Beyond personalized customer experiencesAnkit Bhatt, Senior Vice President of Omnichannel Experience at US Bank, discussed how the organization’s goal is to become central to its customers’ lives. It’s not enough for US Bank to deliver personalized customer experiences — this is “table stakes” as Bhatt explained. Instead, US Bank wants to use AI to anticipate its customers’ needs and simplify their interactions with the bank so they can focus on running their businesses. This includes using AI to predict cash flows from small business customers’ transaction history so they can avoid overdrafts on their accounts. It also includes real-time account opening, loan approvals, and account funding so that business owners get access to the critical funds they need, when they need them. Bhatt explained that the culture at US Bank is focused on customer obsession, and that AI is not just about the technology; it’s about “bringing an experience to life.” Currently the bank is running close to 100 AI-based applications to support this goal. Bhatt and his colleagues at US Bank believe these experiences will develop fiercely loyal customers.
Where AI should be appliedWhen deciding how to use AI in a financial institution, the applications are potentially endless. Emil Matsakh, formerly Executive General Manager, Chief Analytics Office of the Commonwealth Bank of Australia, explains that machine learning algorithms within a financial institution should be focused on 3 core areas:
- Improving the customer experience and their financial well-being through personalized insights
- Optimizing risk-taking, vs. just managing risk
- Enhancing productivity