Mon. Oct 19th, 2020
AI-and-fintech

AI and fintech- Announcements like Selina Finance’s $53 million raise and another $64.7 million raise the next day for a different banking startup spark enterprise artificial intelligence and fintech evangelists to rejoin the debate over how banks are stupid and need help or competition.

The complaint is banks are seemingly too slow to adopt fintech’s bright ideas. They don’t seem to grasp where the industry is headed. Some technologists, tired of marketing their wares to banks, have instead decided to go ahead and launch their own challenger banks.

But old-school financiers aren’t dumb. Most know the “buy versus build” choice in fintech is a false choice. The right question is almost never whether to buy software or build it internally. Instead, banks have often worked to walk the difficult but smarter path right down the middle — and that’s accelerating.

Two reasons why banks are smarter

That’s not to say banks haven’t made horrendous mistakes. Critics complain about banks spending billions trying to be software companies, creating huge IT businesses with huge redundancies in cost and longevity challenges, and investing into ineffectual innovation and “intrapreneurial” endeavors. But overall, banks know their business way better than the entrepreneurial markets that seek to influence them.

First, banks have something most technologists don’t have enough of: Banks have domain expertise. Technologists tend to discount the exchange value of domain knowledge. And that’s a mistake. So much abstract technology, without critical discussion, deep product management alignment and crisp, clear and business-usefulness, makes too much technology abstract from the material value it seeks to create.

Second, banks are not reluctant to buy because they don’t value enterprise artificial intelligence and other fintech. They’re reluctant because they value it too much. They know enterprise AI gives a competitive edge, so why should they get it from the same platform everyone else is attached to, drawing from the same data lake?

Competitiveness, differentiation, alpha, risk transparency and operational productivity will be defined by how highly productive, high-performance cognitive tools are deployed at scale in the incredibly near future. The combination of NLP, ML, AI and cloud will accelerate competitive ideation in order of magnitude. The question is, how do you own the key elements of competitiveness? It’s a tough question for many enterprises to answer.

If they get it right, banks can obtain the true value of their domain expertise and develop a differentiated edge where they don’t just float along with every other bank on someone’s platform. They can define the future of their industry and keep the value. AI is a force multiplier for business knowledge and creativity. If you don’t know your business well, you’re wasting your money. Same goes for the entrepreneur. If you can’t make your portfolio absolutely business relevant, you end up being a consulting business pretending to be a product innovator.

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Article Credit: TC

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