AI & ML in Digital Banking

The technical challenges banks need to overcome to transform the customer experience and strengthen efficiency

- Kalyan Gottipati

IN TODAY’S fast evolving financial world, the demand for innovation and operational efficiency is as high as ever. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into digital banking operations is changing customer experience in ways that the world has never before witnessed.

Banks are being empowered to offer greater personalization of services as well as to improve the efficiency of overall service delivery, decision making, and security through AI and ML. Let’s take a look at how these technologies are transforming banking services, the real-world results they can yield and the technical challenges banks need to overcome to unlock their potential.

The Growing Role of AI and ML in Digital Banking

The global AI in banking market is expected to grow a compound annual growth rate (CAGR) of 23.37% from 2020 to 2025, with financial services being a hotbed of AI adoption. This growth is fueled by a growing need for personalized banking experiences and the operational efficiencies in an increasingly digital first world.

Integrating AI and ML into banking systems: The technical roadmap

Banks must take several technical steps to adopt AI and ML successfully:

◼ Hybrid Cloud Architecture: Many banks still use legacy on-premise systems. Working around that barrier has to do with a hybrid cloud architecture. This enables banks to incrementally migrate workloads to the cloud while still having complete control over sensitive customer data in on-premise environments.

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