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Showing posts with label Disclosures. Show all posts
Showing posts with label Disclosures. Show all posts

Wednesday, March 25, 2026

Will AI Reduce Fair Lending Violations?

YOUR COMPLIANCE QUESTION 

Our company is building an AI engine to monitor for fair lending violations. The AI system is extensive and includes chatbots. It will be integrated into our LOS and several other systems. We are a large mortgage originator and servicer. We use one of the most well-known platforms for loan originating and servicing. The system offers several new AI features. But we ran our own test against the LOS and found that our AI engine is identifying more fair lending issues than the one embedded in the LOS. 

As the company's General Counsel and Chief Risk Officer, I was shocked that building our own AI system could produce better results than a highly rated, well-established LOS. Granted, our AI system is proprietary and reflects our unique compliance needs. Full disclosure: We have been a client of yours for over 15 years, and we have discussed these and other AI findings with your team in order to mitigate compliance risk. 

I wonder if a one-size-fits-all AI integration in the LOS can really be effective, given that fair lending involves many state and federal regulations. We are testing and monitoring our AI integration, but many companies lack the resources we have and will rely on their LOS provider's results. 

Do you think a generic AI system can reduce fair lending violations? 

Signed, 

Risk Averse 

OUR COMPLIANCE SOLUTION 

AI POLICY PROGRAM FOR MORTGAGE BANKING™ 

Our AI Policy Program aligns with Freddie Mac's AI governance requirements for Freddie Mac Sellers/Servicers. Responsible AI practices can help align AI system design, development, and use with applicable legal and regulatory guidelines. 

Our AI Policy Program consists of the following policies: 

1.      Artificial Intelligence Governance Policy

2.      Artificial Intelligence Use Policy

3.      Artificial Intelligence Workplace Policy

4.      Artificial Intelligence Credit Underwriting Policy

5.      Artificial Intelligence Do & Do Not Policy

6.      Artificial Intelligence Ethics Policy

7.      Artificial Intelligence Vendor Management Policy 

Contact us for the presentation and pricing.  

RESPONSE TO YOUR QUESTION 

Let me begin with my conclusion: there is currently no one-size-fits-all, generic AI system that can be thoroughly relied on to reduce fair lending violations. 

Most companies will rely on originating and servicing platforms that integrate AI into fair lending analytics. Unfortunately, companies are generally liable for AI errors, particularly when AI causes financial losses, safety issues, or provides consumers with false information. Legal responsibility typically falls on the business deploying the technology, even if it properly monitors, tests, or ensures that the AI is fit for fair lending detection. 

Legal and Regulatory Risk 

Put another way, your business is responsible for any misinformation provided by your AI chatbots. As you likely know, there are certain aspects of tort law, like duty of care, that require individuals and entities to act with reasonable care to avoid causing foreseeable harm to others. It forms the basis of negligence claims; if this duty is breached and causes injury, the responsible party may be held liable. 

I have repeatedly said that companies must ensure AI systems are properly trained and monitored to avoid liability for errors caused by biased AI. Although developers may be liable for inherent defects, the business deploying the AI is often responsible for how the system is used. 

If you are going to use AI to detect fair lending, you must be able to identify disparate impact patterns across demographic groups, monitor for "redlining" analogs in digital lending, flag outlier decisions that deviate from modeled norms, and generate audit trails for regulatory review. 

AI is rapidly transforming the mortgage industry, promising increased efficiency, faster decision-making, and improved risk assessment. Still, its integration poses significant challenges related to fair lending compliance, data bias, and transparency. While AI can expand credit access by utilizing alternative data, it risks perpetuating historical biases if models are trained on biased data or utilize "black box" algorithms that make decisions hard to explain.

Thursday, March 19, 2026

Will AI Replace Me?

YOUR COMPLIANCE QUESTION 

I have been a loan officer for fifteen years. I am a single mother of two wonderful teenagers. I have also been the breadwinner for 15 years since my husband passed away. I keep reading how AI is going to replace me. 

In the last few weeks, I've read a few articles about how AI is transforming the mortgage world. Part of that transformation looks like I am going to lose my job and be replaced by a computer program. This is so unfair. I have spent all these years building my professional life, and now I feel it is all going to be trashed. 

I heard you speak at a conference recently. You spoke about your new AI Policy Program and answered many audience questions. One of them was about how loan officers, processors, and underwriters are worried about being replaced by AI. I would like you to share your remarks in your newsletter. 

Will AI replace loan officers like me? 

Signed, 

A Human Being 

OUR COMPLIANCE SOLUTION 

AI POLICY PROGRAM FOR MORTGAGE BANKING™ 

Our AI Policy Program aligns with Freddie Mac's AI governance requirements for Freddie Mac Sellers/Servicers. Responsible AI practices can help align AI system design, development, and use with applicable legal and regulatory guidelines.

Our AI Policy Program consists of the following policies: 

1.      Artificial Intelligence Governance Policy

2.      Artificial Intelligence Use Policy

3.      Artificial Intelligence Workplace Policy

4.      Artificial Intelligence Credit Underwriting Policy

5.      Artificial Intelligence Do & Do Not Policy

6.      Artificial Intelligence Ethics Policy

7.      Artificial Intelligence Vendor Management Policy 

Contact us for the presentation and pricing.  

RESPONSE TO YOUR QUESTION 

REVOLUTION AND EVOLUTION 

There have been many technological revolutions in human history. We are now at the advent of another revolution: the onset of artificial intelligence (AI) technology, a massive, incremental, worldwide expansion of knowledge in computer science dedicated to creating systems capable of performing complex tasks that typically require human intelligence. Each revolution has brought about profound changes in civilizations. Surges in technological development have characterized each revolution. 

