VortexDNA predicts credit scores for decreased lending risk

Christchurch, NZ May 21, 2009. Using actual credit data, VortexDNA's algorithms have just been proven to be predictive of credit scores.

With global financial markets in turmoil, the survival of banks and other lending institutions relies more than ever on accurate risk predictions. Lenders can't afford for borrowers to default, but they can't afford not to lend money either.

By combining VortexDNA data with their current models, lenders may be able to better predict likelihood of slow payments or defaults, freeing up credit for low-risk borrowers. New borrowers, or borrowers in data-poor environments such as China, India and Brazil, can be more accurately assessed for lending risk.

Enter VortexDNA. By approaching the problem from a different direction, the company has created a predictive model with profound implications.

"As with every industry in which we work, our aim in the credit market is to minimise inefficiencies and make the system fairer and more accurate," says Branton Kenton-Dau, VortexDNA's CEO. "With better predictions, people receive fairer terms for their loans."

The credit trial comes close on the heels of VortexDNA's recent success in the insurance industry. The company is working with a number of leading U.S. auto insurers to improve underwriting ratios.

In the case of the credit trial, VortexDNA's proprietary system used personal attributes -- other than credit score -- to generate numeric profiles of each customer. They used a control group of 32,000 policies to determine which profiles correlated with which credit scores, and then checked their predictions against a second test group comprising an additional 32,000 policies.