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The Fintech Blueprint

The Fintech Blueprint

By: Lex Sokolin
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Finance is being pulled apart by the forces of frontier technology. From AI, to blockchain and DeFi, mixed reality, chatbots, neobanks, and roboadvisors — the industry will never be the same. Here is the blueprint for navigating the shift.2021 The FinTech Blueprint Economics Leadership Management & Leadership Personal Finance
Episodes
  • How zerohash won Morgan Stanley's crypto business

    How zerohash won Morgan Stanley's crypto business
    Sep 10 2026
    In this episode, Lex chats with Edward Woodford — Founder and CEO of zerohash, a crypto and stablecoin infrastructure platform that lets banks, brokers, and fintechs embed digital-asset trading, payments, and tokenization through a single API. Four years on from their last conversation, zerohash has settled over $65 billion in volume across 7 million customers, gone global under MiCA and EMI licensing in Europe, and onboarded institutions like Morgan Stanley.They discuss the pivot from embedded crypto to pure-play B2B infrastructure, and why the product zerohash actually sells is trust — with licensing treated as a bar, not a goal — in a world where state actors are now the primary threat.Edward breaks down the three core rails (Trade, Transact at roughly 70% of revenue, and Tokenization), and unpacks the emergence of "on-chain money" as a legally fragmented category — stablecoins under GENIUS, tokenized deposits, tokenized money-market funds, and CBDCs, each a distinct form of dollar created inside twelve months. They explore how velocity of money and just-in-time funding reshape SME payroll, why the new Auth product aims to be the open banking of stablecoins, and where the industry sits on an S-curve Edward insists is still nowhere near maturity. Finally, they take a skeptical pass at the machine economy, landing on agent-to-knowledge payment — not consumer micropayments — as the durable intersection of stablecoins and AI, and on the convergence that will pull traditional and crypto-native payment firms into aggressive consolidation.We recorded the podcast earlier in the year, and everything that Edward teased in his conversation has come to market. The E-Trade integration is live. The staking infrastructure has launched. The Treasury published the first proposed rules under the Genius Act, so you can see how those predictions came to market. Also, Stripe and Visa answered his M&A predictions with something even bigger: 140 Company Stablecoin Consortium.NOTABLE DISCUSSION POINTS:Trust is the product; licensing is just table stakes. Edward’s sharpest framing is that “licensing is a bar, not the goal” - getting licensed actually opens you to new risks to manage at scale. For an FI like Morgan Stanley, whose crypto revenue is trivial next to tens of billions in quarterly profit, the deciding factor isn’t upside but de-risked entry: FIPS/government-grade compliance, an eight-year clean track record, and a threat model that now treats state actors as the primary adversary.“On-chain money” has fractured into distinct legal categories in under a year. Post-GENIUS and MiCA, stablecoins (backed 100% by short-term government debt) are now legally separate from tokenized bank deposits (e.g. JPMorgan), tokenized money-market funds, and CBDCs - each a different form of dollar. Edward predicts this taxonomy keeps multiplying, and treats the resulting complexity, including cross-chain stablecoin interoperability, as a widening moat rather than a nuisance.The real AI-stablecoin use case is agent-to-knowledge payment, not micropayments. Edward pushes back on the popular “sub-penny real-time micropayments” narrative - invoking iTunes, where payments got batched rather than charged per song. The durable edge, he argues, is a globally programmable rail where an agent in Mozambique can settle with a content creator in Brazil, with knowledge released on a DvP basis as payment clears. Sub-penny amounts get aggregated into daily or weekly batches.TOPICSStablecoins, EmbeddedFinance, Tokenization, DigitalAssets, Payments, GENIUSAct, MiCA, AgenticPayments, DeFi, RWA, Web3, Fintech, zerohash, MorganStanley, Gusto, Stripe, Circle, Tether, Plaid, Mastercard ABOUT THE FINTECH BLUEPRINT🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV👉 Twitter: https://twitter.com/LexSokolin TIMESTAMPS2’54: From 5% of Ethereum to $65 billion settled: four years of scaling without trading off trust6’19: The everything app comes full circle: from embedded crypto to one infrastructure engine11’29: Interoperability as the value prop: bridging USDC across ETH, Polygon, and Canton16’06: Build, buy, or rent: how zerohash wins the decision inside a firm with billions in profit18’47: Stablecoins are good, crypto is bad: the market's false divide and why zerohash rejects it26’18: Auth, the open banking of stablecoins: killing the two questions that break usability29’55: The next 24 months of consolidation: will Circle, Tether, and zerohash buy the traditional players?37’22: The Fortune 500 is barely penetrated: what usability and distribution unlock next41’10: Agent-to-knowledge transfer: the real intersection of stablecoins and AI, beyond the sneaker purchase46’41: The channels used to connect with Edward & learn more about zerohash Disclaimer here — this ...
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    47 mins
  • Building the AI Distribution Layer for 5000+ Banks, with Fiserv Co-Head of Financial Solutions Srini Krish

