Pressure has been steadily building for residential mortgage lenders as government regulation and scrutiny over Home Mortgage Disclosure Act (HMDA) reporting has increased. Compliance officers have to jump through hoops to deliver accurate fair lending data, and it has become increasingly evident that many are largely underprepared for the level of accuracy required to meet regulation criteria and maintain good standing within the industry.

‘Wait and see’ is a great strategy for checking the weather before an evening out but not for delaying the inevitable technological shift that will revolutionize an industry.

The overarching consequences of faulty data are well known. Compliance teams must sift through and validate data fields, correcting discrepancies between the source documents and loan origination systems. Fair lending compliance is a crucial task, and compliance officers may feel they are constantly playing catch-up as rules and regulations change every year.
Compliance processes and samples can be fraught with human error from operational workflows, so what’s an institution to do when its goal is to limit overhead costs, reduce manpower and improve profit margins while still meeting regulatory requirements? That’s where machine learning comes in.

Future of compliance

Machine learning is no longer a far-off phenomenon and is steadily being integrated into the corporate and industrial world, including our current banking systems. Automation serves many purposes.
For one, the mechanization of services — whether it be providing clients with drive-thru tellers, answering questions with chatbots, or the use of artificial intelligence in data consolidations to set credit limits and forecast lending losses — reduces the professional staff necessary to run these services. Two, it smoothes out processes so that monotonous tasks can run themselves. Third, it’s more cost-effective in the long term.
Automation, in short, serves as an effective tool to reduce risk, curb inefficiencies and redundancies, and drastically reduce human error. Although the mortgage banking industry is not unfamiliar with automation, there has only recently been a push toward automation in the compliance sector.
Automation helps optimize results by freeing lending staff from the most menial tasks, such as sorting through tedious mortgage data or double-checking fair lending data fields. This allows them to add value to their institution in higher-level ways by forging new relationships or solving complex industry problems.
Amid ever-shrinking budgets and capacity, these are positive changes that will provide an edge when it comes to regulation adherence and data integrity. There are a few ways that the push to integrate a robust data integrity process for risk management and compliance could improve your institution’s outcomes.

Save on labor

It’s a challenge to get the data “perfect enough” to pass HMDA regulatory checks. And when the work to manually review data errors piles up, it does so quickly and massively.
As the stacks of paperwork rise and threaten to topple, a lender may deem it necessary to hire people to sort through data despite shrinking margins — thereby causing labor costs to skyrocket in the process. This happens repeatedly, every time the workload gets to be too much.
Banks end up throwing bodies at the problem every quarter or so (and during a labor shortage, no less). What’s worse, the results could still be flagged by compliance for basic human errors. Many institutions are starting to look into the future and are noticing that automation tools can provide a solution to the undue burden that compliance professionals are shouldering.
Automation services can eliminate manual verification for applications, increase lending capacity, and are easily embedded into existing digital onboarding experiences. To many in the industry, an automation investment is worth it to save much heartache down the road.

Increased efficiency

Have you ever had to do something so many times that your eyes just glaze over? Have you had a task so monotonous that you lose track of time and start daydreaming about more important tasks? Through no fault of its own, the human mind wanders. This is how many errors are made — errors that can be easily removed through automation.
Automation was developed to curb errors that result from the manual work that often plagues compliance teams and results in higher rates of burnout. Mortgage quality control teams must manually review data from the loan origination system before it moves to compliance. In compliance, the data is reviewed again and compared to the source documents for each HMDA-required field. This process is unscalable, so applications stack up and quality control runs behind. The more documents stack up, the more professionals are required, and the pressure mounts as they are compelled to plow through piles of data — a dangerous cycle.
Automated compliance systems will continuously sweep document databases, loan origination systems and HMDA loan application registers to easily pinpoint any issues that arise. This removes the need for staff to dig through endless files for one mistake. These systems reduce hours spent on tedious tasks, which increases productivity for employees and adds value to the institution by limiting human interference. This, in turn, reduces risk and increases data accuracy, ultimately improving both employee performance and retention.
The goal of automating compliance tasks is to make compliance professionals and institutions more efficient. Machine learning can help with many tasks: elimination of manual verifications for applications; automatic extraction of data from verified documents; reduction of false positives for fraud and increased lending capacity; providing a chain of custody; and documentation of audit trails.
These are just a few of the tasks that can smooth out the process. By creating an automation solution for monotonous responsibilities that are often slowed down or jeopardized by human error, these systems ensure that all compliance material always meets HMDA standards.

Lay the groundwork

At the end of the day, what’s most important is providing accurate, expertly extracted data that is compliant with fair lending standards. Automation can not only provide better data but higher efficiency, happier staff and lower overhead costs. Who doesn’t love that?
As regulations become more stringent and goalposts keep moving, mortgage companies must stay ahead of the curve and take steps to ensure data quality. But these institutions are often hesitant, with common questions like, “Should we wait and see?” or “Should we hold off on investing in something that we don’t see a lot of people utilizing just yet?”
The short answer is no. “Wait and see” is a great strategy for checking the weather before an evening out but not for delaying the inevitable technological shift that will revolutionize an industry. This monumental shift won’t happen overnight, so laying the groundwork as soon as possible is crucial.
Compliance officers should heed the signs of change and prepare for the highly regulated environment that’s just over the horizon. The future is approaching whether you like it or not, and the time for change is now. ●

Author

  • Tyler Barron is the chief revenue officer at Encapture, an intelligent automation platform providing banks with documentation efficiency. Using machine learning and AI technology, Encapture helps banks reduce compliance risks associated with fair lending guidelines, reduce overhead costs and improve profitability in a volatile market. 

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Nate Clear | 36

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PRMG

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Kyle Johnson | 32

CrossCountry Mortgage

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Chania Ford | 28

Groundfloor Lending

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Alec Finn | 33

American Heritage Lending

Illinois

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Daniel Halvorsen | 36

LoanPeople

Florida

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Travis Harris | 36

Southern Trust Mortgage

Virginia

13 years in business

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Connor Donovan | 26

Park Place Finance

Texas

4 years in business

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Thomas Evans | 31

Acadia Lending Group

Maine

8 years in business

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Justin Margolis | 35

PRMG

Florida

13 years in business

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Daniel Lemeshev | 29

CrossCountry

Mortgage

New Jersey

3 years in business

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Jessica Davolio | 35

Leader Bank

Massachusetts

6 years in business

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