Littman’s Jewelers (Elangy Corporation)

Situation: A premier Jewelry Company having over 100 stores across the country.

Critical Issues: Business losses due to low approval rate and high delinquencies. Excessive amounts of score overrides by credit managers and new locations in certain areas resulting in failure of the existing model’s performance.

Analysis: CBD analysts realized while re-validating their existing model that Littman’s were rejecting an inordinate amount of applicants below the age of 26 due to lack of credit history even though they comprised of over 30% of the total applicants. We recommended that an additional scoring model needed to be developed and deployed for young applicants while the existing scoring model needed to be re-aligned and updated. It was also noticed that margin of profit on some of the items was relatively high and hence posed a lesser risk as long as part of their cost was covered through a structured down payment.

Implemented: CBD developed and implemented a new credit-scoring model for young applicants and re-aligned their existing model to serve the rest of the applicant population. CBD also created a structured down-payment schedule and strategies (deposit matrix) that took into account margin of profits and the applicant score. This allowed Littman’s to accept every applicant as long as they fulfilled the basic requirements. Along with the scoring models, Performance Projection tables related to each model were provided for the management to be able to set cut-offs based on their risk ‘appetite’. They were also provided with management criteria based on risk (Accept/Reject cut-offs) that resulted in faster turn around time for decisions. Additionally they were provided Term length strategies based on score, demographic group, disposable income, down payment, etc.

Result: Littman’s significantly increased approval rate and their cash flow. Within the first 18 months, they were able to increase their approval rate by 10% while reducing their bad debt expense by $1.4 million. This amounted to a 25 fold ROI (Return on Investment). These figures continued to improve over the years and resulted in a much healthier bottom-line for the company. Uniformity of lending decisions across the portfolio also resulted in decisions being made in a consistent and uniform manner, thereby adhering to the strict lending regulations.

Current Situation:

Littman’s recovered their investment cost within the first six months of implementing our solutions.

Shell Canada Products

Situation: An international oil conglomerate with consumer products.

Critical Issues: The Company was seeking to automate its lending process, increase approval rates and reduce losses due to bankruptcies and write-offs. They were especially concerned with accounts with credit limits below $5,000. They were also seeking to monitor their existing portfolio more intelligently and productively.

Critical Issues: The Company was seeking to automate its lending process, increase approval rates and reduce losses due to bankruptcies and write-offs. They were especially concerned with accounts with credit limits below $5,000. They were also seeking to monitor their existing portfolio more intelligently and productively.

Analysis: CBD analysts observed the characteristics of the applicants to estimate the risk in approving credit limits and to arrive an appropriate credit adjudication system. The existing portfolio was not being mined for future trends and behavioral analysis.

Implemented: CBD developed a credit-scoring model for consumer lending and a behavioral scoring model for their existing and future portfolio. Shell Canada was also provided with accept/decline cut-off scores in accordance with the objective of balancing predicted risk vs. predicted approval rate, low point declines based on variables alone, automatic declines bases on policy, override issues, setting of credit limits based upon score and expected usage, monitoring and tracking of applicants data.

Result: Because of the Behavioral Scoring System, Shell Canada was able to increase limits of creditworthy accounts, decrease limits of those indicating a higher degree of risk, making credit line and authorization decisions uniformly across the portfolio, improving effectiveness and efficiency of the collection efforts, facilitating marketing and automating the authorization decisions.

Current Situation: Shell Canada is very happy with the two products. They have streamlined their adjudication and credit monitoring processes without the corresponding increase in risk.


Operation: A furniture retail operation with 9 stores based out of Memphis TN

In Michael Faber words:

“Creative Business Decisions has helped Royal Furniture in automating the lending process that has resulted in increased risk management, decreased losses from write-offs and the streamlining of lending decisions. Our two scorecards (New Applications and Add-On Applications) have performed exceptionally well and we have been able to achieve significant savings from them. Over a period of two years we have gained a great deal of confidence in the automated decisions generated by the scorecards and we are very happy with what Creative Business Decisions has done for us. The scorecards have increased our lending profitability while simultaneously decreasing our risk profile as collection percentages on outstanding balances have improved dramatically since we implemented the scorecards in 2006”.

-Michael Faber, VP

Name withheld on clients request

Situation: A prominent lending institution.

Critical Issues: Rising losses through write-offs and bankruptcies. Inability to grow portfolio due to associated risk. High write-off provision. Inability to collect from delinquent accounts effectively.

Analysis: After data analysis and model re-validation CBD analysts saw the following shortcomings in the existing model – (i) It was not accounting for a region that had a high percentage of delinquencies (ii) It did not have certain variables that would have increased the model’s (and thereby the portfolio’s) performance and (iii) It was not properly aligned. The bank also needed our product called “The Best Bureau Choice” to be able to determine the right bureau report pulling according to region. And finally they also needed a Collection Model to streamline and improve their collection process and proceeds.

Implemented: A new empirical credit-scoring model developed and deployed. A new Management Criteria put in place to adhere to a standard credit policy. A Zip-code preference table implemented so that the bank could pull appropriate credit bureau reports by region and a Collection model was also developed and deployed.

Result: The bank significantly increased approval rates, portfolio and cash flow while lowering their bad debts and delinquencies. They admitted that our models have helped them decrease charge-offs by more than 40%. This has allowed them to keep a much smaller write-off and bad-debt provision. Their collection has also improved significantly.

Current Situation: This is what the Credit Manager wrote in his testimonial to us - “We feel that your scorecard is providing us with an excellent tool in managing the risk profile of our loan portfolio. We wish to express our appreciation for a job well done”.