4 Common Challenges of Manual Credit Decisioning and How to Avoid Them
For financial executives, one of the most important tasks is to make accurate and timely credit decisions. While manual credit decisioning can seem straightforward on its surface, there are numerous challenges that can arise throughout the process. From slow turnaround times and data inconsistencies to unfavorable customer experiences, here are five common issues with manual credit decisioning and how to solve them.
The Problems with Manual Credit Decisioning
Manual credit decisioning, or the process of manually assessing a customer’s ability to repay debt based on their financial information, has been around for decades. However, as the demands of customers and regulatory bodies have increased, manual decisioning processes are often ill-equipped to adequately process this load. This can result in delays in decisions and unfavorable customer experiences, leading to missed opportunities, increased collections and lost revenue. This is why more finance executives are turning to automated credit decisioning solutions—which can quickly provide accurate decisions while meeting compliance requirements—to help streamline their processes and improve customer satisfaction.
Poor Data Quality
The quality of data collected during manual credit decisioning is often inconsistent due to human error. Incorrect or incomplete data can lead to inaccurate decisions, which could result in costly losses for businesses and dissatisfied customers. To avoid this issue, finance executives should leverage automated decisioning tools that utilize sophisticated algorithms to analyze financial data from multiple sources quickly and accurately. This helps ensure that all available information is holistically assessed while also reducing risk by delivering more accurate results.
Time-consuming Processes
Credit decisioning processes are often labor-intensive and time-consuming when done manually, as they require tedious reviews of customer applications before any action is taken. Automating these processes can significantly reduce turnaround times while also helping maintain compliance with industry regulations as well as internal policies.
Unreliable Risk Monitoring
Manual risk monitoring processes are prone to errors due to human bias or oversights which could lead to delinquencies and bad debt if undetected. Alternatively, automated credit decisioning processes leverage real-time monitoring and insights to reduce resources while also offering data-rich, comprehensive risk monitoring. This allows for faster, unbiased decision making that helps protect businesses from fraud and loss without compromising the customer experience.
Lack of Transparency
The lack of real-time visibility into the performance of manual credit decisioning systems makes it difficult for executives to track progress or identify potential issues. This often leads to slow response times and approval delays, which not only impact business operations, but can leave the customer dissatisfied. Automated reporting tools simplify the process by providing a convenient way to monitor these systems in real time without sacrificing quality. Automated credit decisioning also provides greater transparency through digestible metrics, including approval rates and rejection reasons, allowing teams to quickly make informed decisions.
Conclusion
In today’s market, where speed and accuracy are crucial factors for success in credit decisioning, relying solely on manual processes no longer meets customer expectations nor helps businesses remain competitive. By leveraging automated solutions, like a comprehensive and customizable credit management system, businesses can overcome common challenges associated with manual credit decisioning, from slow turnaround times and data inconsistencies to unreliable risk monitoring. Automation not only helps businesses reduce costs, improve operational efficiency, and increase profitability, but also deliver better customer experiences through timely approvals.
Understanding risk early in the customer’s lifecycle can drive insights downstream, including collections predictability and cash flow forecasts. Sidetrade offers a solution for credit and collections managers looking to assess the risk in their portfolio and make sound business decisions that keep cash flowing. Leverage automated crediting, collections, and credit risk management software to optimize the order-to-cash cycle and enhance existing processes. Schedule a consultation with us today to learn more about how you can incorporate our technologies into your business.