5C’s of Credit Risk Analysis
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About the Client[spacer height=”10px”]
The client is a leading rare earth and coal mining company based out of the United States. The mining company is well known for supplying rare minerals and metals to businesses that produce rare-earth-based products that help fuel the global economy, enhance lifestyles, and improve productivity across sectors.
Business Challenge[spacer height=”10px”]
Given the impact of the global economic crisis, leading businesses are now rethinking their business strategy through credit risk modeling. With a similar intent, the mining company approached Quantzig looking to leverage credit risk analytics solutions to analyze risks, enhance cash flow, and reduce loss. To do so, the client needed to deploy a robust credit risk management framework to collate data from disparate sources across the organization and use those insights to predict payment defaults with the help of credit risk modeling. With the help of credit risk modeling, the client also wished to establish a global center of excellence for credit risk analysis, to promote the adoption of credit risk modeling across all product categories and business units.
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Solution Offered[spacer height=”10px”]
The credit risk modeling experts at Quanztig helped the client deploy a holistic credit risk management framework by implementing the best practices to distill actionable insights for effective credit risk management. Our approach to credit risk modeling was comprehensive and it not only helped the client assess the creditworthiness of its customers but also enabled them to analyze reasons for payment default.
Through credit risk modeling we also helped the client devise a collaborative model to unify data in functional silos across the organization, which in turn, played a vital role in enhancing the accuracy of default analysis, improving forecasting & credit risk management.
Quantzig’s credit risk modeling solutions helped the client utilize data from both internal and external sources including exchange rates, commodity rates, and sales orders. The use of advanced machine learning algorithms that leveraged historical data to generate forecasts for credit performance and accounts receivables also helped them to assess the credit risk score for specific categories of users.
Credit risk modeling also helped the client to:
- Gain insights into risk scores, credit strategies and the cost of capital
- Customize payment terms and modify credit limits to reduce risk exposure
- Build unique plans based on the credit risk profile of various categories and customers
- Optimize cash flows using debt factoring as a tool
- Standardize payment terms using customer credit risk profiles
- Determine factors contributing to defaulting and risk across clients, products and regions[spacer height=”10px”]
Wonder how credit risk modeling can help your business? Request a FREE demo to get a glimpse of our capabilities and learn what we can do for you.
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