In today’s rapidly changing marketplace, it is imperative to know your counterparty and to effectively evaluate counterparty credit quality in order to manage existing credit exposures. This enables companies to properly evaluate exposures inherent in potential transactions.
It is critical to evaluate a counterparty on the relevant criteria specifically selected and weighted for its particular industry. A rules-based credit review process ensures consistent policies and consistent results while employing multiple customised scoring models.
Credit managers must consider both qualitative and quantitative elements of their customers and counterparties in order to set policy-driven credit limits.
Brady Credit Risk’s Scoring module utilises decision-tree architecture which allows credit departments to independently establish effective, consistent scoring methodology in order to calculate policy-driven credit limits. The Scoring module includes a standard modifiable calculation logic to meet the ever-changing portfolio scoring requirements.
Request a Demo
Scoring Dictionary and Logic
The Scoring module comes preloaded with a comprehensive dictionary of questions, framed answers, and financial ratios that allows for the creation of a custom portfolio decision tree. Credit departments can independently define additional questions, answers, and proprietary financial ratios known only to the organisation. The decision tree path allows results to be scored against a credit policy, a peer group, or a combination of both.
The Scoring module allows template modifications to be implemented, tracked and re-scored against both existing and historical portfolio data. The system tracks variances between the current and previous scoring models, and provides a summary of changes by relevant area.
Increased market share and risk diversification
Consistent, timely credit reviews allow companies to evaluate new or existing customers and counterparties when appropriate. Removing potentially subjective credit elements from the credit decision process assures management that the company is complying with corporate credit policies and/or regulatory governances.
Eliminating separate and disconnected spreadsheet models allows for changes to be entered at the credit scoring control-centre. Database links reduce the re-keying of static and real-time data elements, allowing for increased data precision. The Workflow module interfaces with The Scoring module, resulting in electronic monitoring and measurement of user-defined key exception indicators. This allows companies to concentrate resources effectively on new and higher risk counterparty credit decisions.
Predictive default monitoring
The Scoring module connects seamlessly to online, third party, financial and capital market data as well as predictive default models in an effort to provide early warning indicators. Whether it is a company name or product specific, it allows the user to consider specific trends and analysis for the credit limit calculation.