Over the past 12 months, the banking industry has become increasingly excited about AI. Virtually every leading consultancy has published research on the impact AI will have on the sector and investment continues to pour into developing innovative solutions. But, alongside all the buzz comes to the inevitable concern that the implementation of this technology will reduce the need for actual human workers.
The notion here is simple - if a bank can automate a process then surely they don't need a human to do it. The answer is not as simple, although these sorts of claims are not entirely unfounded. Over the past decade, the digitalization of customer services has led to a decline in the need for front-of-house staff in banks and the subsequent closure of many branches. Similarly, one of the primary areas where banks are implementing new AI solutions is customer services.
Several tier one institutions have developed AI-powered chatbots and virtual assistants. J.P. Morgan uses AI to answer customers' questions and anticipate what their future needs are likely to be, while UBS's virtual assistant is powered by Amazon Alexa. These products are the ones that are most likely to replace jobs. The more that these products are used, the more they learn, which means that they exponentially improve in their capacity to assist customers without requiring human involvement.
Aside from chatbots and Robotic Process Automation (RPA), which uses similar technology to automate simple administrative tasks such as inputting customer information, the way that banks are currently using AI is not a considerable threat to their employees' jobs. A priority for several top-tier banks has been to use AI systems for detecting fraudulent activity or money laundering. This has been particularly successful, having dramatically reduced the time that investigators spent on false positive leads. In these instances, rather than reducing the need for human input, the AI-powered systems have alleviated time pressures on existing investigators and afforded them the time to investigate each case in more detail.
Otherwise, the areas of interest to banks in terms of AI varies considerably from one to the next. Some are focusing on using the technology within algorithmic trading, while others are developing solutions that can offer tailored products to each customer depending on their own circumstances. The crucial point here is that these projects are very much still in development and are yet to be deployed extensively.
Although media discussion of AI in banking has focused on how it is being used to save banks money by cutting jobs, another primary focus for these institutions is using the technology to improve their risk appetite. The risk is central to the banking industry, which is why so many of their employees are focused on measuring it with regard to their customers. Current technologies cannot make decisions in the same way that humans can, but the application of AI can streamline the process. Analysis and presentation of data powered by AI can reduce human bias in the decision-making process and improve the outcome for both institutions and customers alike, without removing workers from the process.
Ultimately, the application of AI to banking will, like with any other industry, eventually reduce the need for human involvement. This is not to say, however, that the banking industry is in line for a mass upheaval where countless jobs are lost. AI has the potential to revolutionize the industry in a different way, by improving operation efficiency in areas of real importance, like tracing money launderers or enhancing the customer experience.