Tyler Barron, Author at Scotsman Guide

Solving the Compliance Enigma

Tyler Barron — Thu, 01 Feb 2024 12:08:00 +0000

Commercial mortgage lenders know the importance of accurate information for federal reporting of compliance data. But the emphasis on detailed reporting of financial transactions may soon be expanded and become more rigorous for small-business lenders if the applications of new oversight rules connected to the Dodd-Frank Act are implemented.

“Today, small-business lenders are potentially facing increased costs for expanded data requirements.”

Since the late 1970s, banks and other lenders have been reporting key pieces of information regarding lending practices to regulatory authorities under requirements of the Community Reinvestment Act (CRA) and Home Mortgage Disclosure Act (HMDA). The goals of these programs are to increase transparency in lending and to ensure that banks are meeting the needs of the communities in which they are located.

Today, small-business lenders are potentially facing increased costs for expanded data requirements. The Consumer Financial Protection Bureau (CFPB) has issued a proposed rule for Section 1071 of the Dodd-Frank Act that, when finalized, would require financial institutions to collect and report more information about small-business credit applications.

The draft of the regulation released last year states that the new rules are intended to provide a comprehensive view of small-business lending, and to make sure that banks and nonbanks are serving small businesses fairly. The new rules also call for reporting on minority-owned, women-owned and LGBTQ-owned businesses.

The prospective rules to Section 1071 face various legal challenges, some of which argue that the proposal is too burdensome and expensive. At the same time, there is a congressional push to block the CFPB’s proposal, with the House and Senate recently passing a joint resolution to overturn the new Section 1071 rules. President Joe Biden reportedly intends to veto the legislation.

Automation efficiencies

Whatever the final rule requirements end up being, it appears that more scrutiny of small-business lending data is on the way. This has resulted in many bank and nonbank lenders turning to data validation automation as an alternative to scaling up compliance and quality control teams.

Recent legal challenges may have put the timing of the final ruling in flux, but preparation is still crucial for financial institutions. They must address increased regulatory requirements in a challenging macroeconomic environment that also demands finding creative ways to cut costs and become more operationally efficient.

Confidence in data accuracy is key for the preparation to comply with Section 1071. Bank and nonbank lenders should assess their current workflows, identify any gaps — including their ability to collect data — and identify any limitations in their current business systems. It is vital to understand the capacity, constraints and requirements for 1071 reporting while also understanding the organization’s banking systems and how data is currently collected and stored.

A common challenge for mortgage lending workflows is having an efficient way to request and organize borrower documents into a loan origination system (LOS). Automation can ease the inefficiencies tied to document organization by automating the classification step. This will help ensure that documents are in the right place and allows the system to automatically place documents in folders, repositories or loan origination systems. Many times, documents are received and combined into one file, such as a large PDF format, that must be broken down into individual sections and filed into their correct digital folders.

Furthermore, loan processes often require manual “stare and compare” of borrower documents. In other words, mortgage professionals are forced to look at documents side by side and visually discern the differences. This method leads to mistake-prone loan documents, frustrated borrowers and lengthy processing times.

Decreasing manual steps

Automation drastically decreases the time spent on manual labeling, sorting, stacking and reviewing of loan packages, and it eliminates manual data entry. It provides a lift for the underwriting team by automatically extracting key information from small-business financial documents, including tax returns, and allows for faster credit decisions.

Automated loan processing and onboarding, in addition to the collection and validation of data, simplifies downstream audits such as preclosing and post-closing checks. It will also help with compliance audits from HMDA, CRA and the expected regulations in Section 1071 of the Dodd-Frank Act.

Machine learning can automatically extract key data from loan packets, check for missing information or signatures, and compare it to the system of record. It can also make sure the data is congruent across both the systems and final loan package.

The automation process can take these audits even further by triangulating data points across multiple sources. For example, in the case of a compliance audit, data validation processes will be expanded to look at the documents, the LOS, a document repository and, ultimately, a compliance report such as the CRA loan application register or a future Section 1071 loan application register. The method ensures higher-quality reporting, storage of documents and accurate data across multiple systems.

The typical time and cost savings from automated commercial mortgage lending improves margins by cutting expenses on a per-loan basis. As time spent on tasks decreases dramatically, so can the cost per loan. This will allow financial institutions to position themselves to be fully prepared for audits, changes in the market and expansion opportunities. It will also speed up the adoption of changes in regulatory requirements by creating a completely scalable compliance review and reporting process.

Managing labor costs

To satisfy upcoming CRA modernization and Section 1071 requirements, commercial mortgage lenders are faced with the option of greatly increasing the size of their teams (and adding the associated costs) or investing in automation for a fraction of the cost. Not only can automation easily find, consolidate and track reported data points under the expected requirements to comply with Section 1071, but it also allows lenders to retain key compliance employees while attracting new and experienced compliance professionals.

Compliance professionals carry the heavy burden to report accurate data, which can lead to mountains of manual data reviews. Such work can create a vicious cycle of burnout and rising costs. There is a significant amount of change management required for institutions to train commercial mortgage originators, underwriters and others to ensure all data points are collected at application.

The use of automation drastically reduces human errors, providing data integrity and confidence in meeting regulatory requirements. Consequently, compliance professionals can focus on higher-value tasks and lenders can avoid investing in additional compliance personnel in a challenging labor market. Efficiencies created by automation bring cost savings across the commercial mortgage lending process, supporting loan growth without the need to hire additional employees.

Avoiding risk

The legal fight involving Section 1071 will most likely be decided by the U.S. Supreme Court. However the case ends, there still exists a ticking clock for commercial mortgage lenders to prepare their data for the level of accuracy required to meet government regulatory criteria. If the data is not properly managed, prepared and presented, it could adversely affect lenders through reputational risk and large fines.

Risk mitigation is undoubtedly the most important aspect of increased compliance regulations. Future-proofing with automation allows for a full loan review instead of having to use a risk-based approach of sampling. Automation reduces false positives by limiting human interference, so humans only look at exceptions instead of all documents, further decreasing risk for the institution.

The automation of compliance with CRA and Section 1071 regulations ensures high rates of accuracy. Consequently, financial and reputational risks are mitigated by ensuring that fair lending analyses are conducted with accurate and timely data.

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As lenders cautiously prepare for future regulations, a solid foundation of automation will provide them with the confidence needed to emerge from the new regulatory requirements with more efficient methods of operation. Financial institutions owe it to their customers and employees to be ready for the changing regulatory environment. Those that adapt with new ways of solving challenges will emerge with a competitive advantage in the world of small-business lending. ●

The post Solving the Compliance Enigma appeared first on Scotsman Guide.

Automate Your Compliance Tasks

Tyler Barron — Sun, 01 Jan 2023 09:00:00 +0000

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. ●

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