From stone-age tools to learning to control fire, from foraging for food to the first agricultural revolution, from replacing bronze with iron, each stage of technical knowledge enabled widespread human development at the cost of some trade-off in the human social experience that had evolved heretofore. The printing press brought about mass production of books, democratizing knowledge and literacy; the scientific revolution shifted knowledge from philosophy to evidence-based insights; new farming techniques led to increased food output, population growth, and urbanization. 

And, of course, we all know of the industrial revolution, where machine-based manufacturing shifted society away from manual labor; this was then followed by the technical revolution, where mass production became deeply entrenched in lived experience, such as the creation of assembly lines, steel-making methodologies, and the application of electricity, internal combustion, and telecommunications. Over the last 100 years, the green revolution has introduced high-yielding crops, industrial fertilizers, and new agricultural technologies, thereby increasing global food production. 

Which Revolution Are We In Now? 

So, where are we now in the scheme of things? 

In my view, we are currently living in the information and digital revolution, but rapidly transitioning to the artificial intelligence revolution. We are living at a time when computers and transistors, the Internet, personal computing, and smartphones are being rapidly replaced by the artificial intelligence revolution, characterized by discoveries such as gene editing, advanced robotics, and nanotechnology.

Wednesday, February 4, 2026

Freddie Mac Deadline: March 3, 2026 – AI Governance Framework

YOUR COMPLIANCE QUESTION 

We are using your AI Policy Program. Upon receipt, we had it reviewed by our AI committee to determine whether it complies with Freddie's requirements for establishing a comprehensive AI governance framework for AI and Machine Learning. 

I am pleased to report that your AI Policy Program received the committee's approval. It met our checklist based on Freddie's requirements. 

As a Freddie Mac Seller/Servicer, we want to know what the effect would be on us if we had relationship partners that are not in compliance with the AI governance framework.   

What restrictions will Freddie Mac impose on us if our relationship partners do not comply with their AI requirements as of March 3, 2026? 

Signed,

An Anxious Compliance Manager 

OUR COMPLIANCE SOLUTION 

AI POLICY PROGRAM FOR MORTGAGE BANKING™ 

Our AI Policy Program aligns with Freddie Mac's AI governance requirements for the Freddie Mac Seller/Servicer (or "Lender"). Our well-constructed AI Policy Program is a proactive means designed to avoid and mitigate risks associated with Artificial Intelligence and Machine Learning. Responsible AI practices can help align AI system design, development, and use with applicable legal and regulatory guidelines. 

Our AI Policy Program consists of the following policies: 

1.      Artificial Intelligence Governance Policy

2.      Artificial Intelligence Use Policy

3.      Artificial Intelligence Workplace Policy

4.      Artificial Intelligence Credit Underwriting Policy

5.      Artificial Intelligence Do & Do Not Policy

6.      Artificial Intelligence Ethics Policy

7.      Artificial Intelligence Vendor Management Policy 

Discount offer available until March 3, 2026! 

Contact us for the presentation and pricing. 

OUR RESPONSE TO YOUR QUESTION 

Thank you for using our AI Policy Program. Since its release on October 30, 2025, it has been in considerable demand. 

Our AI Policy Program for Mortgage Banking™, which meets Freddie Mac's AI Governance Framework ("AI Framework"), is the first to provide a set of AI policies dedicated to mortgage banking. 

We had been tracking the GSE formulation of AI requirements for several months. 

On March 11, 2025, Freddie released a formal AI/ML governance framework in its Seller/Servicer Guide ("Guide"), introducing a comprehensive AI Framework for Sellers and Servicers that requires formal policies for the use of artificial intelligence ("AI") and machine learning ("ML"). This update mandated that any AI/ML used in the origination or servicing of Freddie Mac-eligible loans be governed by strict policies. 

On December 3, 2025, Bulletin 2025-16 was issued, clarifying timelines and expectations and stating that AI is no longer optional. In effect, Freddie asserted that implementation is a mission-critical, governed enterprise function. 

The compliance effective date is March 3, 2026. 

After considerable review, research, and drafting, we issued our AI Policy Program on October 30, 2025, thirty-four days before Freddie issued Bulletin 2025-16 on December 3, 2025, and Bulletin 2025-17 issued on December 10, 2025. 

On December 10, 2025, Freddie issued Bulletin 2025-17, which introduced revisions to AI Tools relating to servicing, information security, and Seller/Servicer insurance, with most changes effective on March 3, 2026. 

In the context of the AI Framework, "AI Tools" are any artificial intelligence or machine learning tools used in the loan lifecycle. 

BULLETINS 

Bulletin 2025-16 solidifies the compliance effective date of March 3, 2026, requires Lenders to have a comprehensive governance framework for AI/ML Tools used in loan origination or servicing, and, effective January 1, 2026, Lenders must ensure executive oversight, document AI use cases, ensure fairness, mitigate bias, and manage vendor risk.

Thursday, January 22, 2026

Explaining Interest Rates to Borrowers

QUESTION 

I am a new loan officer working for a mortgage broker. I graduated from college two years ago, and I still live with my parents because I can't find a decent job. A friend became a loan officer and said I should do it too. So, I got involved as a side hustle. I've been doing this for nine months. 

At this point, I have made loans for a few family members and a good friend, and I have 6 loans in the pipeline from real estate offices. My borrowers always talk about the rates. It's probably their number one question. They then ask me to explain how rates are determined. No matter how I explain it to them, they get confused, and I don't blame them. The rate is always changing and seems unpredictable. 

