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Training Bankers to Be Data Scientists

This article is from the annual FinTech Forward special report.

One of the hottest topics in Big Data has little to do with technology. But it does have a techie-sounding buzzword: "operationalization."

The term refers to bringing analytics to the front office. It means giving retail bankers the tools to estimate a customer's lifetime value, or see a log of a customer's activity on the bank's website. Sometimes, it means requiring employees to look at a predictive model before they make an offer to the customer.

It's a futuristic vision of banking that, in the coming year, may come closer to reality. In a recent American Banker survey, 36% of bank executives said they were looking to sign new contracts with providers of analytics services.

Charles Thomas has big plans for Big Data and operationalization at Wells Fargo. "Imagine," he said excitedly, "being at an ATM, picking up a mobile device, walking into a store, and having all of that connected in real time," so a front-line banker can "have the right conversation" with the customer.

Thomas, the bank's chief data officer, insists it won't take a "tech revolution" to get there. Rather, it will involve making sure employees have the right skills.

"My question is, how are we really going to get data and analytics as part of our core business processes?"

A core part of Thomas' role at Wells Fargo involves setting a strategy for employee training and development.

He joined the bank in March as its first-ever chief data officer. In his first few months on the job, he has focused on assessing the skills of employees across the bank's business units.

"You'll hear me talk a lot about the people component," he said. "We spend a lot of time talking about tech and tools, but ultimately somebody has to develop an insight into the data."

Discussing his priorities for the coming year, Thomas said he has no plans to hire teams of highly trained data scientists. Instead, he wants to focus on employee development.

"My job is to make sure they have the best skill set," he said.

In a parallel trend, banks want to "democratize" their analytics programs, said David Wallace, a manager at the data management and analytic software provider SAS. They want to give front-line employees the software to easily run back-office calculations.

"If I have a simple, easy-to-use data visualization environment that has automatic analytics in it, I just need to click a button," Wallace said.

DOWN-TO-EARTH VISUALIZATION

This type of software was recently adopted by the Bank of North Carolina. The $3.2 billion-asset bank uses a SAS program that draws on 300 data fields to create easy-to-read charts on topics ranging from loan performance to mobile usage.

Analytics of this kind may change the way many employees approach their jobs. "It's getting into that mind-set where, before I decide what I'm going to do next, I'm going to run the numbers," Wallace said.

Ambreesh Khanna, a vice president in Oracle's financial services unit, said incorporating analytics programs into a bank's front office is "where the next big push is."

He described it as an area of software development that's still in the works. But the most important component, he agreed, is to give employees the training they need to feel comfortable relying on statistics.

"It's not a technology issue, it's a change in the mind-set of how banks operate," Khanna said. "That's where some of the hesitation is today."

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I think it is impossible to turn front-line bankers into data scientists, having tried for several decades myself. To make data work for front-line bankers, the data scientist has to think like a CEO, CMO, CIO, retail head, & front line sales person. They have to deliver "done for them" tools that enable them to do do what the data says to do rather than interpret it themselves. "Call Customer X and talk about this service"; "When Y customers calls for support put them in the front of the line", etc.

I can't stress this enough. Bankers have enough to do without having to analyze the data some "data scientist" gives them. I tried numerous years to help retail & branch mgrs understand their particular data & execute on it. What I found was they didn't have the skills or desire to be analytical. They were in those positions for a reason...they filled the required skillets & enjoyed them. When I tried to make them be like me some were excited at the potential, but even they didn't have time.

I'll never forget the day when a high level retail head told me the data & explanations & sales possibilities were awesome but he didn't have time to deal with it. After cooling off I made a conscious effort from then on to create systems that eliminated analysis on the banker's part & focused on simple execution. That made them happy, which of course made me very happy.

The premise of this article is good, but the onus is on the guys behind the scenes to do the heavy lifting so bankers can do what they do best.
Posted by Scott McClymonds | Friday, November 07 2014 at 2:28PM ET
Making bankers to be data scientists sounds like a huge undertaking but that is world we are moving towards. Analytics will be part of our daily lives and be part of everything we do. Technology is moving at the right pace but I don't see how highly regulated industry like banking can move fast enough to solve their data governance and other Basel like requirements.

Mark
http://www.infocaptor.com
Posted by markzubin | Friday, October 31 2014 at 10:09AM ET
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