Investing in Building Great Experiences

Saturday - September 30 2023, 06:04 UTC - 1 year ago

When it comes to banking, customer experience is Key. JPMorgan Chase is leveraging best practices, cost efficient cloud migration, and emerging AI and machine learning (ML) tools to build better ways to bank. AI/ML is commonplace, and is being used to extract data from documents, classify information, analyze data smartly, and detect issues and outliers. In the near future, AI/ML is expected to be used to proactively predict client needs.

When it comes to banking, whether it’s personal, business, or private, customer experience is everything. Building new technologies and platforms, employing them at scale, and optimizing workflows is especially critical for any large bank looking to meet evolving customer and internal stakeholder demands for faster and more personalized ways of doing business. Institutions like JPMorgan Chase are implementing best practices, cost efficient cloud migration, and emerging AI and machine learning (ML) tools to build better ways to bank, says Head of Managed Accounts, Client Onboarding and Client Services Technology at J. P. Morgan Private Bank, Vrinda Menon.

Menon stresses that it is critical that technologists stay very focused on the business impact of the software and tools they develop. "We coach our teams that success and innovation does not come from rebuilding something that somebody has already built, but instead from leveraging it and taking the next leap with additional features upon it to create high impact business outcomes," says Menon.

At JPMorgan Chase, technologists are encouraged, where possible, to see the bigger picture and solve for the larger pattern rather than just the singular problem at hand. To reduce redundancies and automate tasks, Menon and her team focus on data and measurements that indicate where emerging technologies like AI and machine learning could enhance processes like onboarding or transaction processing at scale.

AI/ML have become commonplace across many industries with private banking being no exception, says Menon. At a base level, AI/ML can extract data from documents, classify information, analyze data smartly and detect issues and outliers across a wide range of use cases. But Menon is looking to the near future when AI/ML can help proactively predict client needs based on various signals. For example, a private banking client that has recently been married may ask their bank for a title change. Using the client’s data in context and this new request, AI/ML tools could proactively help bankers identify additional things to ask this client, such as need to change beneficiaries or the possibility to optimize taxes by considering jointly filed taxes.

"You have an opportunity to be more proactive and think about it holistically so you can address their needs before they even come to you to ask for that level of engagement and detail," says Menon.