Fintech
AI is a huge mistake (if you don’t understand what it’s for)
It amazes me how many people in banks and tech companies talk about cloud, big data, AI, fintech, blockchain, apps, 5G, analytics, APIs and more as if they are all dry. They are containers of technology, but in each container there is a use case, and in many, hundreds or even thousands of use cases. In other words, none of these technological developments are one thing – one thing – instead they are developments that have encouraged many things.
Let’s take Fintech for example. We know that most Fintech startups initially focused on payments and lending, but again these are smaller segments as there are many variations of payments and lending innovations, from peer-to-peer to buy-now-pay-later to from merchant checkout to tokenization and digital wallets. None of these areas represents a homogeneous set of technology. It concerns the granularity and detail of the individual use cases that compose them.
The same goes for artificial intelligence.
Source: Imtiaz Adam
And then you have the map of the AI market in Fintech.
Source: CB Insights
That’s why I find it funny to see fellow fintechs discussing this anomaly. The anomaly is that CxO leaders at banks think AI is a thing and tell their employees they need to be at the forefront of this thing. The fact is, it’s not a thing. It’s a lot of things.
For example, Ron Shevlin, Chief Research Officer at Cornerstone Advisors, note that “AI refers to different types of technologies. Bringing everything together under one label is a huge mistake.”
Likewise, I find that many financial executives are excited about all these technologies but have little understanding of what they actually mean. If I walk into a meeting room and they mention AI, I will ask what LLM means; or if they mention cryptocurrency or blockchain, I will ask them what DLT means.
Now, I hate TLAs (three-letter acronyms) – as regularly stated – but if a company can’t understand the emerging technology landscape, they should make sure they hire someone who can… and I don’t mean a consultant. In fact, consultancies are very good at crafting TLAs to ensure that people are confused and bewildered, but eager to keep up.
The main way to stay ahead is to understand that technology and its many advances, from artificial intelligence to the cloud, are just like banking and its many advances, from investing to lending.
In fact, technology and finance have a lot in common. At the granular level of the banking sector there are also many TLAs, from your BMACH to your IMOs.
So if you’re a CxO at a finance organization and you hear techies talking about AI and cloud, remember that buzzwords are irrelevant – what matters is what you can do with them.
In this regard, there is an excellent article by Igor Tomych, CEO of DashDevs, who explains seven key use cases of AI in banking that are worth a read if you have ten minutes.