In 2012, two Dads met at a preschool Halloween party. We struck up small talk and found a mutual interest in using technology to optimize business operations. The preschool party eventually led to a coffee shop meet. That meeting turned into a lot more meetings, and in 2016, ProPair was born.
Getting Off the Ground: Optimizing People’s Strengths with Machine Learning
My co-founder, Ethan Ewing, is a mortgage industry veteran. I am a data scientist with a passion for building products that help organizations get the most out of their data. We knew together we could create a unique approach that would use machine learning to drive further efficiencies in the consumer lending industry. We believed these efficiencies would improve lead management processes and ultimately deliver higher lead conversion rates across organizations.
In an industry where it was common for only 2% of leads to close, we felt the application of machine learning would likely have a measurable impact on conversion. We started looking at preferences, traits, and patterns of individual loan officers to build a recommendation engine to support our vision to match loan officers more effectively to best fit prospects at optimal times. This was the basis for the ProPair MATCH product. By adding machine learning into what was previously a random or gut-instinct process, we were able to help teams drive efficiency into their lead management and conversion processes.
An Evolving Vision: How ProPair Has Changed Over Time
As is often the case with young companies, the vision for ProPair has changed quite a bit in the years since we started the company. Through incorporating meaningful feedback from our customers, what started as a single feature to improve the lead/loan officer matching process has evolved into a product platform.
We began with what we believed the market needed, but the true platform evolution occurred by partnering with our early adopters and iterating through products and services to solve real-world problems that they were sharing with us. The original plan was about optimizing the efficiency of the lead assignment process. However, once we started talking to more industry players, we adapted and built on the original concept to make a larger impact on many areas of the lead conversion process. The current platform includes prioritization, ranking, nurturing, and custom insight enhancements.
Looking Ahead: What Consumer Direct Lenders Should Know About Machine Learning
The most important piece of information for lenders to understand is that machine learning does not need to be a replacement for your existing processes. It can act as a replacement, but it generally works best as an extension of your existing processes. Machine learning uses mathematics to show you what aspects are working well in your existing processes and what aspects could be improved. Your historical data has many stories to tell you and surfacing that information through machine learning applications will improve your processes over time. Machine learning supplements your domain expertise to amplify your conversions in an automated, repeatable, and robust way. And it does so without the biases that exist within human decision making.
There’s a lot of content out there about machine learning that can be misleading. Lenders should know that simple machine learning products can help them quickly solve fundamental issues weighing down their business. ProPair’s goal is to help educate these companies about how machine learning can act as a supplement to their domain expertise and enable them to better compete in the market. This is true regardless of the size of the mortgage company.
At the end of the day, we want our customers to sleep better at night because they have an efficient process that is being executed and monitored in an automated and systematic way. Relying on a solution driven by machine learning will give you that comfort along with measurable improvements to your business processes. Our clients are experiencing these benefits firsthand. We look forward to sharing these insights with more mortgage lenders and continuing to innovate in the industry over time.
To learn more about our machine learning technology or how we can support your organization, reach out to us via email at email@example.com.