Head of Partner Channel at Nuvei, to explore where payments growth comes from as AI changes the software business.
Ben explains why winning new customers with payments built in is only part of the job. He says sophisticated software vendors attach payments to 80–100% of new customers, while older customers often remain on separate providers. Reaching that installed base requires a clear reason to switch, better reconciliation and someone internally accountable for adoption.
We also discuss:
I also challenge Ben on whether AI companies will build their own payment infrastructure, and we discuss why trust and unresolved liability could slow the move towards fully autonomous purchases.
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What happens when AI agents become part of the workforce? Will companies eventually pay taxes on AI agents? And could stablecoins replace traditional banking infrastructure for global payroll?
In this episode of the WRAP UP podcast, I sit down with Eynat Guez, CEO and co-founder of Papaya Global, to discuss how artificial intelligence and stablecoins are reshaping global employment, payroll and cross-border payments.
Papaya Global has evolved from a workforce management platform into a global payments business processing close to $50 billion annually, according to Eynat.
She shares how Papaya has reduced its human marketing team by roughly half while tripling its use of AI agents. She also predicts that employees will soon manage multiple AI agents and that governments could eventually introduce taxes based on AI token consumption.
We explore why Eynat still refuses to give AI agents direct access to payment systems, despite her confidence in the technology.
The conversation then turns to stablecoins. Eynat explains why Papaya is already using stablecoin rails to move money internationally and predicts that demand for stablecoin payments could reach 30–40% within two years.
In this episode, we discuss:
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Will AI agents eventually manage our investments? Could tokenization make stock markets accessible 24/7? And will we still need trading apps in the future?
In this episode of the WRAP UP podcast, I sit down with Jordan Sinclair, President of Robinhood UK, to explore how artificial intelligence, blockchain technology, and changing consumer expectations are reshaping the future of investing.
Robinhood is expanding beyond traditional stock trading into crypto, tokenized assets, prediction markets, and AI-powered investing. But the wider financial industry is undergoing a similar transformation, with companies like Revolut and Coinbase competing to become the primary financial platform for consumers.
One of the most interesting parts of our conversation was about the role of AI agents in investing.
Robinhood has already introduced agentic trading capabilities in the US, allowing customers to connect AI agents to their investment accounts, allocate funds, and define trading rules.
I asked Jordan a question I've been thinking about for some time: If my AI agent can research markets, access my portfolio, and execute trades, why would I still need a trading app?
We also explored the potential of tokenization to change how financial assets are owned and transferred. Today, moving stocks between brokers can take weeks. Blockchain-based infrastructure could make these transfers much faster and enable trading outside traditional market hours.
Another topic we discussed was the growing popularity of prediction markets. As trading volumes increase, where should regulators draw the line between financial instruments and gambling?
In this episode, we discuss:
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What happens when one of the UK’s largest banks puts AI at the centre of how it serves millions of customers?
In this episode of WRAP UP, I sit down with Suresh Balaji, Chief Marketing Officer of Lloyds Banking Group, to discuss how Lloyds is approaching AI, agentic systems, customer trust and the future of banking.
Lloyds serves around 28 million customers, with 23 million interacting with the group digitally and billions of app logins every year. Now, the bank is testing an AI assistant designed to help customers discover financial products, receive proactive support and better manage their financial lives.
We discuss:
• Why Lloyds already has its consumer AI assistant in beta • Where AI could first appear inside the Lloyds banking app • Why fraud prevention could become one of banking’s most valuable AI use cases • How Lloyds built Cortex and its Envoy “agent factory” • Why Lloyds believes AI needs governance, testing and lifecycle management • How one internal AI agent reduced an eight-week process to around 30 minutes • What Lloyds learned when it tested humans vs AI vs humans working with AI • Why Suresh believes it should be “humans in the lead,” rather than simply humans in the loop • How AI is changing financial-services discovery and marketing • Why trust could become an even bigger competitive advantage in AI-powered banking • Whether legacy banks can use their data and scale to compete with digital challengers • The role AI could play in Britain’s wider economic competitiveness
Suresh also explains Lloyds’ three-part framework for transformation: tasks, tools and talent, and why giving employees access to AI may matter just as much as choosing the underlying models.
A conversation about what AI looks like when it moves beyond experimentation and starts being deployed across one of Britain’s biggest banking groups.
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AI agents are beginning to shop, negotiate and make payments on behalf of consumers and businesses. But most payment infrastructure, compliance rules and liability frameworks were designed for humans.
In this episode of the WRAP UP Podcast, I sit down with Philip Bruno, Chief Strategy and Growth Officer at ACI Worldwide, to explore how the payments industry must adapt to the emerging machine economy.
We discuss why merchants may need to stop blocking bots and start distinguishing trusted customer agents from malicious ones. Philip explains why businesses should remain independent of any single agentic commerce protocol and how payment orchestration could help them support new protocols, rails and payment methods without losing control of their customer relationships.
We also examine one of the biggest unanswered questions in agentic commerce: who is liable when an AI agent makes a mistake? Philip shares his view on how today’s payment rules are being applied to agent-led transactions and why new commercial and regulatory frameworks will be needed.
