Installing effective credit limits to minimize the impact on customer service and credit risk in a Belgian industrial
By reviewing their credit limits and the business rules behind the process of blocking & unblocking orders, this listed Belgian industrial wanted to install a more agile management of credit limits, and a more efficient credit management.
Improving credit limit management to prevent blocked orders
Three years ago, the company created local Credit & Collection departments in each country in which it operates. The purpose was to be close to the business. Previously, this role was performed centrally under the leadership of the Accounting team. As the focus on working capital became stronger, the Credit & Collections teams started to operate under the umbrella of the Finance team (treasury). During the process improvement phase and the implementation of SAP S4HANA, credit limits needed to be reviewed. To define more accurate credit limits, the definition process needed an update.
The trouble with blocked orders
Though the process to release orders was standardized, it was not running well. Credit controllers lost valuable time checking and releasing blocked orders. They all had ‘their own way of working’, deciding how and when to release in function of their own experience and insights. To release orders, some credit controllers allowed a stretch of the credit limit, instead of a review. But this ‘stretch’ was ad hoc and different for every credit controller. Moreover, it was not in compliance with the credit policy.
Credit & Collection departments were struggling with a cumbersome workload, entailing a daily routine of reviewing and releasing orders. They found themselves with too little time to handle all dunning actions in Getpaid or to review credit limits and organize facetime with customers.
Customer service was also impacted as they were often confronted with blocked orders, while trying to meet the shipping deadlines and sales targets.
The process was supported with Way of Working (WoW) documents to ensure clarity and consistency among credit controllers, enabling uniform procedures across the company. As seen in previous projects, effective interaction between Credit & Collection and stakeholders such as Sales, Customer Service, and ICT proved essential.
How data-driven credit limits reduce risk and boost efficiency
Recalculating credit limits
‘TriFinance set the credit limits in such a way that, without increasing the exposure and non-payment risk, a minimal number of orders had to be put on hold,’ TriFinance project consultant Benjamin Celis says. ‘Besides using historical data, we tried to calculate the credit limit that was needed customer by customer. Cooperating with Sales, we also took seasonal effects and the sales growth-path into consideration. Then we compared the credit limit needed with the credit limit that was presented by our provider of financial information, Bureau van Dijk. Depending on the outcome, additional financial assessments were performed in accordance with the company’s Credit Policy.’
All credit limits were then approved, according to the company’s Delegation of Authority, and uploaded in the ERP system with a template file.
Standardizing Credit control with smart business rules
Benjamin Celis also reviewed the business rules behind the automatic blocking. Instead of evaluating the credit limit with all open orders plus the AR, he looked at the real risk the company was running. As open orders which have not yet been released do not represent a risk, these were excluded from the new business rules.
‘I ensured that the process was supported with Way of Working (WoW)-documents) and that it was understood by the different credit controllers,’ Benjamin Celis says, ‘so that uniform procedures were used throughout the company. As in many projects before, ‘I realized again how important the interaction is between Credit & Collection and all the other different stakeholders, like Sales, Customer service or ICT.’
