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

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

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?

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

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 episode is absolutely jam packed with great insights, such as:

- How to ACTUALLY measure product market fit. It’s the most important, and least well defined, term in startups… until now. Turns out, it’s all about retention, and we get deep into how to actually measure it

- What Board Decks and Meetings should look like for pre-seed and seed stage companies

- What selling to banks (and other companies) with long sales cycles means for raising money from VCs

- Why serial entrepreneurs are usually the ones that chase capital-intensive new businesses (like SpaceX)

- How to optimize pricing and contract term length at the earliest stages of a startups life

- How AI is changing sales

- Whether market timing actually matters

- What, other than scaling too early or too late, can kill a startup

If you are building an early stage startup I really encourage you to listen to the whole thing.

Chapter list:

00:00 Introduction to Scaling and Revenue Generation

02:33 Early Stage Board Meetings

08:40 Leading Indicators of Retention with Long Bank Sales Cycles

17:28 What Bank Sales Cycles Mean for Raising VC Money

21:47 VC Discipline and Investment Strategies During Bubbles

26:49 How to Optimize Pricing and Term Length at the Early Stages

31:41 Does Timing Matter for Startups?

36:24 The Other Sciences of Scaling

37:35 The Impact of AI on Scaling Revenue

48:49 Societal Impacts of AI

Peter has a fascinating story, having grown up in Australia and teaching himself to code as part of his “gap year” job working for the government, before traveling to Silicon Valley and landing a job building a core banking system. Many tech jobs later, including stints at Google and Uber, he is now building Synctera, which could in many ways could also be described as a core banking system. 

One of the themes of our conversation were the lessons that we can teach our children, and we covered:

- How an interaction with the conductor of the Sydney Symphony Orchestra when he was 14 years old gave Peter a life philosophy that has stuck with him since- How being lazy can unlock near-endless opportunities- Peter’s core belief that if you build something, you have a responsibility to make sure that, as far as possible, people can’t do bad stuff with it- How the secret to making B2B businesses successful is the relationships built over many years- Lessons on managing teams learnt from Google- The similarities of the dot come bubble and today’s AI hype cycle- How startup life influences parenting styles

Listen along to hear more from Peter, and for a chance to reflect on your own early life lessons. I hope you enjoy the conversation! 

00:00 Introduction and Acquisition Announcement

00:31 Peter's Childhood and the Influence of Music on his Life

11:30 First Job and Teaching Himself to Code

18:06 Moving to the US and Jumping on the Startup Train

21:29 How Startup Life Influences Parenting

24:43 Leadership Lessons from Google

26:33 The Through-line of Payments, the Origins of Synctera and the Importance of Building Relationships

38:10 Acquiring Cable

How does Starbucks offer it's reward card? How does Amazon provide a credit card? All these "embedded finance" programs have banks behind them who help the brands onboard customers, provide oversight, and act as the buffer between the brands and the regulators. 

I went into this conversation thinking that standing up an embedded finance program was mostly about choosing 1 great partner and making sensible decisions around compliance. Now I know how wrong I was! 

A bank getting into BaaS is a bit like a contractor building a house. They may do everything - the plumbing, the electrics, the painting - or they may outsource all those things to others. Deciding what skills you have as a bank, and therefore what you can offer, what you can build internally, and what you need to contract, is step 1. 

We got into detail about the pros and cons of For the Benefit Of (FBO) v Ultimate Beneficial Owner (UBO) account types. An FBO account is a single pooled account at the bank on behalf of a brand or a fintech, whilst a UBO structure means every end consumer (or business) is an actual customer of the bank. There are distinct pros and cons to both set ups, and again, the bank should work out where its skills lie to decide which route to take. 

Making money is harder than it seems! You might make revenue from interchange, interest and/or program management fees, but the size of those buckets varies hugely depending on the type of brand or fintech you work with. Diversification is the key, and scale is needed to make any meaningful revenue. This isn’t an area you can “try out”. You either go hard, or go home. 

For so many more great insights, listen in here. 

In this episode, I talked to Peter Piatetsky, former US Army intelligence analyst, former Treasury Department official, and now CEO of Castellum AI, about the history of sanctions, how they've evolved from a careful diplomatic tool into something governments reach for freely, and what that means for banks. 

We covered the Turkish pastor case that changed how policymakers think about sanctions, how Peter personally figured out how to sanction aircraft at the Treasury, the existence of the UN Credit Union (one of the highest-risk financial institutions in the world), how people actually evade sanctions, and why the explosion of fintechs may be creating more sanctions risk than the sanctions themselves.

If you work in finance, you can't afford to miss this one. 

The data your bank gets when you swipe your card is shockingly bad - a jumbled descriptor of ~50 characters, a merchant category code that might be wrong, and a "city" field that's sometimes just a phone number. 

In this episode I learn about why payments data hasn't meaningfully changed in 30 years, how Spade built a body of merchant data covering 99.9% of payment-accepting businesses in the US and Canada, and what banks can actually do once their merchant data is good. 

We also discuss Spade's freshly announced $40M Series B led by Oak HC/FT with participation from Andreessen Horowitz, what nearly 500% YoY growth breaks inside a company, and why Oban is saying no to obvious opportunities to stay focused.

But maybe not for the same reasons as you. 

I am obsessed with how quickly they have grown, how they seem to be on track to disrupt the gambling industry entirely in no short order, and how they seem to have evaded appropriate regulatory oversight.

An alarming stat: we know that when a state legalizes online sports betting, bankruptcy rates increase by 25-30% over the next 3 to 4 years, and so to me, the fact we’ve found a way to avoid state gambling regulation is… worrying to say the least.