    Building the AI Distribution Layer for 5000+ Banks, with Fiserv Co-Head of Financial Solutions Srini Krish
    Aug 10 2026
    In this episode, Lex chats with Srini Krish — Co-Head of Financial Solutions at Fiserv, one of the original fintechs, in business for nearly five decades and sitting at the intersection of commerce and banking. Lex and Srini discuss how Fiserv acts as the technology backbone for 5,000+ US banks and credit unions that lack the wherewithal to match JPMorgan or Wells Fargo on their own, and how the firm is packaging AI into that distribution layer through Agent OS and partnerships with OpenAI and Anthropic. Srini lays out his four-bucket framework for enterprise AI - better client service, internal productivity, AI embedded in products, and a platform banks can use to build their own agents - and explains why money demands deterministic outcomes rather than probabilistic guesses, keeping a human in the middle as commercial loan underwriting compresses from weeks to hours. They explore the competitive race against challengers like Mercury and Ramp, the mainframe that has outlived thirty years of obituaries, and where power sits between the AI labs and their distribution channels once inference commoditizes. NOTABLE DISCUSSION POINTS: MIPS became tokens. Srini frames the whole AI shift through continuity: engineers once measured effectiveness by MIPS consumed and how often they compiled code; today the metric is token consumption. Same discipline of doing more with minimal resource, thirty years apart.Money forces determinism. Probabilistic outputs are fine for many tasks but unacceptable for balances - a figure 1% or 5% off is a failure, it has to be right every time. So Fiserv’s Agent OS rollout starts with non-real-time, human-in-the-middle use cases and only graduates toward autonomy and eventually customer-built agents. It’s a crawl-walk-run path, and Fiserv says it’s clearly still crawling.The moat is distribution, not model access. Fiserv’s 5,000+ banks and credit unions can’t engage OpenAI or Anthropic directly at scale, so Fiserv becomes the platform that packages agentic workflows - turning commercial loan decisions from a multi-week process into hours, with the auditability and observability those institutions could never build alone. TOPICS Fintech, Fiserv, EmbeddedFinance, AgenticAI, EnterpriseAI, Banking, Payments, DigitalBanking, CommunityBanks, FinancialInfrastructure, AIAgents, OpenAI, Anthropic, ClaudeCode, JPMorganChase, FirstData, Mercury, Ramp, Plaid ABOUT THE FINTECH BLUEPRINT 🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2 🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV 👉 Twitter: https://twitter.com/LexSokolin TIMESTAMPS 1’12: Fintech Before It Was Fashionable: Five Decades at the Intersection of Commerce and Banking 6’13: Access, Move, Trust: What Actually Defines a Fintech Across Three Decades 10’28: A Loan at the Mechanic's Shop: How Embedded Finance Widened the Market and the Money Behind It 13’22: Four Buckets for Enterprise AI: Where Agent OS and the OpenAI Partnership Actually Fit 20’47: Not Savviness but Wherewithal: Why 5,000 Institutions Can't Build JPMorgan's Stack Alone 25’39: Mercury, Ramp, and the Mainframe That Never Died: Why the Incumbents Aren't Going Anywhere 29’51: Both Labs, All Three Clouds: Why the Distribution Channel Sits in the Middle 33’16: The Engineer Who Stops Writing Code: Why Replacement and Expansion Can Both Be True 36’50: It Has to Be 100% Correct Every Time: Why Money Demands Deterministic AI Disclaimer here — this newsletter does not provide investment advice and represents solely the views and opinions of FINTECH BLUEPRINT LTD.Contributors: Lex, Laurence, Matt, Farhad, Mike, DaniellaWant to discuss? Stop by our Discord and reach out here with questions.
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    41 mins
  • How Perplexity's Computer Is Replacing the Family Office, with Perplexity Finance’s Jeff Grimes

