What you may not realize is that I just stated the obvious based on the results of lender HMDA data.
Your examiner shows that you have 3 similarly situated borrowers which resulted in an interest differential that they believe are discriminatory in nature. A White Male received a rate of 3%, A Black Male received 3.5% and a Latino Woman received 4%. They all fall within the same product category, have the same risk adjustments, are in the same MSA and locked on the same day. Therefore, it appears that your company is charging higher interest rates to minority clients. As a result of this, the examiner decides to expand the scope of their investigation. This situation happens all the time with mortgage lenders and your secondary pricing desk knows why! Wait! What did she say
Yes, your pricing department knows this and isn’t worried about it because they understand pricing and how it works. Examiners on the other hand do not generally possess that degree of knowledge and the job of the compliance person is to bridge that gap. Yet if the compliance person in the company doesn’t know why this happens just about every day, they will be ill-equipped to deal with it.
So let’s explore this phenomenon. One Borrower, on one day, at the same time of day can have an interest rate differential of 1%. That’s right a 1% difference in interest rate. Why? Borrower decisions and what I call unknown variables.
Properly defending your company against Fair Lending and Pricing Disparity claims requires a strong compliance management system over both the borrower decisions (unknown variables) and the adjustments, time price differential and closest to Par pricing adjustments (known variables). All of this data on each file needs to be documented, organized, reviewed and instantly recalled.
Lenders lose this battle because they are busy documenting the HMDA data, looking at loans after they close, or inferior information to the superior information gathered by their regulator. As a result they look a little silly to the examiner when they need to pull 500 files, put 2-3 staff people on it for 2 months and try to figure out why one client received one rate and one client received another. Then they create a spreadsheet to try to explain what is not documented. Doesn’t seem like a great plan, does it.
So let me demonstrate what your pricing desk knows that you may not be documenting.
- The White Male is buying his 5th home, is 53 and has no intention of moving anytime some. With rates as low as they are, and retirement around the corner, he wanted to buy-down his rate.
- The Black Male is 25 and buying his first home. He has done really well in saving for a down payment, but needs a little help with closing costs. He is not as worried about the rate because they are so low, so chooses a lender credit to offset those closing costs.
- The Latino Woman doesn’t have a huge down payment and believes that Lender Paid Mortgage Insurance makes more financial sense to her so she chooses that option.
Did the lender discriminate? I would submit that they didn’t. However, if you can’t document the known variables (all items that may result in a price/rate) and all unknown variables (decisions made), you are leaving a gaping hole in your company risk profile that will cause you unnecessary fines, consultants and attorneys, and valuable staff time that could be better spent on bringing in loans!
What are you doing to clean this up before the loan closes?