Credit unions and big data: key tips from Susan Etlinger at WOCCU conference

The industry analyst outlined the risks and opportunities presented by the rise of big data

What is the value of big data for credit unions? Understanding the link between what is happening to big data and a business’s ability to generate revenue was a key topic at the World Credit Union Conference in Vienna.

The four-day event featured a presentation by Susan Etlinger, an industry analyst with Altimeter, which focuses on helping businesses thrive by using disruptive technologies. She gave credit unions some key tips on how to be more proactive in terms of using big data, identify potential risks and understand customer experience.

A key example comes from a surgical team at the University of Iowa Hospitals and Clinics, which used Dell’s data research team called Statistica to analyse data. By doing so they were able to make real-time predictions in the operating room, cutting surgical site infections by 58% and lowering the hospital’s costs.

“Once they figured out patterns they reduced incidents,” said Ms Etlinger.

Related: Add value, Robert Herjavec tells Woccu conference

Similarly, a team at IBM worked with French digital finance group Microcred in Senegal. Using current Microcred customer data, the team developed credit scoring models to predict default at different stages in the loan process.

“They tried to come up with an algorithm to identify the signals of financial health and risk factors in that loan,” added Ms Etlinger.

Mastercard is now testing technology that can predict and score risk based on a customer’s typical shopping and behaviour patterns. The technology helps mitigate false credit card declines.

Susan Etlinger warned of the challenges surrounding big data

A TED speaker, Ms Etlinger is on the board of The Big Boulder Initiative, an industry organisation dedicated to promoting the successful and ethical use of data.

She mentioned other uses of big data in the financial sector.

“In the USA artificial intelligence is used to humanise financial services, a system is interacting with consumer and performs simple transactions,” she said.

“This technology relies on big data. The mechanisms used for fraud prevention are used to provide other services as well – not to replace people but take low value, everyday interaction and provide some simplicity to them.”

But there are challenges: one key issue is that big data can miss out important contextual information. Designed in Sweden, Volvo’s driverless cars, which rely on big data, were unable to detect kangaroos when used in Australia. Due to the fact that they move differently from reindeers, the kangaroos were throwing off the car’s detection system.

She warned that big data needed regulation, and had the power to disenfranchise people because it relied on the information it was given. But data can also show where the bias sits.

“We are at a point where people, numbers, consumers, customers can communicate with us at any time of the day. We need to have a clarity of mission to be able to run the business more effectively. Data is a key ingredient in that.

“Don’t let data and technology distract you from the business but it can help you answer some of the more pressing challenges you have,” she concluded, advising credit unions to “find their kangaroo”.

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