Translating Credit Education into Better Credit Scores

Module by: Ed DeShields

Summary: Translating credit education into actionable credit score improvement is one of the toughest challenges for consumers and their lenders. The following research presents empirical data on a controlled group of consumers recently rejected for a home mortgage and how a well-designed credit education program helped restore their good credit reputation.

Credit education that focuses on tradeline strategies translate into significant short term improvements in the credit score. Calculating which tradelines mathematically produce the largest increases yield measurable results, almost immediately. The catch? Knowing exactly how the formula works.

A summary of a recent research program provided empirical evidence that can be used by consumers and credit professionals to improve the quality of consumer credit. There are many advantages associated with understanding and implementing methodologies that help borrowers improve their credit results; more origination volume, increased credit quality of a lender’s portfolio, fewer defaults, and increased competitiveness are among the most common advantages sought after.

Community Empower (CE) provides programs to provide credit-challenged home mortgage applicants an opportunity to improve their loan worthiness by participating in a formal credit improvement program. The CE program is a unique science that correlates specific credit behavior into consumer credit score values through a proprietary loan/credit quality matching science. Additionally, the program helps credit professionals manage a large portfolio of developable mortgage applicants without increased infrastructure costs.

As background, it should be noted that the CE program uses sophisticated computer models that translate specific credit repair actions into credit score improvements. Data is produced on each applicant case and is presented to the applicant in an easy-to-understand “action plan”. Applicants can interact with a secure internet modeling site, or with professional credit technicians via phone, email or internet chat sessions. Referring loan officers can readily track applicants and as they become credit worthy they are returned to the lending process.

Data Examination

The universe of consumers who entered the credit improvement program totaled 182 cases (N=182) referred by sixty-five (65) unique loan officers. Sixteen applicants were recovered as loan-ready during the evaluation period. The average applicant completed 76 days in the program and entered with a credit score of 550. The average loan officer enrolled two (2) applicants since the inception of the program. The most active loan officer enrolled eight (8) applicants.

Figure 1: The universe of consumers studied realized a significant credit score improvement in a relatively short period of time.

Consumer Score Improvement in Days

An impressive number of cases observed significant increases in their credit score. Sixty-four percent of the applicants or 116 observed cases, increased scores by 36 points raising scores from 547 to 583 (Fig 2).

Figure 2: Two-thirds of the study's participants raised their score significantly while some consumers continued to falter.

Most consumers make significant improvement with education

In our results, score improvement (Fig 3. SCIMPROV to DAYS in the table below) show a -.082 correlation coefficient indicating there is virtually no correlation in the amount of time to increase a credit score. This conclusion is logical because we have proven which type of credit behavior increases or decreases a score and that time affects some values and not others. For example, bankruptcy has a lasting affect that only time can cure once placed on the applicant’s history. Conversely, a past due credit entry is immediately cured simply by making a payment. Therefore, it is clear that CE users follow defined strategies outlined by their “Action Plans” that therefore cause immediate upward movement in the credit score. The act of simply identifying which credit entries require positive action is, in itself, a resolving factor in how to move credit scores. The CE program quickly identifies mathematically how this is to be managed.

Figure 3: Score improvements were signficant with the first 35 days.

Score Improvement in Days

Figure 4: It is significant to mention that we observed that time (in days) carried a very low correlation to whether applicant’s credit score increased even though it is widely known that time is an important scoring factor. A correlation coefficient of zero indicates no correlation in the amount of time to increase a credit score; that of 1 indicates a perfect correlation and that of -1 indicates a negative correlation.

Correlation to Time

Some applicants faltered

It is reasonable to assume not all applicants will complete the program. This is attributable to any number of factors including lack of motivation, changing household priorities or the realization that certain credit derogatory file notations, such as bankruptcy, take longer amounts of time to resolve and fall outside the immediate urgency of the applicant.

Our results show that approximately one-third of the applicants continued to falter. Consequently, their scores actually decreased vs. increased. If an applicant’s credit score worsened, the CE counselor attempted to engage the client. In most cases the applicant could not be contacted and an assumption was made that the applicant was not longer a program participant. Regardless of the outcome of any case CE continued to collect data on each case for the entire enrollment period.

The amount of decrease varied by case and by time. The mean score decrease of observed cases was 22.3 points, or about a 5% decrease in the applicant’s score. However, the SCORE Chart points out that the majority of cases where a reduction in score was realized was actually very small; 10 points or less (Fig 5).

Figure 5: Most decreases in the credit score were less than 10%.

Faltering particpants lose ground

In well designed systems, even short periods can yield good results

In our observed cases thus far, even a short period in the program produces significant results as indicated by the following table. For example, eighteen (18) cases in the program for exactly 30 days shows impressive credit improvement (Fig 6).

Figure 6: This table shows each case and its corresponding increase in credit score by length of time in the program (in days).

Credit Score Improvement in first 60 days

Debt-to-Income for Improving Score Cases

Applicants who improved their scores also improved their debt-to-income ratios. Improving credit scores, combined with improved debt-to-income ratios significantly raise the chances for applicants to become loan ready (Fig 7).

Figure 7: Debt to Income decreased for many as their credit scores improved. Better DI's mean't more participants would qualify for home mortgages. (Note: Negative values mean better Debt to Income ratios.)

Debt to Income Also improved

The top 2/3 of our applicant reduced their debt-to-income ratios by a mean of 7% during the same period.

As might be expected however, faltering applicants experienced increased debt-to-income ratios. The average DI increase for the bottom 1/3 of our applicants was 12% during the program period.

Future Performance

We are often asked to speculate on an expected range of improvement of credit scores and how long does it take to become credit worthy. The Chi-Square value for expected score increase over days shown is 68.9 points of score improvement over 200.4 days. Therefore, the predicted improvement in the credit score after 200 days nears 619. (Future Score = Entry Score (550) + Improvement (68.9) = 619) (Fig 8).

Figure 8: Most participants would qualify within 200 days if they maintain diligent action and had the proper credit information available to them.

Participants well on the way to loan qualification

While individual cases can vary greatly, it is reasonable to assume that applicants surviving the program for 200 days will produce A paper candidates for 2/3 of the applicants.

Conclusion

For years credit issuers have simply turned adverse-action borrowers away with little to no solution. Or, the borrower sought out so-called credit counselors who practiced credit improvement without themselves knowing which credit behavior caused movement in the credit score. This lack of information and empirical data has created an industry now viewed, for the most part, as preditory to the consumer. Tomorrow's credit education will require data analytics and new sciences to translate consumer behavior into increased credit score results for the consumer.

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This work is licensed by Ed DeShields under a Creative Commons Attribution License (CC-BY 2.0).

Last edited by Ed DeShields on Jun 16, 2006 11:09 am GMT-5.