A touch of AI in your financial business won’t have much ROI
We all agree that AI-powered Businesses will Rule the Future. [1]
Finance is no exception and several Fintechs and Techfins see themselves and operate as AI businesses. Square, now Block, is the Fintech that pops up in my mind when I think of a Fintech that is at its core and from the start an AI business.
Any successful data business is essentially an AI open factory business because only with that mindset can the business efficiently manage its operations and grow its ecosystem profitably.
An AI-powered Fintech example
Just this month, Square announced new AI-powered features within its Square Messaging platform. Merchant communications with prospective buyers are improved by AI. Square continues to deploy AI to facilitate mobile and conversational commerce which is on the rise.
Square has been powering its operations internally with AI (specifically, heavy use of Machine learning) and when designing and launching new products (MVPs).
In 2017, they managed to reduce their internal manual work around risk management and fraud detection by 40%, by deploying machine learning.
They continue to deploy and improve AI for fraud detection on their Cash App.
They have been using Machine learning on their merchants` data of payments, inventory movements, and hiring practices, to evaluate the creditworthiness and repayment ability of their small business clients quickly and easily. Square`s Capital lending is part of its Industrial Bank licensed business and last year they bragged that they lent to 58% of their loans went to women-owned businesses (way above the average for traditional loans which is 17%- Source)
As the Square ecosystem has grown and is more complex, they use machine learning to select and suggest to merchants ways to improve their businesses. Square becomes an advisor to its sellers via AI, which is capable of fast personalization. This takes a data science team and machine learning to Predict the best product fit from the Square ecosystem for each sellers’ needs.
AI-powered use cases in financial services, here and there
While Square is an AI-powered business, we should not consider any financial services businesses that deploys AI in one area or another, as an AI-powered business.
For example, just because a bank uses Conversational chatbots for customer service and onboarding, doesn’t make its consumer banking business an AI-powered business. Even if they add AI-enabled notifications to their mobile banking app about budgeting, that doesn’t make them an AI-powered business either.
A banking or non-banking provider that uses AI to originate loans to new customers doesn’t necessarily qualify as an AI-powered lending business. Lending is not only about origination, but also about credit-risk monitoring and delinquency risk after origination. Only when AI is the way the entire operation and life-cycle is managed, the business is an AI-powered lending business.
A robo-advisor or any WealthTech provider that uses AI for risk profiling customers is not necessary an AI-powered investment business. First, all `robos` leave the decision of how much to invest to the customer / investor (no data, no AI, no advice, no change) and then profile them to access their risk tolerance. An AI-powered investment business should start with assisting the consumer with the `how much to invest` decision. This should be AI-monitored over time because it can and should change. Then the decision of where to allocate the investments, should be AI-powered (the 60/40 portfolio can’t be part of an AI-powered investing business anymore).
AI-powered businesses in financial services are not here yet, despite the increased deployment of AI in several aspects of financial services. The deployment is spotty and limited.
AI deployment in financial services falls short of an AI-factory with data scientists and businesspeople collaborating to serve the financial needs of businesses and individuals — the economy.
AI-powered financial services does not mean everything is operated by algorithms. It means AI-powered operational excellence and an intelligent network (partners, suppliers, customers), and AI-powered customer product / service innovation. The AI factory has people with different skills, different ways of collaborating, and greatly improved capabilities to innovate and serve better.
[1] AI-powered Businesses will Rule the Future is the title of an MIT Technology Review article authored by Avrohom Gottheil, the founder of AskTheCEO Media, recapping his conversation with Gary Bhattacharjee, AI practice leader at Infosys, about the evolution of AI and how it will transform businesses in the future. There is mention of AI use cases in the brokerage business.
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