Snippings

Joseph Stiglitz is an American economist best known for explaining why markets don’t always work as neatly as textbook models suggest. He’s a Columbia University professor, a former World Bank chief economist, and a former chair of the U.S. president’s Council of Economic Advisers.

He shared the 2001 Nobel Memorial Prize in Economics for work on asymmetric information: situations where one party knows more than another. Think of a lender who can’t fully assess a borrower’s risk, or an insurance customer who knows more about their health than the insurer does. His work helped show how these information gaps can cause markets to produce inefficient outcomes.

Why take him seriously?
His research changed economics. It supplied rigorous reasons why competition alone doesn’t always deliver the best result.
He has substantial policy experience. He’s worked inside institutions he later criticized, especially on globalization and economic development.
He’s particularly worth reading on inequality, financial markets, and the role of government. He connects technical economics to questions about who benefits from economic policy.

xxx

Textbook economics teaches us that ever-present competition drives profits down to zero, and that it is through these lower competitive prices that society benefits from innovation. The reality is often otherwise. Google and Facebook have had sustained profits for years. Economists have explained why, without effective antitrust enforcement, that is no surprise. .

From: Joseph Stiglitz’s ‘progressive AI agenda’ for the economy.

xxx

xxx

In their fascinating paper on “The Data Economy: Market Size and Global Trade” for the Economic Statistics Centre of Excellence (part of the UK’s National Institute of Economic and Social Research), Diane Coyle and Wendy Li talk about the growing “data gap” between global Big Tech and potential competitors, disruptors and innovators. They argue (convincingly) that this data gap is a a barrier to entry that affects not only businesses but also aggregate innovation, investment and trade:

PROMOTED

Large data holdings, rich in volume and variety, thus give large online platforms a significant competitive advantage, powered by network effects and the virtuous cycle between data and the AI algorithms improving the services and increasing revenues.

This advantage means that the platforms obtain insights about adjacent sectors and can then enter them more easily.

From: Scrooge McData.

xxx

xxx

Data is the new gold and these companies have more data than anyone else, which gives them a competitive advantage. They have also figured out how to leverage this natural competitive advantage by engaging in sometimes hard-to-detect anti-competitive practices, even if doing so violates people’s privacy.

From: Joseph Stiglitz’s ‘progressive AI agenda’ for the economy.

xxx

xxx

AI-led growth, however, creates a tension with Europe’s bid for sovereignty, because Europe controls little of the AI value chain. The technology is set to become completely pervasive: in the economy, in health systems, in education, in energy, in defence, to name just a few areas. This is no ordinary dependency. Being cut off from AI, once the economy runs on it, would be more like being cut off from the US financial system. The effects would be catastrophic.

From: Europe’s difficult choices on AI.

xxx

xxx

We must slow the pace at which we improve the capabilities of AI models.

From: Dario Amodei — We Must Pace the Frontier.

xxx

You have undoubtedly read the story about Revolut. The fintech has confirmed that it disclosed sensitive customer information to an “unauthorized third party” after receiving fraudulent requests sent from a legitimate government agency email domain. The exposed data included customers’ personally identifiable information (PII) including contact details, birth date, email, address and phone numbers. Worse, it also included copies of their identity documents including passports and driver’s licenses. The data “may” have also included verification selfies, account statements and transaction histories!

I had a vague memory of something similar having happened before, and a quick trip to LLM land confirmed by suspicions. A few years ago, hackers tricked tech companies, ranging from Apple and Meta to Discord, into turning given out sensitive personal data by complying with fake emergency data requests (EDRs) seeming to come from official sources. Hackers soon discovered they could obtain access to real law-enforcement email accounts via the usual means (eg, phishing) and then submit EDRs concerning bogus emergencies. Since the requests came from authentic government accounts the companies complied and the compromised data was used to enable significant crimes, including SIM-swapping attacks against cryptocurrency holders, which is I am sure the sort of thing that the Revolut data will be used for.

While I was thinking about this, I got a text from Amazon to say that there was a message waiting for me. So I went to Amazon and logged in to read the message waiting for me. Surely the FBI or the police or whoever could come up with some similar system? In fact, surely someone already has? In fact, while I am not an expert on law enforcement systems, but it took about two seconds’ googling to discover that they already have.

(In fact it turns out that there are several! Kodex Global, Casepoint, Cytrio and Virtu, amongst others).

The platforms (eg, Meta, Google and Apple) tend to run their own in-house Law Enforcement Response System (LERS) portals rather than outsourcing verification to a third party, requiring police to register an account tied to a real agency before any request is processed, which seems sensible. I wonder if they might also demand 2FA for any account that presents a request.

You do have to wonder why, of course, Revolut are storing all of this toxic waste in the first place. I can see why Revolut might need to store 

I remember talking about this with Rowan Akin-Smith at EBA Day earlier this year. Rowan is with Vyntra, one of. my advisory clients, and he’s written a good piece about this in the context of Canada’s immininet instant payments launch. Noting that overly cautious controls can introduce friction that erodes customer confidence almost as effectively as a fraud does, he goes on to say that the banks managing this well will be be the ones “making better decisions earlier, so legitimate payments keep moving while genuine risk gets caught”. Indeed.

So what is needed to make better decisions? We all know the answer to this is: it’s data, shared data.

xxx

Quick Read

Revolut’s compliance team released customer files to an attacker using a spoofed government email domain, exposing IDs, KYC selfies, and Bitcoin histories.

No funds were stolen and no systems were breached, but the stolen files enable highly personalized phishing attacks against identified customers.

The limited, targeted data set suggests attackers deliberately chose high-net-worth accounts; Revolut is notifying affected customers individually rather than issuing a broad disclosure.

From: Revolut Handed Customers’ Passports and Bitcoin Records to a Fake Government Request. Are You Affected?.

xxx

A recent Mastercard survey of 13,000 parent-and-teen pairs across 13 European markets together with Israel and the UK found that a third of all teenagers already use AI on a weekly basis to find and compare products and services, compared to a fifth of their parents. What’s more, more than a third say that they would happily hand over to a fully AI-run shopping assistant that chooses (and, crucially, pays for) products and services.

Well, yeah, whatever, I can hear you thinking, of coruse they do. But based on some workshops I’ve been in recently, I’m not sure if the implications of this transition are really being taken on board by strategists across commerce and finance. Hence I was very interested to read 

xxx

For businesses, this isn’t an abstract infrastructure issue. Payroll, supplier payments, liquidity management, and customer refunds all increasingly depend on an institution’s ability to prevent, detect and recover from disruption in real time. Treasurers are scrutinizing how banks communicate during incidents, how quickly they recover, and how transparent they are about what went wrong. Increasingly, reliability will be measured by a less quantifiable standard: confidence.

From: The Real-Time Rail Paradox: Instant Payments, Real Risk.

xxx

There’s a good paper in the latest issue of the Journal of Payments Strategy & Systems 20(2), pp. 179-193 (Summer 2026). It’s called “The stablecoin era: The history and future of stablecoins” and it’s written by me and noted fintech commentator Simon Taylor. A “preview” presentation of the paper went down so well at Money 20/20 in Amsterdam earlier this year that I decided to head out to Simon’s upcoming Fintech Nerdcon in San Diego on November

When Tim Berners-Lee and his team were designing the World Wide Web, they included error codes such as “500: internal server error”, or “404: page not found”. One such code is “402: payment required”. The original intention was that this code would be used to transact using digital cash or micropayments. It was never implemented and the Collisons argue this is the reason tech went from an equal access opportunity to an oligopoly controlled by five companies now worth more than $3 trillion.