Who disrupts the fintech disruptors? 🤔

It’s game on for fintechs aiming to stay relevant in the long run.

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Greetings all ye fintech junkies!

Fintech disruptors are starting to experience disruptions of their own, with bigger competition threats from incumbents, and more scrutiny from regulators and investors.

In other words, no more ‘microwave’ solutions and ‘oven-ready’ products: stakeholders want to know what’s really cooking.

What you need to know right now:

Block becomes the latest fintech to lay off workers (TechCrunch)

Another wave of massive layoffs has hit the fintech industry, most recently – Block, which had to lay off…wait for it…1,000 workers—AKA 10% of its workforce.

“We decided it would be better to do it at once rather than arbitrarily space them out, which didn’t seem fair to the individuals or to the company. When we know we need to take an action, we want to take it immediately, rather than let things linger on forever.” Jack Dorsey, CEO of Block.

Some more takeaways from the story:

  • Dorsey announced the layoffs in an internal memo, stating that Block’s headcount growth had outpaced its business and revenue growth.
  • Block had previously mentioned in an earnings call that it would reduce its headcount from 13,000 to 12,000 by the end of the year.
  • Block has faced challenges in its business, with declining revenues from Cash App, losses from Afterpay, and falling Bitcoin revenue.
  • Block’s investors have been displeased, with the company’s stock declining by about 30% from January 2023 to October 2023—just around the time Jack Dorsey took over as CEO.
  • The fintech and broader tech sector has seen a wave of layoffs recently, with PayPal laying off 2,500 employees, and Brex laying off 20% of its staff.

Why does this matter?

We all remember those red-carpet fintech days, where all you had to do was say the words ‘financial technology’, and voila! Investor intrigue was at your fingertips.

Alas, those days have come to an end – as these massive layoffs demonstrate.

Investors are losing patience with glitzy gimmicks and procrastinated promises. They want outcomes, and they’re not willing to wait anymore.

What else to read:

UK neobanks need to show sterling qualities, not just fintech growth (FT)

  • UK neobanks, including Revolut, Monzo, Starling, OakNorth, and Wise, have been performing well, with healthy revenue growth and profitability.
  • The challenge for these neobanks is how to exit successfully, with IPOs and M&As as potential options.
  • These digital banks aim to benchmark themselves against tech growth stocks, but their revenue models are more similar to those of traditional banks.
  • Neobanks are growing their customer base but may face challenges as they expand to new countries.
  • UK neobanks are not typically the main bank accounts for their customers, but their revenue growth has been driven by the rise in interest rates.
  • Public market investors will scrutinize the earnings quality of UK neobanks as they consider going public.

Why Did Fintech Stumble? (The Financial Brand)

  • In this op-ed, fintech veteran and commentator James Ledbetter discusses why fintechs have fallen from grace in recent years.
  • According to Ledbetter, the early 2020s saw extreme fintech spectacles, including the meme stock explosion in January 2021.
  • But the meme stock phenomenon and Robinhood’s near collapse exposed some of the major flaws in the fintech ecosystem.
  • Tech failures, regulatory changes, weak internal controls, shrinking capital, and shaky business models were the five biggest flaws that were exposed.
  • The game’s not over yet, though. The fundamentals driving fintech, such as the demand for faster, easier, and cheaper financial transactions, remain intact.

Mastercard jumps into generative AI race with model it says can boost fraud detection by up to 300% (CNBC)

  • Mastercard is launching a generative artificial intelligence model called Decision Intelligence Pro to help banks detect and prevent fraudulent transactions.
  • The model is powered by a proprietary recurrent neural network developed in-house by Mastercard.
  • Mastercard claims that this AI technology can improve fraud detection rates for financial institutions by as much as 300% in some cases.
  • The algorithm is trained on data from approximately 125 billion transactions processed by Mastercard annually.
  • Instead of relying on textual inputs, the algorithm uses a cardholder’s merchant visit history as a prompt to assess transaction legitimacy.
  • The algorithm generates pathways through Mastercard’s network to determine a score, with higher scores indicating typical cardholder behavior and lower scores indicating deviations.
  • This entire process occurs in just 50 milliseconds.
  • Mastercard has invested over $7 billion in cybersecurity and AI technologies over the last five years.

That’s all for this week’s issue – see you next time!