Risk Management Archives - Page 3 of 3 - Cogent QC: Award-Winning Loan Quality Control & Compliance Software

Secondary Review Options in Cogent QC Systems

October 14, 2013 By Kaan Etem

In the most recent issue of American Banker, the CEO of Cape Cod Savings had this to say about the burden of regulatory compliance:

“…Because of HMDA and RESPA, we have checkers who check the checkers. Then we actually have another third layer of checkers who check the checkers who check the checkers. Then we have two outside consulting firms that check again.”

Sound familiar? All too familiar for some Cogent clients, who have multiple layers of QC and compliance operations – often at the corporate level, at the business unit level, and on an outsourced basis. And they invest so much in quality control and compliance because the alternative is painful. To cite just one instance, the Mortgage Bankers Association (MBA) sent this around last week:

“CFPB Assesses Civil Money Penalties For HDMA Data Errors
The CFPB has announced that it assessed civil money penalties against Mortgage Master, Inc., a non-bank, and Washington Federal, a bank, after examinations identified significant data errors in mortgage loans reported pursuant to the Home Mortgage Disclosure Act (HMDA). CFPB followed the announcement with a bulletin outlining the elements of an effective HMDA compliance management system and the resubmission thresholds, as well as other factors that the Bureau uses to determine if they will pursue a public HMDA enforcement action and associated civil penalties.”

Among other things, that bulletin states that “effective HMDA compliance management systems frequently include … comprehensive and regular internal, pre-submission HMDA audits.”

Aside from under-scoring the sheer scope of today’s regulatory compliance requirements, this reality also highlights the need for efficiency in performing secondary and tertiary audit reviews. This is why Cogent has been introducing more extensive secondary audit review options. The latest Supervisor Override functionality was covered in our recent ‘Version 4 Overview’ webinar (clients may contact support@cogentqc.com for a link to the recording.) With that, the possibilities now include:

Revert a completed loan audit and make changes to the original loan audit.
Use Supervisor Review to conduct a parallel supervisor audit, while preserving the original auditor’s work as the official audit of record.
Use Supervisor Override to override individual findings, thereby modifying the official audit of record but preserving a record of the original auditor’s findings.

These different approaches can be combined with appropriate pending and completion of loan reviews to tailor different secondary reviews to different situations. When all eyes are on you, it’s always good to have options.

MBA and FHA and Statistical Sampling in Quality Control

September 25, 2013 By Kaan Etem

We are pleased to see the FHA proposing to introduce more statistical sophistication into its Quality Assurance Process (QAP) and to see the MBA responding with reasonable critiques. There are a number of items under discussion which have been long-standing issues in the industry, including what defines a loan manufacturing defect, what are appropriate tolerance and severity levels for defects, and what are appropriate remedies. “Loan quality” must have a standardized definition to be useful. But the item that caught our attention was the discussion of statistical sampling.

FHA is proposing the following in its solicitation of information:

“Statistical sampling. FHA is also considering whether to establish a process to review a statistically significant random sample of loans for each mortgagee within a prescribed time frame after loan endorsement. Lenders would receive feedback on findings within an established timeframe. FHA would use the statistical sample, to estimate the defect rate on each lender’s overall FHA portfolio and then extrapolate the origination defect rate to all lender originations during the sampled time period, and thus have the lender compensate FHA for the estimated total risk to FHA resulting from the lender’s origination processes.The purpose of this process would be to increase the efficiency of FHA’s post-endorsement review process. HUD invites comment on the use of and optimal methodology for a statistically significant random sample, including the nature of the loans that should be included or excluded from the sample.”

The MBA has responded with this:

“Most importantly, MBA has serious concerns about the impact of a sampling methodology on independent mortgage bankers and community banks and the number of lenders participating in the FHA program. While larger lenders may be able to originate enough loans to generate statistically significant sample sizes, many smaller lenders would be challenged in this regard. It is unclear how HUD would address this situation and what, if any, allowances would be made for small lenders. Moreover, depending on the structure of the penalty system, paying an upfront percentage could have a much greater impact on smaller lenders than larger lenders. The possibility of sampling bias that results in “overpaying” for smaller lenders has potentially devastating consequences reducing competition and increasing the price for consumers. Companies could be forced out of business or cease originating FHA loans.”

Given the number of lenders we have seen who report only on the number of “findings” in their reviews, with no mention of defect rates or sampling method or population counts, it is encouraging to hear influential industry players talking about sample sizes and valid inferences to populations and statistical significance (albeit in a slightly different context.) If nothing else, it reminds us that the loan audits that take up so much of our time represent a small fraction of the loans we originate (or service). And that what matters is the quality of the entire origination (or servicing) pool, not just the samples we draw (which are simply proxies for the population.)

We say let the discussion continue. The more informed lenders are about what constitutes loan quality, the better they can do their jobs.

Fannie Mae releases new list of Loan Defect Categories

September 25, 2013 By Kaan Etem

In case you missed it, Fannie Mae released its new list of Loan Defect Categories on August 27, 2013.

QC- loan-defect-categories-FNMA

Says Fannie, “The list shows the loan defects, by categories, identified by Fannie Mae in post-purchase review of our acquisitions. These defects (which may be eligibility violations) are referenced in reporting to lenders on the quality of their deliveries.”

So if you are setting up or overhauling your standard post-closing audit checklist, this is a good generic template to begin with. It covers all of the essential categories of loan QC errors (or of loan quality, to put it another way). If you are using Cogent’s loan audit software, in which these are called audit question categories, all that’s missing is a category and question coding scheme. With that, your reporting possibilities are almost limitless, allowing you to report by defect category or sub-category, by individual audit question, and so on.

Thanks to Fannie for taking another step towards standardizing the scope of loan quality reviews.

MBA’s Risk Management & Quality Assurance Forum 2013

September 10, 2013 By Kaan Etem

If you’re attending the MBA’s Risk Management & Quality Assurance Forum in Phoenix, AZ this week, stop by Cogent’s booth and say hello to our own Hakki Etem and James Robinson. And if you’re a client, we look forward to seeing you at dinner on Wednesday evening.

There are several interesting and topical sessions on the agenda this year. One session we’ll be paying particular attention to is “Using Sampling Techniques to Manage Quality in Your Organization,” a topic that is near and dear to our hearts.

The rest of the schedule is here: https://events.mortgagebankers.org/RMQA2013/sessions/#INFO

More information about the event here: https://events.mortgagebankers.org/RMQA2013/default.html

See you there!

Meaningful Metrics and Process Improvement

May 29, 2013 By Kaan Etem

“The availability of meaningful and actual information is a true weakness in QC today.” So says Jeremy Burcham, AVP of Loan Review Solutions at Interthinx in a recent video in National Mortgage News’ Ask the Experts series. We agree with that. We also agree when he states that many QC operations – including outsourced QC firms – are not focused on obtaining performance data that will help them improve their processes. Instead, they are often focused on individual issues like fixing a particular loan, or internal issues like what is politically correct within their organizations, or a meaningless metric (e.g., total number of errors found, regardless of context), or even just completing their assigned reviews by the deadline.

Given that the purpose of quality control is to improve processes, there are few activities more important than thinking through the appropriate metrics to use to track progress. If you don’t know where you’re going, as the adage goes, how will you know when you get there? Cogent has some ideas about how to approach this and we invite you to browse the white papers on our website for more information. And there are others with deep expertise in this area. For instance, Avinash Kaushik, one of the most respected authorities on Web Analytics, has these guidelines on the attributes of great metrics.

For now, though, a tip of the hat to Interthinx for helping raise awareness of the need for good, meaningful and actionable data.