How should I explain interest rates to my borrowers?

Thank you! 

A Newbie Loan Officer 

OUR COMPLIANCE SOLUTION

We recommend:

LENDERS COMPLIANCE GROUP, established in 2006. It is the first and only full-service, mortgage risk management firm in the United States. It specializes in residential mortgage compliance and provides the largest suite of compliance solutions for banks, non-banks, credit unions, independent mortgage professionals, and mortgage servicers. 

BROKERS COMPLIANCE GROUP, the first full-service, mortgage risk management firm in the United States. It specializes in outsourced mortgage compliance and offers a full suite of services to mortgage brokers and mini-correspondents. 

OUR ANSWER 

For my response, I am going to assume that your loan applicant is not particularly interested in the secondary and capital markets, the factors that determine mortgage rates, or the securitization factors that affect them. 

That said, I am going to assume that you want a straightforward explanation that you can provide to your loan applicants. I hope to offer a non-technical view that they will understand while you are sitting with them to take the loan application. 

As a new loan officer, please note that when the applicant is sitting down to take the application (or interacting with you online), the point of sale is often a make-or-break moment. 

The point of sale is the most important part of loan sales because it is the primary point where trust is established between the loan officer and the applicants. If you can't explain how mortgage rates are determined, you can lose their trust in your expertise, a factor that could determine if they go with you or somebody else. 

Components that Determine Mortgage Interest Rates

There are essentially two significant components that determine mortgage interest rates: market and economic conditions, and what I'll call personal and lender-specific influences. 

Let's consider each of them. 

Market and Economic Conditions 

Several market and economic factors affect the baseline for all mortgage rates and are largely outside a borrower's control. 

Let's discuss! 

Bond Market & Treasury Yields 

Mortgage rates are directly tied to the yields on U.S. Treasury notes, particularly the 10-year Treasury yield, and mortgage-backed securities (MBS). These are considered "safe havens" for preserving financial assets. When investor demand for these safe-haven assets increases – most often during times of economic uncertainty – yields, and thus mortgage rates, tend to fall. Conversely, low demand pushes rates up. 

Now, this may confuse your borrowers. So, you should tell them that these financial instruments work inversely to interest rates because their "fixed coupon" payment becomes more or less valuable as new such financial instruments offer different rates. So, when market rates rise, existing bonds with lower fixed payments become less attractive, and their prices fall to a competitive yield; and when rates fall, existing bonds become more valuable, and their prices rise. This inverse relationship means if you sell an old bond when rates are up, you'll get less; if you sell when rates are down, you'll get more. 

Inflation 

High inflation leads lenders and investors to demand higher interest rates to offset the erosion of the purchasing power of future payments. When inflation is low, rates tend to be lower. 

An example would be when high inflation prompts the Federal Reserve to raise interest rates, making mortgages more expensive (for instance, from 3% to 6%). Hence, a buyer of a $300,000 home pays more monthly, and when investors demand higher yields on bonds to compensate for their future earnings, they buy less. At the same time, low inflation allows for lower borrowing costs, stimulating spending and investment.

Tuesday, December 2, 2025

Non-Delegated Lenders: Quality Control for Non-QM Loans

Podcast | Substack

QUESTION 

I am one of the underwriters for a non-delegated lender. We received a request from an investor to conduct quality control. My boss says we do not have to do quality control. His position is that, at most, we need only a limited quality control audit. I came from another non-delegated lender, and they always did QC. 

He says we do not have to perform most aspects of QC audits, including credit analysis, re-verifications, credit reports, appraisal reviews, adverse action reviews, EPD issues, and GSE/FHA-VA underwriting reviews. Because we originate non-QM loans, he says QC is minimal. I read your Bulletin 2017-12, and it clearly shows that non-delegated lenders should do QC. 

I would like you to discuss QC requirements for non-delegated lenders. 

Does a non-delegated lender have to do quality control for non-QM loans? 

OUR COMPLIANCE SOLUTIONS 

We recommend the following compliance solutions for quality control support: 

Quality Control Audits

Our audits focus on risk mitigation, compliance, error correction, process improvement, verification, and ongoing monitoring. 

QC Tune-up®

This is our Second Line of Defense review that focuses on predictable output, reliable data, investor confidence, and reduced production cost. 

RESPONSE TO YOUR QUESTION

The question about a non-delegated lender having to conduct quality control seems to be one of those perennial questions that pop up from time to time. There is no mystery to the requirement. I appreciate that you have been reading our Bulletins. Anyone who wants to subscribe to our free Bulletins, please sign up! 

Whether you are originating QM or non-QM loans, you should be conducting quality control audits. Fannie Mae's non-delegated quality control (QC) requirements include having a comprehensive written QC plan, a process for selecting loans for prefunding and post-closing reviews, and a system for reporting and taking corrective action. 

If you're a non-delegated lender originating QM loans, the QC plan should be independent of the production process, and, among other things, you must conduct a minimum number of prefunding and post-closing QC reviews each month, based on a percentage of total loan volume. 

If you're a non-delegated lender originating non-QM loans, you should have QC processes in place. Because non-QM loans do not meet the criteria for purchase by Fannie Mae or Freddie Mac, the lender assumes all the risk, making a robust QC program essential to manage the loan quality and potential defects. 

Let's look somewhat broadly at the QC requirements. You must have a written QC plan that outlines your QC philosophy, objectives, and risks, with a process for selecting loans for review using random and/or discretionary methods across all products. The QC function must be independent of the production process, or, at a minimum, reviews must be conducted by personnel not involved in underwriting the specific loans subject to audit. 

