Since the early stages of building MortgageCS, we have been interacting with financial advisors to validate the platform features. Throughout this process, the platform’s ability to harness real-time mortgage data has earned and maintained a top value position. In fact, this component addresses one of the “aha” moments we learned of back in early 2015. Here is how we learned of the mortgage confidence problem – and what we did to solve it.
Uncovering the Confidence Problem
In early 2015, we conducted an anonymous survey focused on understanding buying behaviors surrounding mortgages. We asked respondents to rank the factors they consider important in a mortgage offer. Perhaps not surprisingly, interest rate took the top spot, followed by bank or lender fees in the second position. The next three positions were inconsistent but included proximity to institution, reputation of institution and personal relationships.
We then asked respondents to rate their level of confidence in obtaining the best loan terms for their given situation. The scale included a 5-point range from Very Confident to Not Confident At All. Shockingly, only 9% of respondents revealed they were Very Confident. When combined with Confident, the number grew to just 21%.
According to this data, only 1 in 5 recent mortgage shoppers were Confident they obtained the best loan terms – despite it being the top priority when ranked against other factors.
How could this be? One possible explanation can be found by looking at the existing mortgage landscape. A fragmented market, with lots of advertising dollars and a perception of a complicated transaction could take some blame. Perhaps consumers are settling early and avoiding “pain” (a human tendency) – rather than continuing on what can be perceived as a long and complicated journey. Or, perhaps there is just no way for consumers to know, given the current tools available to the market.
Solving the Confidence Problem
We looked at what makes people feel confident when shopping. When it comes to many large buying decisions, using prices that other people paid can be a good judge of deal quality. Anyone that has purchased a car recently, likely reviewed what others have been paying. Based on that, they either approach the car buying process with confidence or, if after the fact, may realize they overpaid. Regardless, the fact remains that access to information can create confidence in approaching a buying situation.
So, we applied this to mortgage shopping when building the MortgageCS platform. Market Insights will collect proprietary data, harnessed within the platform, to inform consumers of “what others paid” for a mortgage that matches the key terms of their loan. This is part of our magic sauce and routinely generates a “Whoa!” reaction from financial advisors during a demo presentation.
So, will the Market Insights component solve the problem of “lack of confidence in mortgage offers”? Based on initial reactions from professionals who have witnessed Market Insights in action, it certainly will.