Artificial intelligence (AI) is rapidly evolving across various parts of the banking and payments sectors, and digital consumers are reaping the benefits from institutions that apply this technology.
There are an increasing number of operational use cases for AI as well, which are proving beneficial to employees looking for more efficient ways to complete routine tasks.
To provide a few brief examples, AI is used in the marketplace across a wide range of functional areas including servicing accounts via voice or chat and through budgeting and lifestyle maintenance. With the help of deep analysis and analytics tools, many AI initiatives are designed to understand and improve various consumer behaviors and answer basic consumer inquiries to alleviate pressure on employees.
From an operational standpoint, AI can be utilized for back-office efficiencies like conducting compliance tasks and automating manual, paper-based processes. This redirects resources and human capital in a way that is likely to increase productivity.
Banks like JPMorgan Chase have been investing in AI for years, leveraging this technology to review contracts more efficiently and extract important points and legal clauses from complex documents. Others, like India's Standard Chartered, are deploying AI to help identify and stop illegal transactions.
While these applications are a step in the right direction, most of the aforementioned projects only scratch the surface when it comes to leveraging the potentially transformative power of AI.
Deloitte
Simply put, the underlying technology infrastructure that banks currently use was not created to support the AI technologies that exist today.
Some top banks are realizing the constraints of legacy technology and are beginning to take action, understanding that the complete tech overhaul process can sometimes take years. But by making key decisions to improve – even if slowly at first – these financial institutions are well down the path to becoming digital to the core before others only start to realize the need for change. Banks that are not considering changes to legacy technology risk losing their competitive edge, and potentially face market stagnation.
Moving beyond AI, legacy infrastructure also hinders banks from taking advantage of other cutting-edge technologies such as big data processing and analytics. By leveraging these innovations, banks will gain access to real-time data and insight, identify fraud at a much more efficient rate and unearth opportunities to automate additional manual tasks reaching well-beyond their current capabilities.
While some financial institutions are moving forward with upgrades to their legacy systems, many banks are constrained by concerns related to cost and risk. However, through the use of microservices architecture, open banking and plug-and-play software, these concerns can be mitigated. Replacing legacy systems doesn’t have to be the monumental task it once was.
Leveraging next-generation payment platforms with a modular design and rich suite of APIs, financial institutions can streamline the process of replacing legacy systems one component at a time. The use of modern approaches enables the replacement of single components like the customer management system or the transaction ledger – while continuing to serve other functions from legacy systems – allowing platforms to de-risk and enable transformation projects.
It’s time for banks to seriously consider investing in new infrastructure, even if slowly at first, in order to gain a competitive edge and to be able to take full advantage of modern fintech innovations.
