This article is written and published by S&P Global Market Intelligence, a division independent from S&P Global Ratings. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit scores from the credit ratings issued by S&P Global Ratings.

The need to automate credit risk workflows is an ever-present issue for Credit and Risk Management professionals that has only intensified with the ongoing economic uncertainty sparked by COVID-19, rising fuel prices, and mounting inflation. Indeed, in last year's survey "The Future of Risk Management Digitization in Credit Risk Management”^[1] amongst 200 respondents, 70% confirmed that the pandemic had accelerated their digitization plans. With the increasing pressure placed on many businesses' profit margins, automation can provide an opportunity to cut costs and improve efficiency.   

Defining your credit risk management workflow and identifying supporting data and tools can help to facilitate the automation of significant parts of the process. Automating critical components of credit assessment can enhance your customer experience, reduce the number of potential errors, and enable further standardization of practices across your organization while naturally improving the information flow.

For corporations globally, identifying which parts of their credit workflow can be fully or partially automated and implementing the required changes can be a significant challenge given the inconsistent information received, coverage constraints, especially for small- and medium-sized enterprises, the complexity of credit scoring models and a host of other hurdles. Therefore, it is essential to have robust credit & liquidity models and tools to ingest and standardize customer information in an automated fashion. S&P Global Market Intelligence can help support your enterprise risk management with our Credit Analytics models available via API and data feed by:

• Using pre-generated credit scores and relative benchmarks to quickly and effectively screen companies for new business origination and only undertake in-depth credit assessment when necessary.^[2]   
• Utilizing an independent global credit scoring model that instantly imputes missing financials in conjunction with proprietary financials for credit risk analysis, saving model development time.
• Using financial spreading tools via software as a service to automatically extract and standardize financials from customer documents.
• Incorporating fundamental and daily market-based model outputs that can be used to trigger alerts of portfolio deterioration and monitor customer health.
• Assessing short-term liquidity risk with Payment Behaviour data and models which, alongside creditworthiness, should be automatically factored into the final credit limit.

For more information on how to easily automate your credit risk workflows, visit Credit Analytics Enterprise Solutions.