From Legacy Systems to Intelligent Infrastructure: A Roadmap for AI-Driven Banking IT

Abstract

The banks are still using legacy systems as the core of their business. One of the reasons is that the financial and operational data are stored here and can be used for decision making. Other reasons are that applications developed for many years and very high costs for these applications to be retired. On the other hand, technology and in the past year, a cataclysmic evolution of technology and client demands. This trade-off between stability on legacy systems or competitive advantage on modern architectures, as there are many known cases of banks that have collapsed due to not adapting quickly enough is still a hot topic for many industries, not just banks. The risk and costs of switching to new system is high enough. The objective of this article is to present the main risks and costs of using legacy systems, the preferences of the bank users in terms of software reliability and subjective assessment of the software systems' modernity, an overview on new intelligent IT infrastructures, the preferences for the modernization of systems and a SOLUTION of the modernization of legacy banking systems using an open architecture [1]. Artificial Intelligence (AI) is now widely acknowledged as one of the most important digital transformation enablers across a significant number of industries including the banking sector. AI technologies are assisting the banks in India in upgrading their operations across the board from accounting to sales to contracts to cybersecurity. This paper aims to analyze the application of AI in Banks and to take a case study based on the virtual Assistant of SBI-SIA. The evolution of banking and the emergence of virtual banking was explained in this and the trends in the modern Banking systems were explained along with a Rationale use of AI in Banking [2].