Loan Analytics

There are many opportunities from a loan lead to a fully repaid loan where data may be analyzed to provide decisional insight. For example, better understanding of the low likelihood of a lead to convert can help save wasted origination costs. Insight at the approval stage into a loan's default propensity enables alteration of loan pricing, terms or additional collateral requirements. Data aggregation and normalization is the basis of risk modeling which help build the decision support tools which in turn help take proactive action that help avoid unfortunate events or at least soften their blow.

CoreLogic offers analytics products for the Indian retail loan business. Our pedigree in financial services analytics are honed on the back of the industry leading expertise of mortgage analytics specialists like CoreLogic and LoanPerformance within the stable of our US parent First American.

The first product has been specially created for Indian mortgage lenders is the NPA Risk Calculator TM that helps determine risk propensity of home loans through a default propensity score. This score is intended to be an objective aid in the lender's underwriting decision. The first time this score can be derived is at the time of new loan application processing. The knowledge base of the CoreLogic, team in India that works on US mortgage analytics products coupled with Indian loan data and local market domain expertise was leveraged to create this product.

The NPA Risk Calculator TM provides a proportional score i.e. higher the score higher the risk which is am useful aid to:

Loan Underwriting
  • Early stage go/no-go decisions for efficient use of underwriting resources
  • Identification of risky loans upfront for more due diligence
  • Identifying the levers for negotiation and placing conditionalities
Portfolio grooming
  • Periodic assessment of risk propensity of existing loans to decide on proactive measures. History performance data of existing loans will be required.
  • Structuring of portfolio by devising a desirable risk score /range for loans in that group
  • Simulating loan pools and assess price to provide preparedness to potential portfolio churn
Product Development
  • Devising what-if scenarios and assessing impact of parameters like LoanAge (term), IIR (Installment to Income Ratio), LCR (Loan to Cost Ratio), Loan type (Fixed, Variable) etc on default propensity
Setting of loss reserves
  • The probabilities generated by the calculator maybe used in reserve setting against estimation of potential portfolio losses in a given year.