Artificial intelligence needs real human thoughtfulness.
Chisoo Lyons underscores that apparent irony when talking about the challenges of building AI and machine-learning models for the vehicle-financing industry.
She is a vice president for credit scorer FICO. She leads its advanced analytic initiatives centered on data-driven decision-making.
“Why you are doing it is more important than how you are doing it,” she says at a recent American Financial Services Assn.’s annual Vehicle Finance Conference.
She adds that such efforts require “empathy and communication skills,” two decidedly human traits. (Chisoo Lyons, left)
Much of the finance conference covers using AI and data analytics for car-financing decisions, ranging from whether to approve a credit application to how much of a credit line to advance.
“We need the best people and the best tools,” Lyons says. Each alone “is not enough.”
She describes the strengths and weakness of each.
“People understand context, but they are limited to prior experience and they’re slow,” says Lyons, who holds a master’s degree in industrial engineering from the University of California-Berkeley. “Systems don’t understand context, but they are fast and not limited to prior experience.”
In a Gartner survey, chief information officers ranked AI, machine learning and data analytics as “game-changing technologies.”
Lyons says successful initiatives rely on technology, human expertise and leadership.