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After yesterday’s discussion of being careful with customer data, AI may be the solution. In previous examples of data sharing, such as those mentioned with Barclays and ING ten years ago, it was too much of a blunt instrument. The intelligence was lacking. But I can see banks moving stealthily into customer data sharing, targeting, advertising and more over the next few years using AI tools.
It’s already happening as vendors start to integrate ChatGPT AI tools into financial advice and planning. A good example is Datarails. This innovative solution leverages generative AI to provide instant insights about budgets, forecasts, variances, and spend, enabling finance professionals to make data-driven decisions more efficiently and effectively.
According to the Weekly Fintech Digest on LinkedIn, there are three big benefits of doing this.
- First, it enhances the speed and accuracy of information provided by financial analysts to executives through Fast Finance Requests. This feature allows analysts to instantly generate extra analysis as needed, reducing the time spent on ad-hoc requests and enabling them to focus on strategic tasks.
- Second, [it] provides Executive Self-Service, allowing executives to directly ask detailed financial questions and receive instant answers without tying up the finance team. This feature empowers decision-makers with real-time insights, facilitating more informed and timely decisions.
- Third, the AI Storytelling Assistant transforms complex financial data into engaging presentations and visuals with just a few clicks. This feature helps finance professionals effectively communicate insights to stakeholders, making the story behind the numbers more compelling and actionable.
Interesting but then, as I pointed out the other day, is your AI compliant? That’s a big question. Imagine if your AI service offered the wrong advice or was hacked and redirected customers to a cybercriminal’s service. Just an fyi.
Having said that, I am seeing AI in finance growing fast. It began with simple things like checking contract wordings for JP Morgan or redirecting emails for UBS, but it’s now getting more intelligent by a ten-fold.
Take the example of European challenger bank Bunq.
Bunq’s AI-powered bank offers Finn, an AI-powered bank analytics engine that ‘can give you insights and answers you might never have considered. For example, Bunq gives answers to advanced questions like “What is the average amount I spend on groceries per month?” or “How much did I spend on Amazon this year?”. It can even combine data to answer questions that go beyond transactions, such as “What was that Indian place I went to with a friend in London?”, or “How much did I spend at the cafe near Central Park last Saturday?"’
The challenge with AI enabling bank statement insights, digital lifestyle management or any aspect of financial service electronically, is are you doing it right? Is it regulated? Are you compliant or in breach of the rules? And more.
In fact, according to Jamie Dimon, AI is as transformational today as the printing press was centuries ago.
While we do not know the full effect or the precise rate at which AI will change our business — or how it will affect society at large — we are completely convinced the consequences will be extraordinary and possibly as transformational as some of the major technological inventions of the past several hundred years: think the printing press, the steam engine, electricity, computing and the Internet, among others.
Specifically, he devoted a large part of his annual shareholder letter to the importance of AI for the Wall Street giant’s business and for society at large. Here’s some of what he said:
THE CRITICAL IMPACT OF ARTIFICIAL INTELLIGENCE
Since the firm first started using AI over a decade ago, and its first mention in my 2017 letter to shareholders, we have grown our AI organization materially. It now includes more than 2,000 AI/machine learning (ML) experts and data scientists. We continue to attract some of the best and brightest in this space and have an exceptional firmwide AI/ML and Research department with deep expertise.
We have been actively using predictive AI and ML for years — and now have over 400 use cases in production in areas such as marketing, fraud and risk — and they are increasingly driving real business value across our businesses and functions. We're also exploring the potential that generative AI (GenAI) can unlock across a range of domains, most notably in software engineering, customer service and operations, as well as in general employee productivity. In the future, we envision GenAI helping us reimagine entire business workflows. We will continue to experiment with these AI and ML capabilities and implement solutions in a safe, responsible way.
While we are investing more money in our AI capabilities, many of these projects pay for themselves. Over time, we anticipate that our use of AI has the potential to augment virtually every job, as well as impact our workforce composition. It may reduce certain job categories or roles, but it may create others as well. As we have in the past, we will aggressively retrain and redeploy our talent to make sure we are taking care of our employees if they are affected by this trend.
Finally, as a global leader across businesses and regions, we have large amounts of extraordinarily rich data that, together with AI, can fuel better insights and help us improve how we manage risk and serve our customers. In addition to making sure our data is high quality and easily accessible, we need to complete the migration of our analytical data estate to the public cloud. These new data platforms offer high-performance compute power, which will unlock our ability to use our data in ways that are hard to contemplate today.
Sounds like a good reason to buy my new book! (releasing April 17)