Techno-optimist [tek-noh-op-tuh-mist]
Someone who believes the advancement of technology is paramount to bettering the human condition; the belief that humanity will improve as technology improves.
Technology improves over time. New advents help us build new products that create new businesses that solve new problems. As long as technology continues improving, the products and services we build should improve as well.
Since the creation of the internet in the late 19th century, technological advancements have enabled new businesses to be created. This is true for the internet in general and for financial technology companies more specifically. In fintech however, the nature of the new opportunities that arise are somewhat different.
The earlier internet companies simply took offline experiences and made them digital. Things like information and basic multimedia were now available online. After that, the iPhone allowed these services to be delivered to users on the go. Then cloud took over, allowing more advanced services to be delivered over the internet without companies maintain their own server farms.
Each of these technological progressions paved the way for new businesses to follow. In the case of the early internet, it was companies like Yahoo, Google and AOL. For mobile it was the likes of Uber, Instagram and Snapchat. And cloud created Slack, Figma and Zoom. As technology advances, the set of problems we can use technology to solve expands — and that’s where new companies are born from. Either solving previously unsolvable problems or solving problems significantly better than we could have previously given the technology available at that time.
The same is true for fintech. As technology improves, the set of financial problems we can solve using technology expands. But in fintech, it’s better to think about it as transaction complexity as opposed to problem complexity.
Across the spectrum of financial services there are simpler and more complex transactions. As technology improves, we should use it to handle increasingly complex financial transactions.
We see the same examples of companies in fintech as in the broader internet. Paypal was one of the first fintech companies. Paypal handled the simplest financial transactions — passing money between two individuals. Peer to peer payments over the internet was enabled by the early consumer internet — the dot com era.
The next wave of fintech products were enabled by the proliferation and affordability of cloud and the success of mobile phones and their app markets. These new technologies allowed companies like SoFi, Plaid, Robinhood and Stripe to build more complex banking, payments and lending products (or enable them). These are significantly more complex financial transactions than peer to peer payments — they involve underwriting, decisioning, querying large data sets and creating beautiful, trustworthy digital experiences. This was only possible thanks to the success of new technologies like cloud and mobile.
A way this has been previously framed is that all innovations hinge on some macro trend that enables that innovation to take place. There are macro trends that aren’t technological too. Open banking legislation and the Durbin Amendment to the Dodd-Frank Act in 2010 also played major roles in the second wave of fintech. But as important as the new legislation was the new technology. When building a new product, there is usually some macro change that makes that product viable today when it wasn’t yesterday — in most cases that macro change is technological.
The most recent macro change — technological in nature — is Generative AI. While a powerful new tool, Gen AI presents a particular challenge for fintech companies. These new models are notorious for hallucinating, or making things up. This may be an acceptable cost of progress in some cases, but when making underwriting decisions or providing users with financial advice or information, the costs of a hallucination is entirely unacceptable. Fintech products cannot risk delivering wrong information to users because a model decided to make it up.
There are plenty of solutions to this problem, the most popular of which among fintechs is the human-in-loop commitment. We will use Gen AI to create outputs, but they will never be allowed to make decisions or deliver something to a customer without a human reviewing the output’s accuracy. There are other solutions too and only time will tell which allows for the best customer experience while also ensuring accuracy.
Those details need to be worked out but the certain thing is that given this new technology, the financial transactions new fintechs focus on should be a level of complexity more advanced than their predecessors’. There are whole swaths of financial transactions that are still being handled manually. The underwriting is too complex, the customer insists on speaking to a person, a decision is subjective to a number of factors that can’t be easily quantified. Gen AI certainly won’t be the end-all for all financial transactions, but if it’s as impactful as we’re expecting, we should start seeing startups tackling significantly more complex financial transactions than ever before.
If you’re excited about using new technologies to solve the most complex financial transactions, reach out. We’re always hiring — max at by novella dot com.
