Actually, to some degree they are already here. Today we can buy robots to do simple tasks around the home, and we increasingly see industry turning to robotics to perform functions that were once done by humans. Robots are faster, more efficient, do not take coffee breaks and are not concerned with work/life balance. They can work efficiently and without complaint, with only occasional breaks for their human overseers to repair and update the machinery and perform any necessary programming.
The use of robots—or at least the technology that powers them—is coming to banking as well. There are many areas of banking that can be improved by the use of artificial intelligence and robots to perform tasks faster and at much lower costs. We’ve already seen how technology can automate and improve the arduous task of regulatory compliance, a phenomenon that is often referred to as “regtech.” Much of the compliance process involves the assembly and storage of an almost endless stream of documents, and that is something best done by machines. Oversight of the lending and sales practices can also be done much more accurately and efficiently through the use of technology and big data than by relying on human involvement alone. In the aftermath of the Wells Fargo & Co. cross-selling scandal, I expect to see more banks employ databases and machines to monitor employees and look for irregularities in sales practices.
I was at the FIG Partners Bank CEO Conference recently, and there was a lot of discussion about using technology and data analysis to improve bank lending programs. Bankers are looking for ways to automate much of the underwriting and funding process for both consumer and commercial customers. While there is still plenty of room to debate the advantages of using automation in the sales process compared to relying on people to bring in deals, there is no question that using big data to streamline the underwriting process has shortened approval times from weeks to just days—and in some cases even hours.
Bankers are also starting to use databases and artificial intelligence to manage their loan portfolios. One banker I spoke with said his bank was using data analysis to continually monitor the current loans in its portfolio. Automated systems can collect data about their customers and compare that against all past borrowers to identify those that might be undergoing financial difficulties. Through the use of artificial intelligence, it is now possible to continually scan the portfolio for signs of loans that may be getting close to stress levels and act proactively to head off problems before they fully develop.
In the low-interest rate, low-growth economic conditions we are currently experiencing, banks are continually looking for a way to raise fee income. One of the favored strategies for growing fee income is wealth management, and right now so-called robo-advising is the hot topic in the money management space. Intelligent systems can continually review and test investment strategies and use the gained knowledge to design optimal plans to manage a client’s money. The cost of machine-managed accounts is often much lower than using a human advisor, and community banks can attract customers and raise their fee income levels by using these programs. Those that do not use these machine managers will need a strategy to compete with them, especially in the tech-savvy millennial market.
Banks can also use data management programs to improve their marketing. By collecting and sorting customer data and history, banks can identify customers that are likely targets for different products and services. Cross-selling is temporarily a bad word in the aftermath of the Wells Fargo debacle, but the truth is that the more products a customer has from a particular bank, the deeper their loyalty to the institution will be and the more profitable the overall relationship for the bank. By profiling customers and monitoring current activity levels in deposit and credit accounts, the robots will spot new needs and opportunities that humans may well overlook.
One area where bankers are reluctant to rely on robots is customer service. While we are seeing mini-branches with ATMs and video links back to the main branch making inroads in some markets, the use of robots in customer facing situations is not something that bankers I have spoken with recently seem to embrace. Most bankers are people just like the rest of us and they have had to endure a customer service conversation with a chat bot that did not go well. Banking is a reputation dependent business and a bad customer service experience can have lasting negative implications on the bottom line. For now, interaction with actual humans will continue to be a big part of the customer experience at most community banks.
The bottom line for most bankers is that if new technology and the use of big data can lower costs and improve the profitability of their institutions, they are generally in favor of adding it to their bank. People will still be a big part of the process for most banks, but the robots and machines will play an ever increasing role.