Traditional banks are struggling to keep up with new-age financial services businesses that are gaining advantages from data-driven technologies. However, revitalizing legacy systems with new data-driven technologies, processes, and products can enable scale, driving better customer experiences. Automation in the banking industry can save between 30% to 70%, and various areas can benefit, such as customer service, accounts payable, and HR services. Read on to know how AI-driven process discovery helps identify repetitive and mundane processes, ultimately leading to cost savings and efficiency improvements.
Traditionally, the banking industry was at the forefront of tech-driven transformation. However, the once innovative and cutting-edge technologies have turned into legacy systems. Traditional banks need help to keep up with new-age banking and financial services businesses gaining advantages from new data-driven technologies.
Traditional banking organizations must revitalize their legacy systems by introducing new data-driven technologies, processes, and products. When combined with legacy infrastructure, these new-age systems have the advantage of scale, enabled by vast volumes of historical data that drive better customer experiences.
In the banking industry, there are many areas where manual work can be replaced with automation tools to free up efforts for more effective use elsewhere. Effective banking drives growth and provides hassle-free banking experiences to customers.
As mentioned earlier, the banking industry faces the challenge of ageing, legacy applications, and an intricate web of processes. Further, the nature of banking operations is strictly regulated, and there is no easy access to applications and processes. The data stored includes customers’ personal and confidential data, which Data Privacy and Protection Acts regulate.
A 2020 PwC1 report states that a staggering 81% of banking executives are overwhelmed by the speed of technological change that calls for constant refinement and restructuring of business processes.
Despite being one of the most data-driven sectors, the banking industry must catch up in digital transformation due to core legacy systems developed in the 1970s. The scope of this problem is enormous, with Reuters reporting that almost 43% of US banks use COBOL2, a programming language from the 1950s. These legacy tech stacks are incompatible with digital technologies, making legacy system replacement projects massive, expensive, and, most importantly, risky.
One of the largest Fortune 500 financial services companies in the US, with a wide range of services across retail, commercial banking, investments, insurance, wealth management, asset management, corporate banking, capital markets & specialized lending, was facing a high volume of complex manual processes leading to increased processing time & errors. Employees were spending manual efforts in high volume, low dollar chargebacks leading to potential revenue loss, accounting processes requiring manual checks & validation across several applications, and a high frequency of ATM audits, fraud reporting, credit card loan verification, teller cash reconciliation and financial insights leading to increased error rates in processing.
AI-driven process discovery helps deliver business process insights by accumulating process and task-level data from user devices across the bank, analyzing the collected data, providing insights using visually rich process maps, and creating a blueprint for automating the right processes. During this process, care is taken to ensure compliance with data security and privacy policies.
AI-driven process discovery in banks consciously discovers processes that need to be automated and validate them based on the frequency of execution, efforts involved, and business expectations. This helps banks derive cost and effort savings for automated processes, have a session with businesses, and finalize the processes based on the above points.
The US financial services company adopted AI-driven discovery to streamline its manual processes. They identified over 45 techniques and 35 applications that could benefit from automation and used continuous integration and deployment to create over 230 bots in production. The results have been impressive, with an estimated annual savings of US$184k and a 5% increase in customer satisfaction.
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Automation is becoming increasingly important in the financial sector, especially in banking. As more and more banks are shifting towards online and mobile applications for managing customer accounts, it’s becoming harder to retain customers and stay competitive. But, banks can differentiate themselves by effectively utilizing their workforce and getting the best out of them. And that’s where AI-driven process discovery comes in! Process discovery can save businesses time and effort by effectively identifying repetitive and mundane processes, ultimately leading to cost savings.
Disclaimer Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the respective institutions or funding agencies
