Eric-Thompson

Slashing Risk With Collateral Data

Housing outlooks are optimistic and we’re all entering the busy season. Every lender is focused on borrower experience while getting deals done, and the collateral valuation process is a critical part of your overall success. Make a mistake there, and someone will end up paying the price.

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With the appraisal process — and evaluating collateral in general — there is no such such thing as a zero cost mistake. Whether an error results in the need for re-disclosure, a returned appraisal or a compliance violation, each time a lender, AMC or appraiser takes action on incorrect property information, everyone risks lost time, lost money, or both.

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The problem is, mistakes are understandably prevalent when it comes to evaluating residential property. While some properties may seem similar, each has a distinct footprint. Each property you’re evaluating is surrounded by different neighborhoods and may have modifications or unique characteristics like lot size and views. These details can make a dramatic difference in the value of a property, and if they’re not recognized in the collateral valuation process it can mean losing a deal or making risky lending decisions.

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Fortunately, in the age of big data, the vast majority of properties have a unique data set consisting of thousands of pieces of data. If you want to make the right decisions, you need to be certain your information is correct. If you don’t have access to reliable, relevant data, it’s virtually impossible to understand a property well enough to avoid decisions that lose money.

You can get the data to verify your collateral valuation decisions very easily. Several providers offer software, property reports, and automated valuation models (AVMs). The technology is advanced enough today that you can integrate these systems and pick and choose the valuation verification methods you prefer.

Before you choose the collateral valuation and verification methods best for your lending institution and risk profile, make sure you ask the vendor these questions:

>>What makes this data or verification solution better than alternatives?

>>Can this solution be integrated with your overall process software so the entire collateral valuation workflow is easy to manage?

>>How is the data or solution verified? For example, if you’re using AVMs to verify appraisal report data, do you have a way to choose the best AVM for each individual property?

When you have a data verification solution in place, remember that collateral valuation is just one way to leverage your insights. Many lenders use the same solutions across the entire mortgage chain. With collateral data, you can determine borrower equity and LTVs in seconds. Before you disclose appraisal fees to the borrower, you will have a better idea of the complexity of the assignment. In post-closing, you can use the data to discover a property or neighborhood’s footprint for better due diligence during audits. Finally, in the loan servicing stage, the same data can be used to ascertain your portfolio’s value direction and determine ideal outcomes for properties in your portfolio.

The data you need to make the right lending decisions is out there, and it’s easy to integrate with your overall process. The cost is pennies on the dollar compared to the risks of proceeding blindly, so it’s time to take a step into big data to verify your collateral valuations.

About The Author

Eric Thompson
Eric Thompson is a Senior Consultant at Mercury Network, an online vendor management platform used by more than 700 lenders and AMCs. Eric has been in the industry for over fifteen years with a wide range of experience from appraiser training to owning and operating a successful appraisal management company. His appraisal management and compliance expertise spans smaller community banks and credit unions to the largest lenders and AMCs in the country. He consults with Mercury Network clients on appraisal workflow, compliance, and efficiency issues and he can be reached at Eric.Thompson@MercuryVMP.com.