2023 fintech predictions
‘Tis the season to guess what’s coming next, so we’re ringing in the New Year with fintech predictions. We can all agree it was quite a year, what with crypto tanking, BNPL taking a beating, and record inflation, so there’s lots to work with when it comes to predicting the future.
Andrew Haines, our Global Head of Fintech, has lots of thoughts on what’s in store in 2023. For the past year, he’s been at the heart of Vention's fintech practice, which offers our clients deep expertise into everything from fintech consulting to blockchain (including guidance on what to think about before you start building with blockchain) and as well as best practices for hiring fintech engineers and developing fintech apps.
Read on for Andrew’s assessment of what’s in store for non-banking finance and for crypto’s winners and losers, plus a few additional projections from the fintech trenches.
Prediction #1: 2023 will be marked by dramatic expansion of embedded finance and banking functions in non-banking applications.
Despite an uptick in BNPL use this holiday season, overall, BNPL firms like Klarna are experiencing a lot of challenges currently: Interest rate increases and under-calculated customer default rates have led the stock market to be negative on the entire BNPL trend, so companies will change their offerings.
BNPLs are still here to stay (as they really are just a more evolved version of layaway purchases), particularly given the success of WeChat’s BNPL platform, which launched in April 2020, right when the pandemic hit. WeChat is now the largest embedded finance player in the Far East and has successfully expanded into Europe. Meanwhile, AliPay, which offers BNPL, has almost 1.2 billion active users and 80 million merchants globally.
Prediction #2: Non-bank lending will gather steam.
Call them what you will — peer-to-peer loans, local loans, microloans, crowdfunding — but all sorts of non-bank lending will become more prevalent. Not only that, but they’re going to serve not just visions, as in the kickstarter model of “I have an idea and I need money to make it happen” but also loans for things that have already been done. For example, imagine a business that has a purchase order that it needs to fulfill. In order to get access to finance for that order, it would be willing to share its financial information, and then investors will be willing to take interest on a loan to that business. That way, everything’s secured the way a bank would, but it’s not the bank that’s providing capital.
The non-bank lending model can help lessen the wealth divide by supporting loans to minorities, but it can also make businesses more profitable, including those that have government-backed contracts, by reducing interest. Imagine that you have a company that builds roads. You need to pave the road before you can get paid by the government — but you will still have costs you need to cover in the meantime. A non-banking lender can step in and give you the capital because the lender knows you will get paid — and they’ll charge you 8 percent interest rather than the 15 percent a bank would charge.
Prediction 3: Ten percent of crypto companies will survive and thrive.
It feels like 1999 all over again, when everyone needed a dot.com in their name. Ninety percent of the dot-coms failed, but the 10 percent that survived wound up thriving: Amazon, Ebay, Shutterfly, Priceline. Maybe we don’t know the names of all of the successful ones anymore, because they got bought and were absorbed by another larger company, like Drugstore.com was by Walgreens, but they were still incredibly successful.
It’s going to be the same thing with crypto. We’ll barely remember most of the failures. Who remembers or talks about Webvan and Pets.com and Boo.com. Or Kozmo.com? FTX, BlockFi, Voyager Digital, Three Arrows Capital, Celsius network — those are going to be the Pets.com of the crypto bubble.
FTX might be the culmination (or poster child) of the fast and volatile crypto failures, but at some point, surviving firms will have real and enduring value.
Prediction 4: Regular banks will acquire neo banks at an even faster clip.
Think how pharmaceuticals work: Medical and research universities create the drug, the biotechs prove it, and then the biotech sells it to a massive producer like Pfizer. It’s going to be like that with neobanks: a small new bank will show up with something like AI-powered credit card lending that doesn’t give a credit limit but rather has a limit that goes up and down based on paychecks and various other data points. That product turns out to be profitable, with little risk. A mid-sized, super regional, or budding national bank like PNC or Capital One will buy it and then fold the product into its offerings. Examples include Goldman Sachs’ acquisition of BNPL platform Greensky for $2.2B in March 2022 and Capital One’s many fintech acquisitions, including of travel tech startup Lola in 2021.
It’s just another variation on big companies buying smaller ones to obtain technology (in this case a product) and expertise (if it buys not just the product but the people who created the product).
Prediction 5: AI will make credit analytics even more powerful and credit scores will become more fair.
Credit scoring has gotten much better in the past 10 years, and with the explosion of AI applications we’re seeing, it’s going to be much easier to predict a person’s behavior and credit patterns. Unconscious or inherent bias has been built into credit analysis for as long as credit analysis has existed, and while there are still lots of things that need to be sorted out with respect to bias in credit scoring, even with AI, it’s going to get better and better because ultimately data is data: It tells the facts. More consumers will have access to credit, which is good for the economy, and the models will become much better at assessing who is actually at risk of getting in over their heads with debt — and that means better allocation of capital in the economy.
Prediction 6: AI-based consumer purchasing will merge with embedded finance and affect supply chains and payment rails.
AI will tell you it’s Burberry and where it’s available, including on consignment sites like TheRealReal. If it’s not available anywhere, AI will feed you something similar.
It’s all going to rely on embedded finance and AI: One-stop shop on your phone. You snap a pic of an item and within seconds you can locate it, pay for it with a touchless payment, and have it shipped to you, all from one app. More and more, apps will be integrated with things like QR codes or NFC for automated payments. Already, massive networks like New York’s MTA and London’s Underground are using touchless embedded finance.
Prediction 7: AI will streamline financial contracts
This is going to happen really fast: AI will scan contracts like ISDAs (International Swaps and Derivatives Agreements) and flag unusual clauses for lawyers to review, rather than paying a lawyer to go through all 20 pages of the contract. There will likely always be random things that can be changed in contracts that only a lawyer or law clerk will be able to detect (and having humans still involved to a certain extent will always be a good thing), but AI, natural language processing (NLP), and optical character recognition (OCR) will make legal documentation far less cumbersome.
If something is unusual, a machine learning algorithm will flag it, and presto, far less money will be spent on lawyers. Tools like Claira (“document intelligence for ready-to-go analysis of complex documents”) will make strategic investing, negotiation, risk, projections far more streamlined and efficient. This goes beyond what we currently think of as smart contracts, which are rooted in blockchain. It’s really document intelligence fintech, which will affect everything in a company’s operations, even globally, not to mention making it far easier for contracts to follow and incorporate regulatory changes.