How Associated Bank Uses Data Analytics to Speed New Products and Drive Growth
A strong emphasis on data analytics led by Chun Schiros, a veteran of data analytics at Regions Bank, helps the bank better meet customers' needs and improves development of new products and services. AI will be one of multiple tools she'll use.
By Steve Cocheo, Senior Executive Editor at The Financial Brand
Some corners of banking have a high-touch legacy, where the bankers feel they know the clientele well and see no need for technology to improve their understanding.
Bank data scientist Chun Schiros understands that tradition. "Banking is a trust- and relationship-based business and the connections between customers and bankers are critical," says Chun.
On the other hand, she says, data analytics can turn up insights in the vast troves of raw customer data that banks hold, data that human minds alone sometimes don’t correlate.
"Relationship managers and financial advisors have hundreds of customers on their books. They can’t have spent all of the time to really get to know them all well," explains Schiros. "But data analytics can enable them to cultivate deeper and better relationships."
"High-touch and high-tech are not mutually exclusive ways of serving our customers," says Schiros. "In fact, each should augment the other."
That augmentation is a key part of Schiros’ job description. In May 2024, she became senior vice president and chief analytics officer at Associated Bank-Corp, #59 among U.S. bank holding companies. She arrived at Associated after close to a decade in data analytics at Regions Bank, where she rose to SVP and head of the enterprise data science group. Before that, Schiros, who holds a doctorate in electrical engineering, worked for six years in data analytics in the field of cardiovascular disease at the University of Alabama.
Amping Up Associated’s Data Analytics Efforts
Associated Bank hired Schiros to improve data analysis, use of AI, and the connection of both with product design, all in support of some strategic shifts.
For example, the bank is in the process of putting greater emphasis on business lines that offer more opportunity for building out multi-product relationships. This includes such steps as building up prime and super prime auto lending and deemphasizing mortgage banking. It has also meant reducing wholesale funding in favor of more core deposits. At the end of 2022, Associated also launched a mass affluent banking program.
Schiros’ two main goals are, first, to improve the bank’s use of data to establish, deepen and retain customer relationships in all business lines, and, second, to use data insights to improve products and services.
In these days of continuous streams of news about GenAI, Schiros says it’s important in her business not to confuse tools with purpose.
"Leveraging AI, leveraging machine learning, leveraging statistical analysis, and leveraging data are my tools for extracting insights and turning them into actions," says Schiros. She says the most important step is deciding what the bank wants to accomplish, and then choosing the tools that will get the job done.
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Framing Data Analytics Goals Begins with the Ending
Schiros says she has found a helpful guide in the Amazon Web Services concept of "Working Backwards."
"This means understanding what you need first and what type of goal you want to achieve and working backwards from there," says Schiros.
The essentials of this were set down in a 2006 blog by Werner Vogels, VP and chief technology officer at Amazon. Vogel’s concept literally begins with writing a press release announcing the product, what it does, and why it exists. Other end-game documents created using this approach include a FAQ and even a user’s manual.
Then, according to Vogels’ blog, "work your way backwards until you get to the minimum set of technology requirements to satisfy what you try to achieve."
Schiros will use elements of this approach where practical. Among the priorities her function will be addressing how to expand lending and deposit capabilities and enhancing the experience on the bank’s digital platforms. This follows on a major modernization of the bank’s digital experience that continues.
Key for Schiros will be helping the bank to develop products and services that can be scaled when they prove out.
"Agility is a key component for us," says Schiros. "It is important that we have a flywheel-like framework where ideas are quickly prototyped, pushed to pilot, and then brought up to minimum viable product level. That allows us to test and learn."
Patience is also required.
"Data," says Schiros, "is not something that you can turn into gold overnight."
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Getting Things Right Means Knowing What Right Looks Like
"Everything we do project-wise and product-wise has to support a business need," says Schiros. "I often tell my teams that nothing will create value unless it’s being used."
Accomplishing this requires coordination and communication between Schiros’ staff and the bank’s product team, marketing team and line of business. She says it’s critical to understand what the bank is trying to do — working backward, again — and, often, devising metrics that will help determine if the goals are being met.
There’s a balancing act, too, in that the ideal scope sometimes has to be sacrificed to the present.
"We can’t be building a missile to the moon when our business units need to have some immediate impact on results."
— Chun Schiros, Associated Bank
Ultimately, Schiros says getting data analytics and its role vis-à-vies products and services right has a payoff: "It is the secret sauce of how your bank can differentiate itself."