The QC plan for QM loans must cover both prefunding and post-closing reviews, ensuring compliance with the Fannie Mae Selling Guide, the lender contract, and applicable laws. You can check out Fannie's requirements in the Lender Quality Control Programs, Plans, and Processes section. 

With respect to pre-funding, a minimum number of prefunding reviews must be completed each month, with the loan selection meeting at least the lesser of 10% of the prior month's total loans, 10% of current month projections, or 750 loans. 

Regarding post-closing, loans must be selected for monthly reviews, and the entire QC cycle must be completed within 90 days of loan closing. 

You must have documented procedures for reporting QC findings to management, documenting loan level findings for resolution, and taking timely corrective actions. All QC-related documentation must be retained for at least three years. An internal audit of the QC process itself should be performed annually to ensure compliance with the lender's policies and procedures. Our QC Tune-up®, a Second Line of Defense function, provides such support.

Thursday, September 4, 2025

Artificial Intelligence Disclosure

QUESTION 

I am the General Counsel and Compliance Officer of a mortgage lender. Our footprint is currently in 35 states. Recently, we have begun to use Artificial Intelligence in our loan origination process. However, I have some concerns about proper consumer disclosure. 

In my view, we should be disclosing our specific use of AI to borrowers. We should disclose the role AI plays in our loan applications from the point of sale to close, and, if applicable, beyond. But I do not find much regulatory guidance to lean on. I would appreciate your views on AI disclosure and, if possible, which areas would be subject to such disclosure. 

Is there a requirement for a mortgage lender to issue an AI consumer disclosure? 

What regulatory areas are potentially impacted by AI, thereby causing AI disclosure? 

COMPLIANCE SOLUTIONS 

AI Tune-up® 

Artificial Intelligence Statement  

RESPONSE 

There is currently no broad legal requirement for lenders to disclose the general use of AI in loan applications. However, under existing consumer protection and fair lending laws, lenders are legally required to disclose specific, accurate reasons for adverse actions, such as a loan denial, even if a complex AI or algorithmic system made the decision. 

This transparency is mandated by the Equal Credit Opportunity Act (ECOA), and regulatory bodies like the Consumer Financial Protection Bureau (CFPB) have issued guidance emphasizing that the complexity of AI is not an excuse for failing to provide a clear explanation. 

Regulatory Mandates 

Take, for instance, the regulatory mandates involving adverse action disclosure. The CFPB has directly addressed the issue of "black-box" models, which are AI systems whose logic is not clear even to their developers. The CFPB emphasizes that lenders cannot point to a broad category from a checklist, such as "purchasing history," if a consumer is denied credit based on AI analysis. Instead, the lender must provide specific details, such as the types of goods or places that influenced the decision. 

Also, there is no "AI exemption." A lender's use of AI or machine learning does not create a special exemption from fair lending laws. The CFPB has made it a priority to ensure that the use of technology does not allow lenders to circumvent established consumer protection regulations. In addition to the CFPB, regulators and the Federal Trade Commission have warned that there is no "AI exemption" for existing fair lending and consumer protection laws. Therefore, undisclosed AI could be found to violate these laws, leading to enforcement actions. 

The Colorado Artificial Intelligence Act 

Some state laws specifically address AI disclosure. For example, the Colorado Artificial Intelligence Act (CAIA) requires developers to test for algorithmic discrimination in consequential decisions, and some state consumer protection statutes allow for prosecution if an AI's biased outcomes cause consumer harm. This is a landmark act in many ways. If you are originating loans in Colorado, you should review the relevant regulations. However, you would do well to conduct a statewide review of AI legislation in all states where you are licensed to originate mortgage loans. 

CAIA may be a model for the direction states are going with respect to AI disclosure. The Act defines algorithmic discrimination, which is the unlawful differential treatment that disfavors an individual or group on the basis of protected characteristics. The algorithmic discrimination would be caused by high-risk artificial intelligence systems, defined as any system that, when deployed, makes — or is a substantial factor in making — a "consequential decision," which generally relates to those involving education, employment, financial services, housing, health care, or legal services. 

Under the CAIA, there are stipulated requirements for developers to clearly display on their website or in public use an up-to-date disclosure of any high-risk AI systems they have developed and make available how they manage known or reasonably foreseeable risks of algorithmic discrimination. Any determination that the AI system has caused or is reasonably likely to cause algorithmic discrimination must be brought to the attention of the Colorado attorney general, among others.

Monday, September 30, 2024

RESPA Violations: Inconsistent Enforcement

QUESTION 

I am the General Counsel and Compliance Officer of a mortgage lender in the Northeast. We originate retail and wholesale loans and are licensed in all states and territories. Recently, we had a multistate banking audit. The audit found that some of our Third-Party Originators (TPOs) had violated RESPA. 

After conducting a servicing quality control audit, we have decided to sue several TPOs for causing these RESPA violations. The problem we’re having is that RESPA does not address its enforcement consistently or comprehensively. It provides specific penalties in some sections but fails to mention remedies for violations in other sections. 

I want some guidance in navigating RESPA’s maze to determine where a private right of action is available and where it isn’t. In particular, I need some advice on how the TRID rule affected RESPA enforcement and private causes of action. 

COMPLIANCE SOLUTIONS 

Servicing Quality Control Audits 

Servicing Tune-up® 

Servicing Compliance 

ANSWER 

The Dodd-Frank Wall Street Reform (Dodd-Frank) and Consumer Protection Act (CPA) may have altered your scenario somewhat. Although courts generally have failed to examine this issue thoroughly, it is important to note that courts have given Chevron deference to the CFPB’s analysis of the topic. However, that approach may be about to change in light of Chevron's demise,[i] which I will discuss a bit below. 

