Enhancing credit scoring with alternative data

CFPB Insights On Alternative Data Use In Credit Scoring

The growing utilization of alternative data in credit decisions and scoring models continues to attract the attention of regulators. Although clear and practical guidance from regulators remains elusive, regulator pronouncements provide some clues and takeaways for market participants. Recently, for example, the Consumer Financial Protection Bureau issued a request for information (RFI) regardi...

Enhancing credit scoring model performance by a hybrid scoring matrix

Competition of the consumer credit market in Taiwan has become severe recently. Therefore, most financial institutions actively develop credit scoring models based on assessments of the credit approval of new customers and the credit risk management of existing customers. This study uses a genetic algorithm for feature selection and decision trees for customer segmentation. Moreover, it utilize...

Consumer credit scoring models with limited data

In this paper we design the neural network consumer credit scoring models for financial institutions where data usually used in previous research are not available. We use extensive primarily accounting data set on transactions and account balances of clients available in each financial institution. As many of these numerous variables are correlated and have very questionable information conten...

Credit Scoring with Social Network Data

Credit Scoring and Data Mining

Credit scoring is the use of predictive modelling techniques to support decision making in lending. It is a field of immense practical value that also supports a modest amount of academic research. Interestingly, the academic research tends not to be put into practice. This is not a result of insularity and arrogance on the part of the practitioners, but rather, of the practitioners having a be...