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. ●