If you’re using outside counsel for this litigation, be sure to retain a firm that has extensive experience in such matters. You can contact me here to discuss a referral. 

I will give you a brief overview with an emphasis on the TILA-RESPA Disclosure Integration Rule (TRID Rule). Let’s first talk history! 

RESPA PENALTIES 

The Real Estate Settlement Procedures Act (RESPA) contains penalty provisions for Section 6, which deals with mortgage servicing and escrow administration);[ii] Section 8, which prohibits kickbacks and unearned fees);[iii] Section 9, which deals with title companies;[iv] and the escrow statement requirements of Section 10.[v] 

RESPA does not include penalties for violations of other sections, such as Section 4 (HUD-1 Settlement Statements), Section 5 (Special Information Booklets and Good Faith Estimates), Section 10 (Limitations on Escrow Accounts), and Section 12 (Fees for Preparation of Truth-in-Lending or Settlement Statements). However, the absence of RESPA penalty provisions may no longer afford defendants the comfort it once did. 

RESPA’s HANDOFF TO TILA 

The TRID Rule, adopted in November 2013, and effective October 3, 2015, introduced another twist to RESPA enforcement. As just stated, RESPA does not provide private rights of action for violations of Sections 4 and 5, the sections regarding Good Faith Estimates and Settlement Statements. The TRID Rule extrapolated some of the RESPA Section 4 and 5 requirements that had previously appeared in Regulation X (implementing RESPA) over to Regulation Z (implementing TILA, the Truth in Lending Act). 

A HISTORY LESSON 

This transmogrification of RESPA Sections 4 and 5 had the effect of expanding RESPA liability by bringing those provisions into the purview of the TILA – and TILA provides for a private right of action. You might think of it as legal and regulatory prestidigitation! 

Now, there was considerable pushback to this switcheroo. One of the biggest gripes was that the TRID Rule would invite consumers to bring lawsuits seeking TILA remedies for RESPA violations. The upshot of this concern was to have the Consumer Financial Protection Bureau (CFPB or Bureau) specify which provisions of Regulation Z, as affected by the TRID Rule, relate to TILA requirements and which relate to RESPA requirements.[vi] 

The CFPB awkwardly responded in this way: 

“While the final regulations and official interpretations do not specify which provisions relate to TILA requirements and which relate to RESPA requirements, the section-by-section analysis of the final rule contains a detailed discussion of the statutory authority for each of the integrated disclosure provision.” 

And, having side-stepped a formal resolution, the 

“… detailed discussions of the statutory authority for each of the integrated disclosure provisions [in the section-by-section analysis] provide sufficient guidance for industry, consumers, and the courts regarding the liability issues raised by the commenters.” 

Obviously, this was hardly a satisfying response. Nevertheless, industry participants implemented the TRID Rule while still expressing considerable concern about the CFPB's choice to fit the changes into Regulation Z. The apprehension stemmed from the fact that TILA and Regulation Z impose substantial liability for disclosure violations, compared to the general lack of liability under RESPA and its implementing Regulation X. 

THE CFPB’S SOLOMONIC DECISION 

The CFPB chose to exclude most closed-end consumer credit transactions secured by real property, other than reverse mortgages, from the early disclosure requirements of Regulation Z[vii] and the standard closed-end disclosure requirements of Regulation Z.[viii] In place of those requirements, the CFPB’s TRID Rule created three sets of provisions for the partially-excluded loans: 

1.     Loan Estimate. 

2.     Closing Disclosure. 

3.     Special Information Booklet. 

This partial exclusion of TRID Rule transactions from certain Regulation Z provisions leaves the rest of Regulation Z in effect for those transactions, as previously applied.[ix]

Conversely, the CFPB fit the TRID changes into the RESPA regime by excluding the loans covered by the TRID Rule from five provisions of RESPA Regulation X: 

·       Special Information Booklet. Regulation X § 1024.6. For loans subject to the TRID Rule, Regulation Z § 1026.19(g) imposes the same Special Information Booklet requirement. 

·       Good Faith Estimate. Regulation X § 1024.7. For loans subject to the TRID Rule, Regulation Z § 1026.19(e) imposes the Loan Estimate requirement. 

·       HUD-1/1A Settlement Statement. Regulation X § 1024.8. For loans subject to the TRID Rule, Regulation Z § 1026.19(f) imposes the Closing Disclosure requirement. 

·       HUD-1/1A Administration. Regulation X § 1024.10, one day advance inspection of HUD-1/1A Settlement Statement, delivery, and recordkeeping requirements. For loans subject to the TRID Rule, Regulation Z §§ 1026.19(e) and (f) impose corresponding requirements for Loan Estimates and Closing Disclosures. 

·       Servicing Transfer Application Disclosure. Regulation X § 1024.33(a). For loans subject to the TRID Rule, Regulation Z § 1026.37(m)(6) requires a corresponding disclosure on page three of the Loan Estimate. 

In general, the TRID Rule leaves these provisions of Regulation X in place for the loans not subject to TRID, that is, reverse mortgages and the few federally related mortgage loans made by creditors not subject to Regulation Z (i.e., lenders who make five or fewer mortgage loans per calendar year secured by dwellings, unless they make more than one High Cost Mortgage  (HCM)). All of the other provisions of Regulation X remain in place for federally related mortgage loans, including those subject to the TRID Rule. 

GOOD LUCK WITH THAT! 

