SPSS Business Solutions | Risk Management

Using Credit Scoring to Minimize Risk

Each year, organizations lose billions of dollars in revenue due to customers who default on bank loans, telephone bills, credit cards payment, and a variety of other types of accounts.

Predictive analytics solutions from SPSS enable organizations in a wide range of industries to determine, prior to extending credit, which customers are likely to be a good credit risk and which are not. By using predictive analytics, organizations gain real-time answers to the question of whether to extend credit and, if so, how best to minimize the risk level and maximize the potential return to the organization.

SPSS solutions enable your organization to:

Analyze a virtually unlimited number of cases
Score individuals based on profiles using relevant characteristics
Incorporate data from standard databases with text, Web, and survey data to enhance scoring accuracy
Determine if, or at what levels, credit should be extended
Deliver scores and recommended actions to take, in real time if needed, to decision makers and decision-dependent systems

As a result, your organization can:

Reduce loses due to loan or payment defaults
Decrease late payments
Identify optimal billing plans for customers who are higher risk, reducing the risk of default
Streamline the credit approval process for customers less likely to default, improving customer satisfaction rates

When you’re able to identify credit risk in advance, your organization is better positioned to make intelligent credit-related decisions, protecting its bottom line.

Learn more about how predictive analytics helps organization manage credit risk.

Find out how organizations in the telecommunications industry benefit from SPSS credit scoring solutions.

Learn more about SPSS data mining and statistical technologies.

You can also see how customers, such as Financiera Familiar, are using credit scoring solutions from SPSS to minimize their risk.