MaxDecisions Delivers 4% Direct Mail Response RateMaxDecisions, Inc. Delivers $40 Cost Per Funded Loan to Sub-Prime Lender in The United States

Direct Mail Marketing
MaxDecisions, Inc. delivers an industry first 4% response rate in subprime consumer lending direct mail channel.

MaxDecisions, Inc. announces that it has achieved unparalleled success with its latest generation of Direct Mail modeling techniques. In July 2017, MaxDecisions, Inc. engaged with a mid-size sub-prime lender to expand the lender’s direct marketing channel. MaxDecisions took over the campaign and worked with the lender’s management team and credit bureau to quickly deployed a direct mail campaign with over 250,000 pieces across 10 states. The result of the campaign produced close to 10,000 responders and over 2,500 loans.

challenge

When MaxDecisions, Inc. took over this portfolio. There had already been four campaigns deployed from Sept 2016 to April 2017. These previous campaigns varied from 0.2% to 0.9% response rate (netted anywhere from 200 to 500 loans). The wide range of swings cause the lenders to under and over staff constantly and created many cash drag issues with their investors. The unpredictability of response rates and the quality of the responders caused further issues with lender’s underwriting staff and default rates.

In May 2017, MaxDecisions Inc. was named as the new analytics firm to help calibrate this lender’s marketing channel. We took our best practices and implemented the latest generation of Direct Mail Response and Risk Model and quickly launched another quarter million piece marketing campaign in June 2017. The result of this campaign produced 10X more loans than any of the previous campaign (normalized over campaign volume):

  • Attention to details:

    One of the biggest issues with the previous analytics shop was attention to details. We found a number of critical issues which could have been easily avoided if proper Quality Control was put into the place. For example, one of the previous campaigns contained over 70% of the population without a credit score. This could have been easily avoided if a simple summary statistics chart were to produced before and after receiving the pre-screen file from credit bureaus.

  • Understanding of the product and industry:

    There are other common sense mistakes uncovered by MaxDecisions, Inc. from previous campaigns which could have been easily avoided if the previous team had a good understanding of the subprime market and it’s audience. For example, in the last campaign (April 2017), 100,000 records were sent out for mailing and it’s population average Vantage score was 680 and the Estimated Household Income was $150k. These numbers in our opinion are typical customers for LendingClub and Prosper (36% and below) personal installment loans. This audience is not suited for subprime loans, whatever response the lender did receive from this ill-posed campaign were all adversely selected responders. The result is a 20 basis point response rate with high first payment defaults.

  • Custom models win every time:

    MaxDecisions quickly developed a set of risk and response models catering to the subprime population for this lender. We leveraged our experience and our rigorous analytic capabilities to deliver unprecedented results for our clients. Most often, prospects with higher FICO or Vantage scores perform well, however when customers score below 600 FICO or Vantage, these industry scores tend to deteriorate in terms of predictability of response and default. MaxDecisions, Inc. unique solution is to leverage industry scores were needed and always produce custom models for our clients to achieve the best results.

solution

MaxDecisions, Inc. leveraged decades of analytical skill set and years of industry experience to produce a comprehensive Direct Mail strategy. From the design of the letters to the consumers to list selection from credit bureaus to the application of custom models. Every step is checked by multiple strategists and data scientists. Because of our experience in the online finance industry, we can quickly spot weak spots and suggest improvements immediately.

We are now delivering our third campaign for this lender with the 3rd generation of risk and response model specifically designed for our client to further increase the resposne rate and decrease default rates. We and our client believe that getting the optimal results require continuous monitoring and recalibrating our custom models.

results

The June 2017 campaign has settled with over 10,000 responders and 2,500 loans. We are continuously calibrating our selection strategy and our predictive risk and response models to further refine responders and increase conversion rates.

By the numbers, the effort:

  • Increased response rate from 0.2% to 4% (20x increase in response rate)
  • Decreased cost per funded loan dramatically to sub $40 per funded loan
  • Response Rate (%)
  • Loan Count