How Financial Institutions Can Use AI and Data-Driven Techniques to Improve Performance and Profitability
Produced by: BankTalk
Host: Charlie Kelly, Partner at Remedy Consulting.
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While AI is not a new concept, its use by community financial institutions is.
AI and advanced analytics have long been shown to make banks more productive and profitable, but price and complexity have limited their use to only the largest financial institutions. Now that is changing.
In a recent podcast with BankTalk host Charlie Kelly, Supreet Singh, Finlytica CEO, discusses how community financial institutions can use data and AI to measure performance and put those insights into action to drive change.
Supreet explains the approach to collecting relevant customer data based on the institution’s end goals and the outcome they want to target. He also describes how bringing in an expert who understands what data to collect to support specific use cases, who can pull the data from the bank’s various silos, and then provide an integrated platform for running data analysis can help accelerate time to value.
Further in the episode, Supreet and Charlie talk about specific uses of AI in banks, such as revenue growth, profitability, and risk management, and how analytics can not only improve performance but also have a direct impact on building strong customer relationships. Finally, Supreet shares some of the KPIs to track while measuring performance, such as the number of accounts, wallet growth, and product penetrations.
Today, AI technologies are integral to running a community bank, and community bankers need to deploy these technologies at scale to compete with large banks and non-bank competitors.
Listen to the podcast and get insights into how banks should be thinking about data and analytics as a tool to improve performance.