Potentials of developing AI solutions in the Sri Lankan banking industry

Abstract

Banks are chasing AI-based implementations to gain a competitive advantage and benefit in bank operations. In addition to improving fraud detection and regulatory compliance, these deployments are thought to lower operational costs, lower risk, enhance tailored client experience, enhance loan and credit decision-making, automate the investment process, and so forth. While the world banking industry has gone so far with AI implementations, it is interesting to investigate where the Sri Lankan Banking industry is today with AI and the potential of effectively developing AI solutions in the Sri Lankan banking industry. This research has addressed this problem via eleven interviews with Sri Lankan banking industry experts in different banks and one AI- based IT company that works with banks. This research was completed using the qualitative analysis method influenced by the Straussian grounded theory. This study's data came from a series of observations and interviews. The current usage of AI in Sri Lankan banks is observed mainly with chatbots on websites. Additionally, experimental AI usage, including customer behavior analysis, customer onboarding, and loan portfolio management, is observed through research data analysis. AI in Sri Lankan Banks is driven mainly by competitor pressure. With current implementations, the Sri Lankan banking industry is at the “Active level” of Gartner’s AI maturity model. There is far more potential to grow ahead with AI implementations. Challenges identified in AI implementations in Sri Lankan banking include security-related regulations & compliance, knowledge gap (internal, outsourcing), Data availability, and return on investment. This research also presents recommendations for effectively integrating AI Solutions within the Sri Lankan Banking Industry.