Why and How to Upgrade the Credit-Review Process and Frequency of Reviews.
As originally published in the Credit Research Foundation’s publication, Perspective by CRF (Q1 2021). (link)
We are in a period of unprecedented economic disruption, which can quickly and adversely affect customer creditworthiness. Thus, it is imperative that Credit functions review and calibrate their processes and harness technology to address rising risk levels.
Establishing an effective credit assessment policy and process in the commercial B2B environment requires a strategic approach, effective guardrails with company-wide support, and enabling technology. Companies that do not apply a rigorous, structured approach and fail to monitor, review and update customer credit risk profiles more frequently, run the risk of increasing risk exposure, carrying aged and overdue receivables, ultimately leading to increased bad debt reserves and write-offs.Meanwhile, organizations that go beyond static, defined periodic review cycles and embrace an approach of continuous monitoring of dynamic credit management information, performing frequent ongoing credit reviews linked to customer value and risk, will be better positioned for successfully navigating the current economic climate and minimizing credit defaults and potential bad debt write-offs.
TO REVIEW
YOUR CREDIT PROCESS.
Addressing New and Existing Customers
The effectiveness of the credit review process begins at the very start, with the vetting of new customers prior to granting any unrestricted payment terms (e.g., net 30 days) and credit limit values. The review process should ensure an approval workflow that mitigates risk of Phishing attacks, ensures standard credit limits across the portfolio parent/child relationships, and ensures a robust credit limit determination that utilizes credit scores, financial metrics, referrals and payment behavior. Equally important is the ongoing monitoring and management of the existing customer base. Credit functions must have insight into the up-to-date risk stratification of their entire AR portfolio, so they can partner with Sales and Finance teams to help support business objectives through the following actions:
- Maximizing revenue by targeting sales growth with the most financially sound and creditworthy customers.
- Mitigating credit and risk exposure through proactive and strategic credit risk evaluation and ongoing monitoring through automated scorecard evaluation and workflow approvals including predictive analytics assessing credit score and payment behavior trends to allow visibility to potential customer liquidity issues.
- Incorporating balanced scorecards by combining external credit data with internal payment performance and tracked customer behaviors (i.e., broken payment promises, dispute volumes, credit, and order hold volumes, etc.).
- Establishing accurate bad debt reserves that incorporate specific amounts for high-risk customers and accurate general reserves based on defined aging bucket percentages based on External Auditor guidelines and historical loss percentages across aging buckets.
- Minimizing bad debt write-offs through targeted and timely credit sanctions and risk mitigation actions.
- As organizations navigate the current economic environment, having a well-defined credit model and assessment approach, along with more frequent credit reviews, is paramount for making sound decisions and managing overall AR portfolio risk effectively.
- Implementing a rolling customer credit review and assessment of portfolio risk, including (credit limit utilization reporting, reporting of customers without ERP limits assigned, accuracy and update mechanism for adjusting historical loss rates).
Onboarding New Customers
The best way to safeguard the AR portfolio is by making sound credit decisions at the start, when onboarding a new customer, asking critical questions such as – what payment terms should we provide? And how much credit do we extend to the new customer? To answer these questions, credit managers must have robust and current data about customers’ financial health, and ultimately their ability to pay for goods and services rendered, as well as expected customer revenue generation.
The new-customer review process and modeling should include the following elements:
- External credit bureau and financial scoring information.
- Customer sales and demand forecasts (monthly, quarterly, and/or annual projections)
- Audited customer financials where required and available
- Trade and bank references, where required.
Once the scorecards are established and new customers are assigned appropriate risk grades, credit limits and payment terms, the credit function is in a position to effectively manage the portfolio through ongoing automated credit monitoring and frequent reviews of existing customers.
Ongoing Portfolio Monitoring
Because the economic environment is putting greater stress on companies’ credit standing, it may not be enough to follow the usual annual, semi-annual, quarterly, or even monthly credit review cadence. With the right technology and scoring methodology, companies can establish a near real-time monitoring process of customers’ credit profiles with the intent of predicting financial duress situations. Most ERP platforms and available 3rd party solutions can provide integration with credit monitoring service providers that allow for the continuous monitoring and updating of credit risk data. Through daily updates from customer credit providers, coupled with internal payment performance analysis, organizations can be better positioned to detect and anticipate potential defaults.
Scanning for potential credit issues through visibility into critical information and modeling must incorporate a daily refresh of external credit bureau risk data, as well as ongoing surveillance of internal customer historical payment performance information. With a proactive and agile credit monitoring process, the credit function can apply an exception-based approach, so it focuses on credit risk mitigation actions for customers demonstrating increased risk and likelihood for payment default.
This additional data must be mapped to a set of actions/sanctions, decisions, and protocols for managing potential risk exposure cases; examples of sanctions to consider include:
- Credit holds at the account and/or order level
- Payment term restrictions (e.g., advance payment requirements)
- Deposit requirements
- Payment workout agreements
- Formal note guarantees with company owners/principals.
The various sanctions available to the credit function should be clearly documented within the credit policy and well understood by the sales and commercial teams. This will help to avoid any miscommunication with the customer regarding the credit policy, risk exposure and AR delinquency. The more the sales organization is aware of, and in agreement with, the credit policy, the lesser the chance of internal contention regarding the use of formal credit sanctions.
Leveraging Leading Edge Technologies
Companies looking to upgrade their credit management processes and approach can harness available leading-edge technologies that employ AI, Machine Learning, and automation capabilities to streamline and improve the credit management functions and ability to manage customer risk while supporting and even contributing to corporate revenue and growth objectives.
Core features to look for with solutions in the marketplace include:
- Online credit application workflow with integration into ERP source system for customer onboarding.
- Configurable and customer scorecards utilizing external credit bureau data elements and analytic data trends.
- Defined Levels of Authority (LOA) to expedite approval workflows and safeguards against phishing attacks.
- Predictive modeling using AI and Machine Learning to proactively identify potential high-risk accounts.
- Dynamic modeling to automate and streamline ongoing periodic credit reviews for all existing customers.
- Risk-based collection strategies by linking treatment approach to credit risk profiles.
- Managing credit and order hold mechanism with integration into source order processing and billing systems.
To further optimize the existing review process in today’s climate, firms should also consider lowering thresholds that trigger reviews or alerts. The old parameters in this fluid and sporadic environment might not trigger a review early enough. Also, firms may also want to segment their customer base by industries and customer hierarchy and rank them by their different degrees impacted by the current economic conditions.