A careful consideration of the CFPB’s detailed discussion in its section-by-section analysis of the TRID Rule suggests that the agency’s response can be summarized as follows: 

Bona Fortuna in separating disclosure liability between TILA and RESPA! 

Take a deep breath and consider this off-the-cuff outline of the TRID disclosures in the context of the statutory framework for each disclosure item through the lens of the following cascade: 

1.     Any prior implementation of that requirement,

2.     The CFPB’s research into the effectiveness of that disclosure from both a consumer and industry perspective,

3.     The Bureau’s alteration (if applicable) of the statutory requirement or previous regulatory implementation of the requirement to respond to its research,

4.     The Bureau’s agency’s reasons for implementing that disclosure as part of TILA-RESPA disclosure integration, and

5.     The statutory support for including the final version of the disclosure. 

And that’s just for starters! 

In most cases, the ultimate statutory support rested on a specific requirement stated in TILA, RESPA, and/or the Dodd-Frank Act, bolstered by the regulatory flexibility offered in TILA § 105(a) (sometimes also § 105(f)), RESPA § 19(a), and Dodd-Frank Act §§ 1032(a) and 1405(b). 

The CFPB relied on regulatory flexibility given by these provisions because the agency found it necessary to reconcile differences between the RESPA and TILA statutes and between sometimes differing provisions within the TILA statute itself. The agency also found it appropriate to alter many of the statutory requirements (and even discard some) based on conclusions drawn from its research. Consequently, many resulting disclosure items are not derived solely from one statute or the other but from one or more statutory starting points and the broad rulemaking authority given to the CFPB by TILA, RESPA, and the Dodd-Frank Act. Obviously, unraveling the final result to separate a RESPA claim from a TILA claim can be a challenging task. 

So far, most courts have taken the CFPB at its word and relied on its analysis of the TRID Rule (and the 2013 RESPA and TILA Mortgage Servicing Rule) to determine whether a private right of action is available for a regulatory violation. But there has been litigation.[x] And now, after the U.S. Supreme Court’s overruling of the Chevron deference,[xi] I think we’re likely to see courts dive more deeply into this issue.

OBSERVATIONS

As suggested above, the U.S. Supreme Court’s overruling of Chevron deference may require courts to ignore the CFPB’s stated “intentions” and look more closely at the underlying statutory provisions.[xii] 

Conceivably, borrowers might add Dodd-Frank Act claims to their RESPA claims. That is, they might claim that violations of RESPA violate the Dodd-Frank Act. Section 1055 of the Dodd-Frank Act offers the possibility of substantially higher penalties than those specified by RESPA – ranging from $5,000 per day for any violation to $1 million per day for a “knowing violation” (adjusted annually to reflect inflation). Whether an enforcement agency must seek Dodd-Frank penalties or may be obtained by consumers in private actions is an open question courts may someday decide. 

Jonathan Foxx, Ph.D., MBA
Chairman & Managing Director 
Lenders Compliance Group


[i] Loper Bright Enterprises v. Raimondo, 144 S. Ct. 2244 (2024)

[ii] 12 USC §§ 2605(d) and 2614

[iii] 12 USC §§ 2607(d) and 2614

[iv] 12 USC §§ 2608(b) and 2614

[v] 12 USC §§ 2609(d)

[vi] Indeed, a rather convoluted view suggested that the CFPB should implement the TILA disclosure requirements in Regulation Z and the RESPA disclosure requirements in Regulation X in order to discourage litigation invoking TILA’s liability scheme for RESPA violations.

[vii] Regulation Z § 1026.19(a)

[viii] Regulation Z § 1026.18

[ix] For example, the Consumer Handbook on Adjustable Rate Mortgages (CHARM) Booklet and ARM Program Disclosure requirements of Regulation Z § 1026.19(b) continue to apply as they did prior to the TRID Rule.

[x] A recent decision by a federal district court in Texas illustrates this issue. Bassett v. PHH Mortgage, 2024 U.S. Dist. (S.D. Tex. June 27, 2024) (magistrate recommendation), approved and case dismissed by 2024 U.S. Dist. (July 16, 2024). Note: This litigation determined, in particular, that 12 U.S.C. §§ 2605(f) and 2614 do not create private causes of action, nor does RESPA provide private causes of action for violations of Regulation X §§ 1024.35 and 1024.39. As support, the court cited several other decisions within its district. The court acknowledged that Regulation X § 1024.41, “unlike the other RESPA provisions at issue…expressly provides for a private right of action.”

[xi] Op. cit. i

[xii] Op. cit. x

Friday, July 5, 2024

Risk-Based Pricing Notice: Timing

QUESTION 

We have a question about the risk-based pricing method. Our procedures already cover the required format of the pricing notice and the types of credit covered. What we want to know is when we are required to provide the risk-based pricing notice for closed-end credit transactions. Also, a question that concerns us is if we need to provide it if we are not going to do the loan. 

When are we required to provide the risk-based pricing notice for closed-end credit? 

Do we have to provide the risk-based notice if we don’t do the loan? 

COMPLIANCE SOLUTION 

Policies & Procedures 

ANSWER 

FACTA  (Fair and Accurate Credit Transactions Act), which amended the FCRA (Fair Credit Reporting Act), added a requirement that mandates that if you use a consumer report in connection with an application for, or a grant, extension, of other provision of, credit on material terms that are materially less favorable than the most favorable terms available to a substantial proportion of consumers from or through your financial institution, based in whole or in part on a consumer report, then you must provide a notice to the consumer containing specific information. 

The purpose of the requirement is to alert the consumer as to how information in their consumer report and their credit score can affect the terms of credit they receive. It is meant to enable the consumer to assess if there are any errors in their consumer report and, further, allows them to understand better how certain factors may influence their credit standing. 

