The Value of User Experience When Managing Risk

Much has been written about the rise of machine learning and artificial intelligence and how it will impact the auto lending industry. While there has been a significant amount of hype, the promise of artificial intelligence is simply game changing.

The most obvious application is that thinking machines will be able to assess risk and provide an accurate estimate of whether certain borrowers will repay their loans. The ramifications of this change will be massive. If auto lenders are better able to understand whether a particular borrower is not able to pay back the entirety of his or her auto loan, lenders can mitigate their risk while offering better pricing and more approvals to new loan applicants.

All of this is well and good. The technology is getting more sophisticated, meaning that auto lenders will be able to make even better predictions on whether borrowers will pay back their principal in full. But having said that, developing more accurate predictions isn’t the only component of making this technology appealing to auto lenders.

Essentially, when we are leaving out half the equation. The other half of the equation is easy and beautiful user experiences.

New software can be intimidating, especially for users who do not think they are “tech-savvy.” Even if an application or new piece of software promises to make a user’s life simpler or easier, the software will fail if the user does not deem it easy to use. Users will forego an improvement (even a significant one) in their day-to-day tasks if the switching costs are too high.

It is easy to look at several industries that face this problem. The legal industry, for example, is inundated with startups promising new technology. But having said this, lawyers and legal professionals often hesitate to adopt such technology because they have already built long-lasting habits and are intimidated by software that seems confusing or difficult to use.

Ultimately, there is power in the simple and the beautiful. It is difficult to get this correct. But once it does happen, users are more likely to use and enjoy the product.

We face a similar problem in the auto lending space. A lending professional at an auto dealership, for example, has built-in habits that have served him and her throughout their career. While those habits may not be the most efficient, the system works well for them and their team.

So when they are approached by a hot new startup promising to use machine learning and artificial intelligence to minimize their loan risk, these professionals seem interested, yet skeptical. Once the software gets into their hands, their skepticism is often validated, as the software (while powerful) is difficult to navigate. Further, the data is displayed in a stale form. Users often aren’t able to filter through the data and visually see where some of their riskiest loans are coming from.

In sum, no one is making these lenders’ jobs easier for them. Something needs to be done to help auto lenders leverage the power of machine learning in a beautiful, easy-to-use format.

One startup that is attempting to solve this problem is Aclaro. Aclaró is leveraging the power of machine learning and artificial intelligence to help auto lenders manage their risk. While there are other startups that are attempting to solve the same problem, Aclaró prides itself on its beautiful user interface. At this time, Aclaró is offering a free dashboard preview of its risk assessment dashboard. If you are interested in experiencing Alcaro’s simple, beautiful platform, we invite you to visit the Aclaró website.

Developments in artificial intelligence and machine learning are absolutely promising. It is going to make auto lenders’ jobs much easier and will increase lenders’ bottom lines. That said, the machine learning algorithms themselves are only half the equation. Tech companies and startups working on this problem cannot ignore the user experience. By emphasizing simplicity, beauty, and ease-of-use, auto lenders will be happier (and better) at their jobs.

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