FIS Moderne Banking-Plattform
Bringen Sie Ihre Bank mit einer modernen Core-Plattform voran.
Six reasons why your credit risk is not what you think
April 12, 2017
With the receivables portfolio being the largest asset on many corporations’ balance sheets, credit risk is one of the most important risks to be managed. The difficulty for many credit and collections teams, however, is that before trying to monitor and mitigate their credit risk, they often struggle to identify their level of risk in the first place.
- Decentralized credit and collections organizations, or regional shared service centers that use different systems, find it very difficult to set credit limits and to measure credit risk for customers with whom they work in more than one location.
- Companies that engage in M&A acquire credit risk to both new and familiar customers. In many cases, it can take a long time to integrate this data and present a global view of credit risk to customers across the enterprise, a problem that is exacerbated every time a new acquisition is made.
- As companies expand their business into new, less familiar territories, particularly emerging markets, external credit agency information may be more limited or not exist at all. This means that credit teams need to establish credit limits based on a combination of external and internal data and insights, which can be more time-consuming and lack rigor if it is not done in a systematic way. Increased political risk is also adding to the complexity of these calculations.
- Companies should be looking at credit risk and collections risk separately. In this paradigm, credit risk management involves evaluating the financial viability of a customer or prospective customer, and projecting the organization’s future financial stability. Leveraging external data can play a key role in evaluating new customers for credit or existing customers for credit line adjustments. Collections risk evaluates the customers’ ability to pay and involves the risk inherent in the invoices that are already out the door. By leveraging internal data within predictive analytics or statistical models that look at a company’s own experiences with each customer to help predict future delinquencies, companies can accelerate collections by identifying high risk customers and move those customers to a high touch “call” collections strategies.
- Few companies (28 percent, according to the 2017 FIS Credit and Collections Market Study) monitor dispute cycle time. However, unresolved disputes create a cloud of uncertainty around credit risk calculations. In the worst cases, customers are prevented from placing new orders while credit limits are shown as utilized; at the very least, credit managers lack a clear view of risk to these customers.
- Automated cash allocation rates vary considerably across organizations, with around a third of companies reporting hit rates of 50 percent or below. As a result, risk limits are incorrectly shown as utilized, which not only hampers new business, but also distracts credit teams from genuine credit risk concerns. Currently, less than half (42 percent) measure performance in cash allocation.
There is no single response to these diverse challenges, but it is essential to create an accurate picture of credit risk before seeking to monitor, refine and mitigate these risks. Implementing a consistent credit and collections management tool across the enterprise is a logical place to start, creating a single source of truth across different collections teams, including a global view of risk for each customer. Just as importantly, working towards a culture of performance measurement and improvement across the metrics that impact on credit risk can be a valuable means of identifying priorities and increasing visibility and confidence in credit risk.