IT'S TIME FOR BUSINESS INTELLIGENCE (BI) to take back what the 2016 regulations took away. As every lender poured money into implementing new systems and procedures, the bottom line felt the pinch. Now that mortgage manufacturing lines are running full-steam with higher loan volume thanks to lower interest rates, there is opportunity to collect a lot of valuable data. What you do with that data at this point in the business cycle will not only set the course for profitability but for quality as well.
Core mortgage metrics
Leveraging performance indicators to improve the bottom line by comparing key milestones and sales versus costs from application through closing is nothing new. Most lenders have established the discipline to measure key pull-through points, velocity, the number of employees per loan closed and the cost to close a loan even by job role.
Tools are available to dig deep into market share and customer profiles. Within the market-share metrics are layers of sophisticated metrics for social media to measure what's working and what's not. The ability to factually state, on any given day, the time it takes a loan to move through each step in the mortgage life cycle, and other metrics, has become a status symbol. You know what is going on and where it needs to go.
Quality in the mix
In all of this data should be indicators of where loan quality is headed. A focus on only increasing the velocity of a loan closing can often mean the team is rushing--and with rushing comes mistakes.
When volume is good and loans are closing on time, the revenue can hide a lot of problems. It becomes easier, for example, to keep paying hundreds of dollars per transaction for costs to cure on Closing Disclosure (CD) tolerance errors in order to save a day in the closing cycle. The assembly line has a quality problem, but the team has found a way to work around it, for the sake of the metrics, with a little help from the bank account.
Historically the good times leave behind a trail of cleanup and compliance risk. If you need proof, just look at the Great Recession. This also happens in simple seasonal volume swings. The key is to identify the predictive indicators of a quality problem.
Lagging or leading
Business intelligence for regulatory compliance is generally still working with performance measurements that are lagging indicators. Post-closing quality-control (PCQC) reports are good examples of lagging indicators. PCQC results reveal defect rates...