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Signs of a strengthening economy and the resulting rise in interest rates have put the brakes on the mortgage “refi” explosion. What was a seemingly endless influx of first and second mortgage originations has declined dramatically, something that has proven painful for many lending organizations. Maintaining existing mortgage customers has become difficult for many credit unions as well. To answer these challenges, savvy credit unions are implementing progressive solutions to attract new members and better manage the profitability of existing ones. A pertinent example can be found with today’s Automated Valuation Model (AVM) technology. Over the past several years, AVMs have proven to be a valuable tool for helping mortgage professionals quickly assess property values. In addition to estimating a subject property’s market value, other useful data can be derived from an AVM, such as high and low values of the home, comparables, census information, mapping features and confidence scores. By blending this information with consumer credit and demographic data, credit unions are improving their acquisition marketing, quality control and portfolio review efforts. Using AVMs to Make Direct Marketing and Distribution Decisions The four areas where lenders are now incorporating AVMs include prescreens, account triggers, portfolio reviews and branch location decisions. Credit unions can easily apply these approaches. In each scenario, the lending institution uses AVM data to assess the amount of equity a targeted prospect has in their home. This information is then correlated with other predictive credit and demographic characteristics to make a variety of important business decisions. This can be done on an individual or batch basis, with results generated in real-time. The direct impact for lenders is the ability to eliminate unqualified applicants before executing a marketing campaign, thereby reducing associated costs and increasing efficiency. In the prescreen world, AVMs enable lenders to better target prospects for direct mail solicitations. Lists are pre-screened by looking for individuals that closely resemble an ideal customer from a risk and marketing perspective, which can partially lower direct marketing costs. Marketing lists can be processed in batch mode, meaning one file can be received that contains many pre-approved prospects. The second area where credit unions can leverage AVM data is predictive “triggers.” This application works by monitoring a population for credit and equity changes relevant to a lender’s business, and outputting these individual’s records on a daily basis. Lenders can quickly target prospects with the right product at the most opportune time. Many service providers such as TransUnion will customize and fully automate their solutions to give lenders customized data. AVM data also is being used to generate analytical reports for portfolio reviews. Lenders can obtain actionable conclusions and recommendations for how to best reach a particular target audience within their own portfolio. Among the many uses of such an analysis is the ability to uncover cross-sell opportunities. Similar to pre-screens and account triggers, these reports analyze key credit characteristics and home equity values. Trends are then uncovered to assess changes in consumers’ lives that indicate the need for additional products, such as home equity loans, HELOCs or refis. Lastly, lenders are starting to use AVM data to more accurately target new or revitalized geographic areas for potential branch locations. For years, lenders have analyzed aggregated consumer credit information for this purpose. Now, blending AVM data into the analysis can identify trends in property values, an insight that can signify the potential attractiveness of increasing your prominence in a certain area. In this scenario, the lender looks for high concentrations of consumers with credit and AVM characteristics that define their customer base and then determines whether it warrants opening a new branch. Here is an example that ties all this together: Through analyzing AVM data, ABC credit union might identify a large number of high net worth consumers moving to a city where home values are beginning to soar. With this intelligence, ABC might decide to open a new branch location in the city’s downtown area. By combining this knowledge with credit and demographic data, the lender can gain a direct link to potential borrowers living in town. ABC can examine this group and locate the types of individuals who match their acquisition strategy. Finally, the lender can quickly and efficiently execute a direct marketing campaign, and have confidence that it is targeting an audience rich with potential. Wrapping it All Up No one knows when the next “refi” boom will hit, or what changes affecting member levels and activity lie ahead. Therefore, improving current business practices with innovative solutions such as the ones presented in this article can be critical to any credit union’s success. Those who make little or no effort to maximize the effectiveness of firm-offer direct marketing initiatives are certain to be left out in the cold. The opportunity rests in leveraging the right technology with the right data. And oftentimes, it lies right at your fingertips.

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