Timing is a central feature of the risk-based pricing notice (“Notice”). The timing of the Notice depends on the particular situation. However, I can summarize the general timing rules for a closed-end credit transaction.

Suppose you are granting, extending, or offering some other provision of closed-end credit. In that case, the Notice must be provided to the consumer before consummation of the transaction – but not earlier than the time the decision to approve an application for, or a grant, extension, or other provision of, credit is communicated to the consumer by the financial institution required to provide the Notice. 

In the case of a review of credit that has been extended to a consumer, the Notice must be provided to the consumer at the time the decision to increase the APR (Annual Percentage Rate) based on a consumer report is communicated to the consumer by the financial institution required to provide the Notice. 

If no Notice of the increase in the APR is provided to the consumer before the effective date of the change in the APR, the Notice must be provided no later than five days after the effective date of the change in the APR.[i] 

Now, your other question is often asked because the answer does not seem intuitive. You asked if a Notice must be provided if a financial institution does not grant, extend, or otherwise provide credit. 

The short answer is No! 

The requirement to provide a Notice applies only when, based in whole or in part on a consumer report, a financial institution grants, extends or otherwise provides credit to a consumer on material terms that are materially less favorable than the most favorable material terms available to a substantial proportion of consumers from or through that financial institution. That leads to a brief discussion of adverse action. 

There is an express exception to the Notice requirement when a consumer is provided with an adverse action notice.[ii] Potentially, a financial institution may need to provide a Notice if it grants, extends, or otherwise provides credit and the consumer does not accept the credit, because the deadline by which a Notice must be provided may be reached before the financial institution learns that the consumer will not accept the credit.


Jonathan Foxx, Ph.D., MBA
Chairman & Managing Director 
Lenders Compliance Group


[i] 75 FR 2724, 12 CFR § 222.73(c); 16 CFR § 640.4(c)

[ii] 75 FR 2724, 2731

Thursday, March 14, 2024

Steering Practices in Comparison Platforms

QUESTION 

A few months ago, you wrote about the regulatory challenges associated with comparison platforms. It was eye-opening to us. Because of your guidance, we revised our relationship with a comparison platform. Thank you! 

But I must write you about a recent problem with the comparison platform. The platform offers placement for our loan products because of financial inducement, making the listing likely to be seen by the consumer. The preferred placement has many more features, such as requiring fewer clicks to access product information or increasing the likelihood that a consumer will consider or select our listing. We paid extra for the placement to be "featured." We also found that the platform was even putting itself in the digital comparison versus our listing. 

Our Compliance Officer believes that we have become entangled in a steering scenario. She has met with management to get them to cancel the arrangement with the platform altogether. They are reluctant to cancel because they think she is exaggerating the risk. They get a lot of business from the leads generated from the comparison platform. 

I would like your view. You are always direct and abide by legal and regulatory guidelines. 

Do digital comparison platforms or lead generators cause potential regulatory violations by preferencing products or services based on financial or other benefits to the platform operator?

COMPLIANCE SOLUTION

Policies and Procedures

ANSWER 

Yes. The comparison platform may violate the prohibition on abusive acts or practices if they distort the shopping experience by steering consumers to certain products or services based on adjusted remuneration to the operator. And, to be clear, this is steering. If steering is implemented, it violates the Consumer Financial Protection Act (CFPA). 

Similarly, lead generators can violate the prohibition on abusive practices if they steer consumers to one participating financial services provider instead of another based on compensation received. It is often the case that consumers rely on a digital comparison platform or a lead generator to act in their interests. Unfortunately, however, it is also the case that platforms and lead generators may take unreasonable advantage of consumers by giving preferential treatment to their own or other products or services through steering or enhanced product placement for financial or other benefits. This way leads to UDAAP violations. 

My article, Pitfalls of Mortgage Comparison Platforms, focused on RESPA Section 8 violations triggered by referrals from rate comparison platforms. I noted the Consumer Financial Protection Bureau (CFPB) maintains that operators of online comparison platforms receive a prohibited referral fee when they use or present information in a way that steers consumers to mortgage lenders in exchange for a payment or something else of value. 

Another article I published, RESPA Section 8 Triggers on Mortgage Comparison Platforms, focused on several circumstances where digital mortgage comparison-shopping platforms may violate RESPA. 

For a wider view, you can read my article, Digital Mortgage Comparison Platforms, where I stated, among other things, that the CFPB appears to suggest RESPA may be violated even where every lender pays the same compensation to the platform operator, if the information provided has the effect of steering a consumer to a particular lender. 

You may want to read the aforementioned articles in the context of my response to your question about preferencing products and services on a digital comparison platform. Your use of the verb "preferencing" is correct because the CFPB uses this word to flag steering! 

At its core, preferencing involves compensation arrangements associated with digital comparison platforms.[i] Loan product providers pay some platforms on a fee-per-action basis (i.e., by receiving fees per click, per application, per conversion, per offer, or per sale). Often, the platform may allow firms to bid against each other for advantageous placement by paying "bounties," which target consumers fitting certain consumer characteristics or aimed at meeting certain volume goals. 

Lead generators sell consumer information to lenders. Sometimes, they provide this service without contacting the consumer. But, regulatory concerns grow when these entities collect data directly from consumers by advertising websites that present themselves as helping consumers get a loan or connect with lenders. There has been plenty of litigation in this area, such as in Federal Trade Commission v ITMedia Solutions, LLC.[ii] The complaint alleged that the lead generator "unlawfully used a 'loan application' form to collect consumers' information by deceptively presenting itself as connecting consumers with lenders.”[iii] 

If you want a basic guideline, here it is:

You must protect and facilitate the consumers' ability to effectively compare and choose among options for consumer financial products or services. If you are not doing so or involving yourself in arrangements that contravene this guideline, you are exposing yourself to regulatory violations. 

