Better control of risk exposure

Drawing on high-quality customer data, an accurate credit scoring allows banks, credit unions and other lenders to control their risk exposure through selective credit approval.

The broader customer data gets analyzed, the more accurate the risk assessment can be. On one hand, you can increase the share of loans to customers for whom the risk is overestimated as a result of using traditional scoring methods. On the other hand, you can build safer credit portfolios, better estimating the risk of customer bankruptcy.

Business advantages

  • More accurate scoring
  • Increased sales of less risky loans
  • Safer loan portfolio

Our approach

As this is a data-driven solution, our data scientists analyze your data and evaluate its business potential, then create a solution that uses the potential best. We take a closer look at demographic and financial situation of the client, their past transactions, their loan history and related products, plus publicly available data from the internet and social media.

We use all of that to create the most accurate model that can provide a financial health score and predict how likely the client is to miss an installment payment or adhere to their financial obligations in general.

We can provide you with either a lightweight solution dedicated to solve your particular pain point, or a full one, encompassing other useful features.

See our products that leverage machine learning for credit scoring:

Loan Origination

Comarch Loan Origination enables more efficient control of credit risk and allows for a significant reduction of time needed to grant a loan. The system automates the work of client advisors managing the credit-granting process at its every stage.