Navigating the landscape of credit risk remains a significant challenge for businesses across industries. The unpredictability of default scenarios and potential financial losses pose a considerable threat, hindering the stability and growth of enterprises. Effective credit risk management demands proactive measures to mitigate vulnerabilities.
This article aims to comprehensively explore credit risk mitigation strategies. It provides insights into challenges faced by finance professionals and presents best practices to empower teams in making informed credit decisions, mitigating risks, and fostering strong customer relationships. By gaining a deeper understanding of this crucial financial aspect, teams can navigate lending operations confidently, fostering sustainable growth.
Before delving into credit risk mitigation, it’s crucial to grasp the essence of credit management control. This systematic approach regulates a company’s credit policies and practices, aiming to minimize credit risk, optimize cash flow, and ensure timely customer payments while maintaining financial stability.
A credit management plan operates as the company’s proactive strategy against late payments or defaults, encompassing a continuous process involving risk identification, evaluation, and strategic measures to mitigate potential losses.
By implementing a well-defined credit management plan, businesses can safeguard their cash flow, enhance performance, and minimize the impact of defaults on their overall operations. Notably, credit risk mitigation serves as a fundamental component of credit management control, empowering organizations to establish more effective credit controls.
Credit risk mitigation is a process by which a company reduces its exposure to credit risks. It involves assessing creditworthiness, monitoring credit profiles, and managing risks to prevent revenue loss, ensuring a healthy balance sheet and cash flows.
Before implementing credit risk mitigation strategies, organizations should consider critical aspects that significantly impact their approach. These include:
Monitoring portfolio risk is pivotal for an organization’s success and risk mitigation. This approach involves identifying, assessing, measuring, and managing risks within the customer portfolio, ensuring enhanced business value delivery and risk mitigation.
Continuous monitoring of the receivables performance metrics such as days sales outstanding (DSO), and average days delinquent gives companies a bird’s eye view of their performance and operational efficiency. These metrics provide actionable data for companies to focus on and take corrective measures proactively.
Credit teams are often caught up in routine tasks that can easily be automated. These include processes such as credit application process, correspondence etc. This restricts the team from investing their time and efforts in higher-value tasks such as working with sales to improve customer experience and conducting analysis to make better credit decisions.
Technology plays a vital role in building an agile credit function. By leveraging digitalization in the credit management process, organizations can undergo major transformation empowering credit teams to create strategic value in the office of the CFO.
Let’s look at the significant challenges faced by credit teams while evaluating credit risk for their customers.
Credit risk monitoring techniques involve a lot of communication between ERPs, spreadsheets, and credit reports. As a result of the manual effort involved, credit teams lack end-to-end visibility on their portfolio risk. This means that if the credit risk fluctuates, they won’t be able to track that change in real-time.
Imagine the risk manual credit management imposes on the organization’s bottom line. It is recommended that credit teams evaluate their customers on a real-time basis with automated credit management systems.
Whenever an order gets blocked due to insufficient credit balance, the sales team might insist the credit team release the order to ensure a good customer experience. In such cases, many times credit teams release the order based on a verbal payment commitment which isn’t always reliable.
Credit teams can proactively handle blocked orders by leveraging AI capabilities. AI helps credit teams predict upcoming blocked orders to proactively recover a partial payment from the customer before releasing the order.
The financial environment is vulnerable to unforeseeable economic changes. The constantly evolving landscape of interest rates, inflation, and market dynamics can significantly influence the creditworthiness of borrowers. Navigating these fluctuations to protect financial interests remains a persistent challenge.
Let us explore how organizations can mitigate the challenges related to credit risks by adopting and implementing some key credit risk management processes.
Many organizations have dedicated credit teams for measuring the credit risk of their customer portfolios. But how will they assess the credit risk? What’s the procedure for credit risk evaluation?
To answer these questions, organizations must build a robust credit control policy that essentially acts as a framework for credit teams. Every organization has its specific credit policy, but overall, a credit policy should provide clearly articulated guidelines around:
A structured credit policy ensures that the credit team uses a standardized method for managing a customer’s credit risk. This leads to consistent credit decisions and eliminating compliance issues because there is an audit trail. Additionally, a credit policy helps to swiftly onboard new talent onto the credit team because they can quickly consume the guidelines to start evaluating credit risk.
The onboarding process is a key touchpoint for customers within the organization, where first impressions are often formed. The whole process should be seamless and hassle free for better customer experiences.
But often organizations including mid-sized businesses, the customer onboarding process is manual and cumbersome. Manual processing along with complex workflows where data or approvals are needed from multiple teams often leads to errors and substantial delays.
To ensure a superior customer onboarding experience, online credit application forms should replace the paper-intensive process. With an online credit application form, customers can fill in their financial information without missing out on any important details. A key aspect for organizations to consider while designing the credit application form is to include all important customer details that will enable us to assess the creditworthiness of the customer. Missing out on key elements would impact the risk mitigation decision-making process.
E-workflows enable automatic approvals (provided the required criteria are met) to support faster onboarding. Automating the credit application and approval workflow results in faster customer onboarding that improves CX and further standardizes the credit assessment for better credit decisions.
Apart from the information provided in the credit application form, organizations should also research their customers’ financial backgrounds using data provided by third-party credit agencies.
Credit rating agencies and bureaus help predict customers’ current and future financial health. Here’s a list of authenticated credit information sources for risk assessment:
Source: Link
Third-party credit agencies provide the latest, authentic, and accurate information about companies. However to access this information organizations often need to pay a substantial subscription fee to aggregate the credit information from different sources. Order-to-cash (02C) automation solutions like ours provide out-of-box integration with leading credit agencies, thus helping organizations save on high subscription fees.
