How AI Partnerships Can Empower Traditional Banks
Find out why partnerships are the best way for traditional banks to harness AI if they don’t want to lose customers.
The path to AI (artificial intelligence) adoption is riddled with challenges, including talent shortages and cultural barriers. Dr. Anna Becker, CEO and co-founder of Endotech.io, explains why partnerships with AI-oriented firms emerge as a strategic avenue for banks to deliver innovative financial services.
Artificial intelligence has been a game changer in many areas of business and industry. However, it has yet to realize its potential in the banking sector. With only 32% of financial service providers using AI for any purpose, banks have a long way to go before they can take full advantage of everything this fast-developing tech offers.
For banks, taking advantage of AI isn’t a luxury. Today, dozens of apps and websites offer services that directly compete with banks, and those offerings are usually cheaper, more convenient, and more efficient than what banks can offer. Digital banks and banking service apps are slowly but surely taking customers away from traditional banks – and over a quarter of Americans do their banking strictly online. If traditional banks want to avoid losing more customers, they need to innovate – and innovation in 2024 is tightly linked with AI.
Banks use AI most often for security, with advanced data analysis systems used to detect fraud, hacking attempts, and other cyber threats. In addition, AI currently helps many banks optimize IT operations, automate customer service, and boost digital marketing. Banks that aren’t yet using AI for these and other purposes are very interested in doing so – with 85% of IT executives in banking reporting that they have a “clear strategy” for adopting AI in the development of new products and services.
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While banks’ current AI uses are important, there are great untapped opportunities for traditional banks to utilize AI for advanced financial services. And those are in their exact area of expertise — financial service.
More banks could use AI to conduct predictive analysis on investment opportunities for their customers, guiding the best investments for them based on their income, lifestyle, age, family situation, savings, and other factors while using advanced machine learning and AI algorithms to match customers with the investments that will yield the most potential for them.
These new services would be a welcome change for many customers. It offers a vast improvement over the current advisory system, where bankers can provide limited information and data on investment opportunities, often based just on a prospectus and a basic Google search. AI should also play a bigger role in asset trading for banks’ customers, helping them make the most of market movements.
Other areas where AI will change the way banks work include customer verification; dynamic risk analysis, ensuring that customers don’t get in over their heads on risky investments or loans; customer behavior analysis, allowing banks to serve clients with tailor-made product offerings better; and automated onboarding, using advanced LLMs (large language models) to communicate with customers opening accounts or buying new products. AI could thus make these and other activities a lot more efficient and cost-effective for banks – while providing customers with an enhanced level of service and greater safety and security.
Among the examples of banks using AI for these purposes is JPMorgan Chase, CNBC reported that the bank is developing an AI-driven ChatGPT-style engine that will work with investors on where to put their money. According to the patent filing, the bank has already requested a patent for its system, called IndexGPT, which will “tap cloud computing software using artificial intelligence” for “analyzing and selecting securities tailored to customer needs.”
Deutsche Bank, too, is utilizing AI for investment offerings. Adriyan Eliyahu K. calls it The Bank’s “Next Best Offer” algorithms examine investors’ portfolios and provide them with investment options – but if a better offer becomes available, the algorithm will suggest switching to the better alternative.
The system considers numerous factors – demographics, income, risk tolerance, fees for switching between investments, and much more, with the algorithm “checking that the expected benefits of switching exceed the costs” of switching. It will provide the customer with an advantage.
Morgan Stanley, as well, is embracing AI, having recently rolled out a chatbot that draws on huge amounts of data to help financial advisors work with clients seeking investment advice. Here, the chatbot can also draw on the data associated with a client’s account and life situation. It uses machine learning and other advanced AI technologies to guide investors toward the vehicles that will most benefit them. The chatbot is based on OpenAI technology and is geared toward assisting human advisors, who “will always be the center of Morgan Stanley wealth management’s universe,” according to the Bank.
See More: Why Banks Need New Technologies To Catch Up With Buy Now, Pay Later Fintech Companies
Facing Talent Scarcity: Banks Struggle to Drive Innovation
With that, these banks are outliers; few can build a system like this in-house, and even a giant like Morgan Stanley is working with an outside organization to develop its chatbot technology, as is Deutsche Bank. For banks that don’t have the resources of these giants, the idea of building an AI service in-house is likely an impossible dream.
And even if they had the resources, there just aren’t enough engineers and data scientists to go around – and those available demand very high salaries. Thus, for many banks, the lack of forward movement in developing AI services comes down to a lack of skilled personnel. There’s a huge skills gap in AI – three-quarters of companies in all sectors report difficulty acquiring talent.
When acquiring that talent, banks are struggling more than many other sectors. With its reputation as a staid, conservative industry that eschews all but the most necessary changes, the banking industry is a hard sell to dynamic professionals with high-level AI skills, who are more likely to seek work in a high-level tech firm, where they will have a much better opportunity to innovate.
Meanwhile, there is fierce competition in the sector over the limited AI talent, with giants like Goldman Sachs, Morgan Stanley, and Citigroup outright competing for the same small pool of available professionals. At the same time, banking’s conservative culture also holds it back from having a comprehensive vision of what AI can do and why it is so necessary. Given that, how does a traditional bank advance its AI offerings?
The easiest, fastest, and most efficient way is to partner with AI-oriented firms, such as fintechs, that can set banks on the path of AI innovation. Such companies will have already garnered experience in developing financial products. They will be familiar with legal and regulatory issues, and their technology enables banks to inaugurate and provide the services their customers demand quickly.
This approach can help banks reduce development risk, learn from the implementation experiences of other players, weigh the actual vs. promised benefits of different providers, and shorten time to market by avoiding often excessively long software and system development cycles. Partnering with an AI-oriented data analysis company that can build customized algorithms, develop appropriate LLMs, and construct the appropriate data capture systems enables advanced machine learning to work its magic.
AI Partnerships Can Empower Banks
The partnership model works – and is being adopted by some of the world’s biggest banks. Deutsche Bank, for example, initially attempted to build an AI infrastructure in-house, bank executives said. Still, they realized that partners with AI-oriented firms was much more efficient, based on the realization that Deutsche Bank “is not an IT company, but a bank.”
Meanwhile, Japan’s Mizuho Bank partners with Microsoft on several projects using its Azure platform, including one that enables traders to time their bond trading better and realize maximum benefit from those trades. The Commercial Bank of Dubai partners with PWC “to accelerate the adoption of AI technologies across CBD’s operations,” focusing on “elevating customer experiences and enhancing engagement through personalized AI-driven customer service solutions.”
The potential for banks, both large and small, – and customers – is enormous. Both can benefit immensely, for example, from new products based on automated AI risk profiles for various markets, something that in the past has taken hundreds of hours and dozens of developers to build. With machine learning-based advanced AI, that development is largely automated, and the development results are much more accurate. This is the kind of work banks would be unlikely to do on their own – but very likely to do with an AI partner.
Banks can offer These kinds of services using AI – and they are the better, more advanced investment advice services customers are looking for. If customers can’t get those services at traditional banks, they will turn to other fintech startups that can provide them. And that holds for other traditional banking services that fintechs or other providers can provide more cheaply, efficiently, and effectively. Banks that want to avoid losing out need to adopt AI more aggressively, sooner rather than later, and the most reliable and efficient way to do so is through leveraging partnerships.
What steps has your organization taken to streamline the business processes with help of AI? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
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