SPSS Analytics Partner | Case Study – Adira Finance

Case Study – Adira Finance

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Solution Components

  • IBM SPSS Modeler
  • IBM Decision Center
  • IBM Decision Server
  • IBM Operational Decision Manager

“By significantly increasing the speed and accuracy with which it determines each customer’s credit worthiness, Adira Finance can help ensure it extends loans to the right people with the right terms.”

Pramono Pranoto, Head of Analytics

Adira Finance

Predictive analytics used to more effectively manage credit risk and tailor loan offers



PT Adira Dinamika Multi Finance Tbk (Adira Finance) is a leading automotive financing company in Indonesia that provides car and motorcycle financing services to four million active customers. Based in Jakarta, the company employs more than 38,000 people at approximately 200 branches, 370 representative offices and 80 collecting units nationwide.


Business need

Automotive financing company PT Adira Dinamika Multi Finance Tbk (Adira Finance) sought a way to mine data on four million customers for intelligence it could use to optimize risk management across the organization.



The company deployed a credit lifecycle management solution that uses predictive analytics to identify customer groups with the highest likelihood of defaulting on loans and capitalizes on those insights to rapidly generate individualized credit scores and risk profiles. Applying advanced modeling capabilities, the solution detects distinct trends and patterns in customer attributes and behaviors, such as income levels and payment histories among people purchasing motorcycles, and correlates them with risk levels.



Using the IBM predictive analytics solution, each Adira Finance loan officer can now manage up to 700 customer accounts, more than tripling the 200 accounts that each officer previously handled when reliant on manual processes. In addition, with increased visibility into customers’ risk profiles, collections personnel can prioritize collection efforts and reduce the number of nonperforming loans. Further, because the solution automatically generates credit scores and risk profiles, loan officers can more consistently evaluate applicants and improve credit offers so that the company can extend the right terms to each customer.

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