Compliance Article
11/06/2007
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The decline in mortgage origination volume in recent years has increased focus on loan profitability in addition to meeting traditional regulatory compliance objectives. Lenders face stricter due diligence policies and must ensure each loan meets the investor’s criteria prior to closing. Missed regulatory errors will compromise profitability as the cost to correct compliance problems like high cost loans, Truth in Lending errors and RESPA violations increase if caught later in the lending process. Adding to these challenges, states continue to pass more restrictive legislation. Constant changes in legislation require ongoing monitoring, often resulting in revisions to policies and controls. Sales and underwriting staff must receive these revisions in a timely and understandable manner. Besides maintaining a fully trained staff, lenders must also manage risks within their lending networks when empowering correspondents and brokers to lend in the institution’s name.
To manage continuous legislative changes, stricter investor requirements, and growing lending networks, many lenders are using automation. This practice assures every loan is consistently reviewed according to their lending guidelines. Service oriented architectures (SOAs) enable lenders to automate compliance rules in support of workflow invoking tests at multiple points during the loan lifecycle. This implementation applies the same standards and lending policies to the entire portfolio, reducing errors in interpretation and training. In correspondent lending channels where a lender’s risk extends to include a network of brokers and lenders, compliance automation guarantees the proper application of state usury and fee limits to every loan for the lender’s license type. Receiving this real-time informs the lender if limits have been exceeded and a correction made before underwriting or closing. In addition to reducing risk, proactive compliance enables lenders to optimize portfolio value. Pre-closing tests – like a pricing fair lending review comparing a predicted range for interest rate, APR, yield spread premium and points and fees against other similarly situated applicants – automatically highlight inconsistencies among loan originators and brokers. The fair lending analysis not only validates the pricing of the loan but also assures fair treatment of the borrower. This analysis also identifies potential fair lending problems that might not otherwise be recognized until after the loan has already been made. Beyond data accuracy and consistency, automation contributes to overall loan profitability when used to identify loans that qualify for a premium on the secondary market. Custom rule configuration enables lenders to define criteria to identify loans that qualify for a premium based on certain characteristics like CRA or HUD credits. Identification of these loans across the entire portfolio enables lenders to proactively identify premium loans and route them to the appropriate investor.