Many credit teams often use the same scoring model for all their accounts. This one-size-fits-all model is an inefficient way to calculate credit scores.
Customer demography varies in many ways including by industry, type, geography, and compliance measures required. Organizations need a flexible scoring model to get accurate scores for each of their customers. Credit scoring models must utilize real-time data from credible sources to ensure that organizations can keep track of all high-risk accounts.
The sales teams often play a pivotal role in customer onboarding and credit review decisions based on their client perspective. Without concrete customer information, this can often lead to providing skewed customer views resulting in unfavorable credit provision for high-risk customers.
Credit decisions made without data-driven validation of the creditworthiness of customers are likely to lead to higher bad debts adversely impacting the cash flow.
Some major metrics to use while calculating the creditworthiness or credit score for a customer are:
Many mid-sized businesses often lack proper workflow for credit approvals and correspondence delivery. The absence of standardized workflows results in miscommunications, leading to erroneous credit decisions. Incomplete data on the credit application form and the time taken for a credit to be approved by the senior management can result in delays in the overall process as well as impact customer experience. To counter these challenges organizations must streamline the credit approval process using electronic forms and automation systems.
Apart from internal communication, the customer needs to be apprised early on about credit acceptance, credit denials, and any additional data needed. These communications should be done swiftly so that the customer can provide prompt responses. Many mid-sized businesses often rely on paper-based correspondence techniques such as sending letters by post to convey such information. This is not only time-consuming but is inefficient, and expensive.
Organizations need to adopt the usage of electronic channels (emails, notifications and automated alerts on the app) to make the correspondence process smooth. With the usage of ready-to-use templates, the credit team can save the time spent drafting the letters. Further correspondence delivery via email saves on the costs.
Constant monitoring of customers’ financial health is crucial to stay on top of high-risk customer accounts. This can be done with periodic credit risk reviews. Periodic reviews refer to the updating of credit data and scores in specific time intervals for better credit risk accuracy. The parameters tracked include payment behavior, type of deductions, order size, and seasonality, among others.
Any changes in these factors influence a customer’s credit score and credit limit. Periodic reviews help you keep a constant tab on your customers’ financial health and take proactive measures such as updating credit terms and monitoring chances of delinquency.
Digitalization is a key enabler when it comes to mitigating credit risk. Let us understand what are the key benefits that organizations can experience when they digitize their credit risk management processes.
Using automated solutions is an efficient way to monitor risk in real time. Such solutions integrate easily with credit agencies and send alerts to credit risk management teams directly. Real-time credit risk monitoring keeps organizations updated about all the risks and opportunities. It helps to identify and mitigate credit risk before it becomes a problem. The cumulative impact of this is a reduction in bad debts, with better financial stability and cash flow.
With increased information on customers’ creditworthiness in real time, credit teams can make credit decisions specifically about credit controls. The credit teams can closely work with sales in identifying customers to extend credits, increase credit limits, and provide better payment terms and exclusive offers such as discounts on early payment. This can greatly aid in attracting more customers and increasing sales volume with existing customers.
Efficient and rapid customer onboarding, coupled with clear and streamlined communication regarding credit decisions, enhances key customer touchpoints, leading to an overall elevation in the customer experience.
Automation enables real-time credit management, lowers credit risk, and reduces bad debts through automated periodic reviews, faster customer onboarding, bank and trade reference validation, real-time credit risk alerts and alert-triggered credit reviews. In fact, 66% of firms utilizing AR automation have reported improved DSO and 49% have achieved lower delinquency rates.
HighRadius Credit Cloud is an AI-based credit risk management software that empowers credit teams to mitigate risk with real-time credit visibility and manage global portfolios through comprehensive workflows. With end-to-end management of the entire credit management process organizations are able to get a complete view of credit risks at all stages which enables them to make better credit decisions and expedite the customer onboarding process by 67%.
The key components of credit risk management involve a streamlined customer onboarding process, efficient credit data aggregation from various sources, implementation of a best-in-class credit scoring model, standardized approval workflows, and regular periodic credit reviews, with credit teams serving as the primary defense against financial risks to the business.
Implementing online credit application forms, supported by e-workflows for automatic approvals based on specified criteria, accelerates customer onboarding by replacing manual processes and enhancing the overall experience through efficient automation.
The essential fields in a credit application form include the type of business, requested credit extension, applicant’s certification, applicant’s authorization, and terms & conditions.
The top information sources for credit risk assessment include third-party credit rating agencies and bureaus such as Equifax, FICO, D&B, and Experian, which provide authenticated and accurate information about companies.
To build the perfect credit scoring model, employ a flexible approach that considers the diverse characteristics of your customer base, and utilizes real-time data from credible sources such as bank and trade references, public financial statements, credit agency information, and financial stress prediction, while avoiding a one-size-fits-all model that may lead to inefficient and inaccurate credit scores.
Major factors to consider for credit scoring include the delinquency score, Paydex score, average days beyond the term, predictive scoring based on historical trade data, failure score indicating the probability of bankruptcy, and the number of years in business. All of these together provide a comprehensive view of effective credit risk management and decision-making.
Periodic credit reviews are crucial for staying on top of high-risk customer accounts as they involve constant monitoring of financial health, updating credit data and scores at specific intervals, tracking parameters such as payment behavior and order size, allowing for timely adjustments to credit terms and monitoring the likelihood of delinquency.
Standardized credit management workflows, facilitated by electronic forms and automation systems, help fast-track approvals by eliminating miscommunications, reducing delays caused by incomplete data, and ensuring a more efficient credit approval process in mid-sized businesses.
To improve correspondence with clients, organizations should transition from time-consuming and expensive paper-based methods to efficient electronic channels such as emails and app notifications, utilizing ready-to-use templates for streamlined communication and cost savings.
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