    How Perplexity's Computer Is Replacing the Family Office, with Perplexity Finance’s Jeff Grimes
    Jul 20 2026
    In this episode, Lex chats with Jeff Grimes — who is Head of Live Events Products at Perplexity, the AI company that has evolved from an "answer engine" into an "agent platform" built around Perplexity Computer, its multi-agent digital worker. They discuss how Perplexity has shifted financial research from the how to the what, letting a user describe an outcome in a single sentence while Computer orchestrates 20+ frontier models, direct tool calls to licensed live data, and finance-specific skills to produce the artifact. Jeff explains the enterprise strategy behind traceability - the north star that 100% of every quantitative figure traces back to its source filing - alongside bring-your-own-license connections via MCP and the consumer "personal CFO" vision powered by Plaid. They explore what 5x revenue growth on a 34% headcount increase signals for finance jobs, and why the future looks like a 24/7 family office that proactively surfaces and, with permission, executes financial actions for everyone. NOTABLE DISCUSSION POINTS: The “how to what” collapse is the real product thesis, not just better models. The shift to zero-shot rests on three stacked unlocks: direct tool calls to licensed live data (Quartr for earnings transcripts, unusual whales for insider and political holdings, SEC filings for historicals) instead of relying on web freshness; a thinking-model router that orchestrates 20+ frontier models in parallel, matching the model to the job (a heavy thinking model for macro analysis, a lighter one for ticker-matching 550 names); and ~20 opinionated finance skills (DCF, three-statement, LBO, comps) tuned through expert-led evals. Together they turn one sentence into a polished equity-research artifact.Traceability is the enterprise wedge, framed as “don’t trust and verify.” The stated north star is that 100% of every number in any output is hover-traceable back to the source filing - pre-scrolled to the page, highlighted, with the full chain of calculations exposed. The framing inverts the usual “trust but verify”: assume the user won’t trust the model, so trust must be earned per number. Paired with bring-your-own-license via MCP (FactSet, LSEG, Morningstar, CarbonArc, PitchBook), this is the concrete answer to why regulated institutions get comfortable adopting.The productivity and jobs signal is quantified and lived internally. Perplexity grew annual run rate 5x while increasing headcount only ~34%. Computer began as a company-wide Slack bot where every request was visible to all employees; Jeff now runs 9–10 scheduled cron jobs each morning and says essentially all code is written first by his agents. On the consumer side, the emergent pattern is build-your-own long-tail apps that no roadmap-bound product could serve - a DraftKings-addiction accountability system that emails a user’s spouse on any bet, or a GitHub-style heatmap of daily spending - which is the real substance of the personal-CFO bet. TOPICS Perplexity, Perplexity Computer, Perplexity AI, Google, Shadebot, Plaid, Yodlee, Claude, ChatGPT, AI, Artificial Intelligence, LLM, CFO, financial services, AI commerce ABOUT THE FINTECH BLUEPRINT 🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2 🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV 👉 Twitter: https://twitter.com/LexSokolin TIMESTAMPS 1’05: A company built on failed founders: Why the startup that didn't work out led here 5’10: A playing card company that became Nintendo: How curiosity carried Perplexity from answers to actions 9’52: We're basically at zero shot now: Why prompt engineering is disappearing from finance work 15’21: A thinking model that routes the job: How Perplexity picks Claude Opus for macro and Grok for tickers 20’12: Two tracks, one engine: Building for enterprise workflows and a personal CFO at once 25’25: Bring your own license, or use ours: How Perplexity gets institutions comfortable enough to adopt 32’54: 5x revenue on 34% more headcount: The productivity gain Perplexity lived firsthand 37’28: Connect everything from your mortgage to the painting on your wall: Building the true personal CFO 45’15: A family office that works 24/7 for everyone: The proactive, automated future of the personal CFO 48’01: The channels used to connect with Jeff & learn more about Perplexity Computer Disclaimer here — this newsletter does not provide investment advice and represents solely the views and opinions of FINTECH BLUEPRINT LTD.Contributors: Lex, Laurence, Matt, Farhad, Mike, DaniellaWant to discuss? Stop by our Discord and reach out here with questions.
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    49 mins
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