Indeed, this guideline is a foundational, statutory objective of the CFPB.[iv] Consider it a mandate. The CFPA legislative history states that an important purpose of the CFPB is to ensure that "a consumer can shop and compare products based on quality, price, and convenience without having to worry about getting trapped by the fine print into an abusive deal."[v] 

As I noted above, unreasonable advantage is tantamount to a threshold issue implicating UDAAP.[vi] So, let's describe this concept in the context of digital comparison platforms and lead generators:

These entities leverage consumer reliance to take unreasonable advantage of consumers where they preference particular providers or products over others in exchange for financial or other benefits to the operator, as opposed to making presentations or lead distribution decisions using other factors not relating to the platform operator's or lead generator's relative compensation from different providers, including where consumers put reasonable reliance on the entity to act in accordance with consumers' interest.[vii] 

The phrase "reasonable reliance" and "consumers' interest" can mean many things. Litigation often turns on the interpretation of these terms. However, a growing body of federal agency guidelines and case law has pretty much determined their regulatory parameters. Once a comparison platform or lead generator puts itself into a position to assist people in selecting a provider, the door opens to consumer reliance. The entities’ representations and communications can be explicit or implicit. 

For instance, reasonable consumer reliance may exist when a platform or lead generator assumes the role of acting on consumers' behalf or helping them select products or services based on consumers' interests.[viii] If you visit digital comparison platforms, you may see that some of them "match" consumers to specific products and services, whether done by automated algorithms, artificial intelligence, or curated recommendations. 

Some lead generators promote themselves as intermediaries between themselves and well-known financial institutions. That in itself can engender consumer reliance[ix] because their real, market-enterprising role may be hidden by presenting themselves as a tool for consumers to connect with trusted lenders or receive the best available terms for a consumer financial product or service. This means of contact with the public, given the consumer's individual circumstances, may lead the consumer to reasonably rely on the entity to act in the consumer's interests.[x] 

Here's a brief explanation of how a comparison platform or lead generator explicitly or implicitly engenders consumer reliance:

If a comparison platform or lead generator explicitly or implicitly holds out its services as presenting information based on a consumer's interests, it may be reasonable for the consumer to rely on the service to respond accordingly. 

I have seen comparison platforms openly stating that their service is "objective!" Now, that may be so, or it may not, but the service certainly claims it to be so – and that is sufficient for explicitly engendering consumer reliance. 

In fact, even if the platform does not openly state its service is objective, it may use certain words or phrases that implicitly engender consumer reliance, such as using the word "expertise" in helping consumers evaluate options; describing their service as providing "research-based" rankings of options for consumers; stating that they will "help you today" to "achieve your financial goals"; purporting to match consumers with the "best" or "right" offers; claiming to "put consumers first;" or providing a "one stop shop" claiming all the information consumers need to make informed selections among potential providers.[xi] 

To expand on the aforementioned "consumers’ interest” stated in my description of unreasonable advantage, comparison platforms and lead generators may adjust their presentations of consumer products and services based on fees or other benefits that are not in a consumer’s interest. These adjustments occurring in digital comparison platforms and lead generators are a form of steering. There is a significant body of law, federal agency guidelines, and consumer disclosure regulations that have concluded consumers’ interests are not served when consumers are steered toward more expensive or less favorable products, and would be the case when those products are offered by digital comparison platforms and lead generators (or their affiliates) where those products generate more revenue for these entities.[xii]


Jonathan Foxx, Ph.D., MBA
Chairman & Managing Director 
Lenders Compliance Group


[i] Preferencing and Steering Practices by Digital Intermediaries for Consumer Financial Products or Services, Intermediaries for Consumer Financial Products or Services, Consumer Financial Protection Circular 2024–01, Consumer Financial Projection Bureau, 12 CFR Part X, FR: Vol. 89, No. 49, March 12, 2024 (Rules and Regulations 17706-17709)

[ii] Federal Trade Commission v. ITMedia Solutions LLC et al., FTC Matter/File Number 1523225, Civil Action Number 2:16-cv-09483, C.D. Cal. January 5, 2022 (Complaint and Order)

[iii] Idem

[iv] Under the CFPA, a central purpose of the CFPB is to promote ‘‘fair, transparent, and competitive’’ markets. See 12 USC 5511(a).

[v] S. Rep. No. 111–176, at 11, 229 (2010).

[vi] There are violation triggers in many other prongs of the abusive prohibition, such as under 12 U.S.C. 5531(d), 12 U.S.C. 5531 and 5536(a)(1)(B)’s prohibitions against unfair or deceptive acts or practices, or other Federal, State, or local laws.

[vii] See 12 U.S.C. 5531(d)(2)(C), and generally, Policy Statement on Abusive Acts or Practices, April 3, 2023, Consumer Financial Protection Bureau

[viii] Idem

[ix] See CFPA § 2031 (d)(2)(C)

[x] Op. cit. i., Reasonable Reliance, at 17708

[xi] Op. cit. ii

[xii] See, i.e., FTC v. Blue Global, LLC, No. 2:17–cv–2117, D. Ariz. July 3, 2017. Blue Global collected loan applications and promised to match consumers with loans that had the best interest rates, finance charges, and repayment periods when, in fact, they indiscriminately sold leads.