UNITED WHOLESALE MORTGAGE
“ There has been a cultural shift that ' s happened in Michigan ,” Bressler explains . “ I grew up here . Everybody in Michigan was very blue collar , because it ' s all about automotive . You put your head down , you go to work , and that ' s it . We ' ve really started to shift . We ' re still very blue collar , but we ' ve really started to shift into this white-collar , heady , highly technical and highly educated mix . That ' s been fantastic to watch .”
The challenge posed by fraud increases as you scale At the heart of UWM ’ s rise to the top is an obsessive focus on understanding and meeting customers ’ needs . Sometimes , that is even separate from revenue or sales . “ We started building large scale fintech products for the broker community and their customers , obviously specific to the mortgage industry ,” Bressler says . “ We gave them away for free to all of the brokers and we said you didn ' t even have to use us .”
The reason , he explains , is all about providing brokers and borrowers with the tools they need to find the right product . When you ’ re operating in the wholesale space , brokers can shop up to 20 or 30 different lenders at a time – so there ’ s no guarantee that brokers will use UWM in spite of making these convenient tools available , but nine times out of 10 they do .
“ It has built up a ridiculous amount of loyalty from our clients ,” he continues . “ They truly feel like we have their best interest at heart , so that loyalty carries over when rates are high and when rates are low .”
As UWM has scaled , the risk posed by fraud has increased . Lenders are in the business of risk , so mitigating that risk is an important factor in improving your bottom line .
Bressler says : “ We ' ve invested very highly in data science and business analytics . We use a lot of our modelling and our data to predict behaviours . The biggest risk to a mortgage company typically is fraud from a consumer or from a loan officer . We have so many technology guardrails around everything that we do here , and then using that on top of our data scientists , we ' ve been able to model and predict where we would see fraud and how we would detect it ahead of time . From the front end all the way down to the back end , we ' re constantly analysing the data and serving that up to our teams to make sure that we ' re protected .”
To give an indication of UWM ’ s capabilities in fraud detection and prevention , the company ’ s information