In a recent post, I brought up a very serious issue that every data-driven business is now grappling with: how to calibrate the “virtue” of data. In other words, when is it ethical to use all the vast volumes of data we now have access to, and when is it not? Should companies use predictive analytics to gauge whether a customer may be pregnant? Should insurance companies use data to predict someone may suffer a cardiac arrest within five years, and thereby deny coverage due to a “pre-existing condition”? Should we edit genes based on data that says a child may be born autistic?
Those are tough examples that highlight potential negative consequences. Now let’s look at a much more positive example: how to use big data to vastly improve the consumer lending business.
Taking the Shark Out of the Loan
Consumer financing is a much-needed service. You need a cash advance before your next paycheck; you need a few extra bucks to fix your car; you need to pay a bigger-then-expected doctor bill. So you head to the nearest payday lending business and apply for a short-term loan. And in many cases, your eyeballs pop when you look at the interest rate. Could be anywhere from 10% to 100% or more, depending on your personal financial history.
And of course, the payday lending industry is not exactly known for its deep concern with the specifics of your situation. It’s a business Tony Soprano had a lot of experience with. Sometimes it’s convenient for consumer lending companies NOT to consider all available data about a prospective customer so it can charge a higher rate.
Mogo set out to change all that. Mogo is a financial technology company focused on building the best digital banking experience in Canada, and its specialty is using data to bring fairness and convenience to the process. It harnesses big data to help people AVOID the high credit rates of traditional lenders so people have cheaper and more convenient access to credit.
One of the ways Mogo does that is by integrating multiple data sources so that it gets a much more detailed picture of each applicant’s financial situation.
When It Comes to Loans, Integrating More Data Is Just Good Business
Mogo looks at not just the usual credit files from credit bureaus, but also very fine-grained information about each individual’s payment history and habits from many sources. Mogo runs a sophisticated predictive algorithm that provides a very accurate assessment of a person’s ability to repay the loan on time. In many cases that means consumers get the loan they need faster and cheaper than through traditional payday lending companies. It’s a great example of using social analytics to drive consumer benefits.
Since its early days, Mogo has been using Talend as an integral part of its data integration infrastructure.
Originally, they went with Talend’s open source solution because they had a limited budget and needed something robust that would scale. What they found was that as their business grew, Talend grew with them on many fronts.
“We’re building a fully digital financial services platform,” said Thomas Groh, VP of Data at Mogo. “We’re adding not just new data sources but also new data-driven products and services, and we’re making it available on all major platforms—web, IOS, Android. Talend gives us the solid data infrastructure we need to handle all of our business processes, and we aren’t about to out-scale Talend anytime soon.”
Mogo likes a few other things about Talend, including the ease with which they can onboard employees who didn’t have previous exposure to open source data integration tools. “It’s easy from a programming perspective; it’s easy to componentize code and visually separate functions; and it’s easy to put data flows together in a standard way,” Groh said. “I love how quickly we can just get something done.”
Paid Version a “No-Brainer”
For Mogo, there was an obvious benefit in moving from the free edition of Talend Open Studio to the paid support version. “Because of the success of our early prototypes using TOS we soon needed the enterprise-class support, and our success criteria were shifting as well,” said Thomas Groh. “We needed a data integration platform that could orchestrate all points: customer contact, CRM, marketing campaigns, the offer generation process, everything. Talend gave us that. Talend was able to participate directly in all of our operational processes.”
The bottom line: “Talend is like a refrigerator for Mogo,” said Thomas. “It just runs. It’s our backbone. And it gives us the least stress of any tool that we use as part of our analytics infrastructure.”
Ah, how refreshing! Finally, a case where the impact of data integration is not a difficult ethical dilemma. For Mogo, it’s all good.
We’re looking forward to hearing more stories about companies that are using Talend to bring out the best in people and commerce. Got one?