The conversation then turns to what Philip calls the “three-horse race” between stablecoins, tokenised bank deposits and instant payments. We break down where each option could succeed, why instant payments may eventually overtake debit cards globally, and how stablecoins could become especially important for cross-border payments and markets with unstable currencies.
Philip also explains ACI Worldwide’s approach to intelligent payment orchestration, including technology that can identify transactions likely to fail, recommend repairs and reduce the time required to fix a wire payment from around 40 minutes to two minutes.
We also discuss:
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What does it take to turn one of the world’s largest digital banks into an AI-first company?
In this episode of the WRAP UP podcast, I sit down with Eric Young, CTO of Nubank, to discuss how the company is using AI across engineering, credit, and customer experiences.
Nubank has reported that its weekly AI token use grew almost 10x since the beginning of the year, while engineering productivity increased by 50% and testing cycles became 90% faster. Eric explains how the company thinks about the return on that investment, why there is no single perfect productivity metric, and how Nubank measures changes in code delivery, product velocity and automation without reducing the work to a simplistic scorecard.
We discuss why Nubank is not betting on one AI provider or one model. Eric shares how the company dynamically routes workloads across different models based on performance, cost and quality, while also exploring self-hosted open-weight models. He explains why flexibility matters in a market where model capabilities are shifting quickly.
Eric also takes us inside Nubank’s own foundation-model work. With 135 million customers and hundreds of terabytes of financial and app-event data flowing through the platform each year, Nubank is building models that can better understand financial behaviour, improve credit decisions, support responsible lending and personalise experiences at scale.
We also discuss the harder side of AI in banking:
• How AI can help banks detect fraud patterns in real time
• Why clean, structured data can be a bigger advantage than simply having more data
• How Nubank tests and evaluates AI systems before exposing them to customers
• Where human oversight remains essential when AI interacts with financial decisions
• How the company approaches accountability, guardrails and customer protection
• Why incumbents with decades of data may still struggle if their data is fragmented or poorly structured
• What Nubank sees as the real competitive challenge: rising customer expectations
• The skills engineers, product managers and designers need to succeed in an AI-first organisation
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LinkedIn: https://www.linkedin.com/in/sirojboboev/
Newsletter: https://www.fintechwrapup.com/
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AI has made fraud cheaper, faster, and harder to spot. Deepfakes can pass visual checks, agents can move through websites on behalf of users, and fraud rings are buying real accounts through Telegram marketplaces.
In this episode of WRAP UP, I sit down with Tamas Kadar, co-founder and CEO of SEON, to discuss how AI is making online fraud more sophisticated and what banks, fintechs and digital businesses can do to stop it.
We explore how deepfakes, synthetic identities and AI agents are helping fraudsters automate attacks at scale. Tamas explains why a face, document or video is no longer enough to verify a customer, and why fraud detection now needs to go beyond a single KYC check.
We discuss the signals that matter, including email, phone, IP, device intelligence, digital footprints and behavioural data. Tamas explains why risk teams need to monitor the full customer journey, from registration and onboarding to login and transaction, rather than rely on separate tools that only assess risk at one point in time.
We also cover account takeover through breached credentials and the growing threat of account handover, where real people open verified accounts that are later sold through Telegram and dark web marketplaces. These accounts can then be used for mule activity, scams and moving illicit funds.
Tamas shares how SEON has expanded its risk intelligence to more than 1,100 signals, how financial institutions can combine this data with their own internal AI models, and why dynamic friction is key: letting genuine customers move smoothly while introducing extra verification only when activity looks suspicious.
Finally, we discuss what banks and fintechs should do now to prepare for AI-driven fraud, including how to handle AI agents, why live proofs of concept matter when selecting a fraud platform, and why simple integration should be part of every vendor decision.
Learn more about SEON: https://seon.io/editions/signal-intelligence-2026/?utm_source=seon&utm_medium=fintech-wrap-up&utm_campaign=podcast_fintech-wrap-up-podcast-launch_fy26-q3&utm_content=
For most people, buying a US stock is simple. For millions across Central Asia, Latin America, Africa and other parts of the world, it can still mean high barriers, limited access and a long process to open a brokerage account.
Tokenized equities could change that.
In this episode of WRAP UP, I sit down with Mark Greenberg, Chief Commercial Officer of Kraken/Payward, to discuss whether tokenized stocks can give more people access to global markets, starting with as little as $5 or $10.
We talk about what Kraken has learned from building XStocks, which has processed almost $40 billion in volume, and why the real opportunity is not only bringing stocks onchain. It is making access to equities possible for people who have been excluded from global capital markets for years.
Mark also explains why stablecoins are becoming more than a trading tool. We discuss dollar yield, cross-border B2B payments, the slow progress of stablecoin remittances and why moving money and trading assets are increasingly part of the same infrastructure problem.
We also discuss:
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LinkedIn: https://www.linkedin.com/in/sirojboboev/
Newsletter: https://www.fintechwrapup.com/
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