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Best Practices-Fair Lending Workflow-Data Integrity!

The number one issue with the CFPB and lenders is Data Integrity.  Many lenders have had to go back to their HMDA data, scrub it and resubmit it.  Now that is a lot of work that you do not want!  Not to mention it starts you out on the wrong foot with the examiners. So to prep for this part of your workflow I am going to start with data systems and data flow.

Step One:

List all of the technology that is used by your company for origination purposes.  As an example, your LOS system, your pricing engine, quality management tools, etc.  If you do not know what they are, then it will be tough to build policy around your data flow.

Step Two:

What system does your HMDA data populate from?  This will be your first and highest priority to get correct since this is where the examiners start.  Do you know how to pull your HMDA data from this system?  Does compliance have access to this information to run periodic checks?

Step Three:

What positions are tasked with data input?  What is each positions area of responsibility for the data?  Please note that this should be should be highly defined in your policies and procedures as to who is responsible for what.

Step Four:

How is this data monitored for completeness by the responsible party?  Is it the employee responsibility with management oversight?  Does the manager pull a report each day or week and look for data that seems way out of line?  The attorneys who are doing mock audits are shocked by what they see.  DTIs of 212%, LTV or 368%, and income of $0 are just some examples.  Are there any incentives for correct information or disincentives for incorrect information?

Step Five:

Who is responsible for doing the final data audit before the loan closes?  What system is considered to be the “bible” of your data?  If you pull HMDA data from an LOS then the LOS should be spot on.  If not, someone is not doing their job and someone is not monitoring that they did their job.  Four eyes are better than two.  It is tough to proof your own work!

Step Six:

Track and evaluate data fails by employee and as a whole.  If you see patterns repeating, then it is quite possible you have policy, training gaps or someone who doesn’t want to perform to expectations.

Getting your data right does take a village.  Yet if accuracy is not demanded of the responsible party and monitored, then you will have little chance of getting it right!

Next Up-The final piece to this series-Client Interaction & Client Parity.

Tammy Butler, Master CMB

Author Tammy Butler, Master CMB

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