Solving Scams as a Second Time Founder

Solving Scams as a Second Time Founder

In this episode I spoke to Nicky Goulimis, co-founder and CEO of TunicPay, about why she started a second company, what TunicPay is building, and how they’ve managed to land some of the UK’s biggest banks as customers in under three years. Here’s what we covered: •       What it’s really like to start a second company •       The difference between fraud and scams  •       Why all of the fraud defences banks have built over 20 years don’t work for scams •       How TunicPay’s payment context protocol works •       Who should bear liability for scams  •       How TunicPay landed major UK banks as their first customers, and how they navigated those organisations •       How they’re thinking about entering the US market, where the bank liability model is completely different •       Why Nicky thinks FinTech has been unambitious about scams, and what she’d like to see If you work in financial services, fraud, or payments - or if you’ve ever been close to being scammed - you should listen to this episode. Timestamps: 00:00 Nicky's Entrepreneurial Journey 13:05 Solving scams 20:18 Understanding Liability in Fraud Prevention 25:15 Stopping scams in real time 32:06 Navigating Partnerships with Major Banks 38:12 Expanding into the U.S. Market This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit natashavernier.substack.com [https://natashavernier.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

What Good B2B Marketing Looks Like with Colton Pond

In this episode I spoke to Colton Pond, CMO at Socure, about how to build B2B marketing that actually drives revenue. Colton has spent 10 years leading marketing at FinTech companies including MX, Truv, Loan Pro, and Socure, and he has very strong opinions. Here’s what we covered: - What founders get wrong about marketing, and why most marketers are too fluffy to become founders - How to think about marketing at seed stage — focus, low-noise channels, and guerrilla tactics - When to hire a marketing lead and what to look for - Why MQLs are a swear word, and what metrics actually matter - How marketing strategy changes at Series A/B vs Series C/D - When to launch your own conference — and when not to - How AI is changing content marketing, and how to use it without producing slop - People and purpose over profit — and the mentor who taught him that If you’re building a B2B startup, or leading marketing at one, you should listen to this episode. Timestamps: 00:00 The Journey of Colton Pond 10:54 Marketing Strategies for Startups 24:03 Scaling Marketing Efforts in Series A and B 28:29 Rethinking Marketing Metrics 37:49 The Importance of Community and Conferences 43:18 Hiring Strategies for Growth Stages 46:09 AI's Transformative Role in Marketing 51:05 The Mindset of Successful Marketers This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit natashavernier.substack.com [https://natashavernier.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

Understanding Stablecoins

Stablecoins keep coming up. In news, in fintech conversations, in the context of regulation. And while I keep nodding along, I can’t really see beyond the use case of international transactions.  Why else would anyone use them? And is there a consumer use-case?  So I asked Peter Glyman, who has spent years working at the intersection of payments, blockchain, and financial services, to help me understand it all. Here’s what we covered: What stablecoins are, how they differ from cryptocurrencies, and how the blockchain works as the underlying ledger How pegging to the US dollar works in practice, and what the Genius Act requires of stablecoin issuers The strongest real-world use cases: cross-border payments, merchant payments, and programmable smart contracts What tokenized deposits are, and why banks might prefer them to stablecoins The decentralisation question - what it actually means (and doesn't) when companies like Circle and Coinbase are centralised entities Whether traditional banks will adapt to stablecoin technology or get disrupted by new blockchain-first players If you work in financial services, payments, or fintech, you should probably listen to this episode. Timestamps: 00:00 What is a stablecoin? 03:24 Blockchains, distributed ledgers, and different blockchain architectures 08:49 How Circle became a stablecoin provider 11:35 The Genius Act and what it requires 18:30 How pegging to the dollar actually works 19:16 The 2023 USDC de-peg and what actually happened 21:06 Real-world use cases: payments, remittances, and programmability 24:14 Tokenized deposits — and why banks may prefer them 27:11 Decentralisation: what it actually means (and doesn’t) 33:15 Opportunities still to be built 37:13 Will banks be disrupted or will they adapt? This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit natashavernier.substack.com [https://natashavernier.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

AI and Actually Good Customer Support

Listen on Apple Podcasts [https://podcasts.apple.com/gb/podcast/in-control-with-natasha-vernier/id1866655597] or Spotify [https://open.spotify.com/show/3uQxpRfmjpKlaxJcJZNUZs?si=db7e687731994d1e] Everyone already seems to know everything about AI and LLMs. I think I missed the part where the basic questions were asked and answered, and given AI will almost certainly be a core part of all our lives, that felt like a gap worth closing. Luckily, my good friend Dimitri Masin, CEO and Co-founder of Gradient Labs (which builds customer operation agents for financial services), knows all about it, and was willing to answer my “stupid” questions. So, I finally understand why the frontier LLMs cost so much to build, how the training actually happens, and how to build actually useful agents with them. 00:00 Understanding the basics of AI 10:29 Model context windows 13:33 Open sourced LLMs 18:26 Automating customer support with agents 26:43 Why brand matters more than ever, and how to measure AI performance 32:23 Agents for back office operations 36:38 Gradient Lab's Co founders This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit natashavernier.substack.com [https://natashavernier.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

Enabling Banks to Use AI

In this episode I spoke to Kareem Saleh, the CEO of Fairplay, about how banks can use AI safely. Fairplay is a technology that tests, tunes and validates models for banks, and so he was the perfect person to ask about the risks - and mitigators - of generative AI within financial services.  Here’s what we talked about: - How banks have always used machine learning models, and what is different with generative AI - The risks that gen AI and agents bring to banks - Practical tips on how to mitigate those risks - How banks can evidence to the regulators that they are using AI safely - Why banks may end up having to have 2 systems - their AI native system, and a secondary non-AI system as a failsafe - What keeps Kareem up at night If you work in a bank or fintech, you should listen to this episode. 00:00 Introduction to AI in Banking 02:44 The Old World of Machine Learning in Banks 09:44 Risks Associated with Generative AI 16:32 Potential Consumer Harms and Institutional Risks 19:32 Managing AI Risks in Banking 25:28 Guarding Against Hallucinations and Runaway Behaviors in AI 31:35 Regulatory Compliance and Risk Appetite 34:46 Future of AI in Banking  This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit natashavernier.substack.com [https://natashavernier.substack.com?utm_medium=podcast&utm_campaign=CTA_1]