Are we creating a whole generation of gamblers? Have we found a way to avoid gambling regulation? Is it simply another tool through which the rich get richer and the poor get poorer?

To understand more about prediction markets I begged Alex Johnson, founder of Fintech Takes, to chat to me. He’s the fountain of much knowledge, and like me, is pretty obsessed with what’s happening here. This episode is a cracker, and we covered so much, including:

→ What prediction markets are and how they work

→ The regulatory landscape they exist within, and that which they’ve managed to avoid

→ Where their volumes come from - what kind of predictions are being made?

→ Some pretty suspect behaviours linked to politics and predictions on these markets

→ How Robinhood and others are starting to present prediction markets as an investment opportunity

Well done if you knew that he invented the credit card!

On this week’s episode of In Control, I was lucky enough to speak to Susan Ehrlich, and to learn all about credit cards. 

Susan ran the credit card divisions at Citibank, Washington Mutual, Sears, and Amazon, including building the Amazon Prime 5% cashback card. Now she's a partner at Core Innovation Capital. In other words: she knows how this industry actually works! 

I absolutely LOVED this conversation because Susan was able to go so deep. She taught me about the history of the industry, how banks and merchants make money from credit cards, and completely demystified the proposed 10% cap on interest rates. 

You do not want to miss this episode! 

We covered:

- The three revenue streams: interchange fees, interest income, and late fees- Why credit cards are the most profitable product banks have- How Delta makes $7 billion/year from their loyalty program- The origins of the first credit card - The Diners Club - in 1950, started by someone who forgot his wallet at lunch- What happens to access and rewards if the rate cap goes through

Or, how student-athletes are paid to play?

On the latest episode of In Control, Richard Scioli of Analog taught me how NIL works, including how creative the compensation can become. 

Unlimited BBQ for offensive linesmen? Done. 

Decoldest Crawford as the face of… you got it… an air conditioning company? Done. 

Richard got into it all to break down the business of college sports. We covered:

- The three buckets of NIL (Name, Image, Likeness) and how they work- Why college athletes setting up LLCs is now standard practice- How 10 people regulate 363 Division 1 schools and 175,000 athletes- The private equity deals reshaping athletic departments

They always look baffled, but she might actually be onto something! In-person fraud rates in the US are much higher than in Europe.

Why is card fraud so prevalent?
We share our 16-digit card numbers everywhere - is that safe?
How do merchants actually protect this data?

To dig into all of this, I spoke to Colin Luce, CEO at Basis Theory, and it turns out there's a quiet power struggle happening.

Visa and MasterCard want merchants to rely on their tokens and delete the original card data.

Merchants don't trust what comes next.

Once you give up that data, you can't switch processors, you can't negotiate, you take whatever pricing the networks decide.

We also discussed in the podcast:

- Why agentic commerce isn't really a payments revolution
- Why MasterCard are getting rid of the PAN
- Whether consumers care about card fraud
- How your Stripe token is useless with Adyen

Props to you if you knew it was escheatment. 

This is the craziest area of financial compliance I’ve learnt about in a long time, and my head is still reeling from my chat with Allen Osgood, CEO of Eisen.

What started out as me wondering what would happen to the Bitcoin that I can’t access (moved country, changed phone number…) turned into a mind bending story of a man who lost all of his Amazon stock (bye bye nice retirement), how claiming your own money back from states has become rife with fraud, and how there are $70bn of funds being held by US states that they just make money off and use to fill budget. 

We also discussed:- Why states are incentivised to NOT return your money- The story of a guy who lost hundreds of thousands in Amazon stock because he didn’t log into his account- How 1 in 7 Americans have money sitting unclaimed with the government- The contingency fee auditors who make 10-12% of everything they can claim

Back when I was Head of Financial Crime at Monzo, I watched fraudsters pump tens of thousands of pounds of petrol using cards with just £100 on them. We had their names, addresses, photos - everything! But the police didn't know what to do with it.

And that was before AI changed everything.

Now Yuliya Kazakevich, who's led fraud teams at Charles Schwab, Apple, Adyen, Cash App, and Lithic, is watching fraud evolve in ways that genuinely concern her.And if someone with her experience is worried, we should all be paying attention!

It was great to welcome Yuliya on the pod to discuss all of this. Here’s what we covered:

- Whether AI companies should be liable for enabling fraudsters- Why JP Morgan is opening more branches- How AI is scaling fraud to terrifying new levels- The shift from unauthorised to authorised fraud- How law enforcement is overwhelmed and under-resourced to tackle fraud

Fraud is evolving faster than we can keep up - and we need to start paying attention.

I've been talking about bank M&A a lot lately because it affects everyone, not just bankers. We all need a bank to function in the world - to get paid, rent an apartment, receive welfare etc. So what happens when banks start disappearing?

Joe and I got into ALL of it on this episode:

- Why $10.1 billion is the worst size for a bank to be
- How Needham Bank integrated BankProv over a single weekend
- The embedded finance future and who's going to win
- Whether branches will exist in 15 years
- How banks might use your data to offer you loans before you ask
- Why the talent crisis is accelerating everything

If you want to learn more about the future of banking, check out this episode.

- Why businesses still mail checks like it's 1987
- How Venmo actually makes money (it's not from moving money)
- Why banks charge $20 for a wire transfer
- What stablecoins will actually be used for.

One thing that blew my mind: Delta makes $2 billion a quarter from payments alone - they're basically a payments company that happens to fly planes.

So if you’re as baffled as I was by how banking works in the US, this one’s for you.