Optimizing Operational Performance With Ai-Driven Credit Control


As business operations increasingly rely on software automation and real-time analytics, executives need to evaluate how to capitalize upon tech-driven advances to optimize their order-to-cash process. Artificial intelligence-driven credit control systems provide the capability to quickly identify and respond to even the smallest changes in customer payment status, thus offering financial executives the visibility to rapidly adjust operational policies and realize immediate operational performance gains.

Deployment of an AI-based credit control system and associated advanced analytics reorganizes customer and financial data into an easily-accessible platform. C-suite financiers are thus empowered with predictive models to identify high-risk customers, potentially risky customers and high-potential customers in an effort to drive improved cash flow management. AI-driven credit control systems have both reactive and pro-active capabilities, allowing businesses to move beyond simple credit control functions, such as payment reminding, credit limit checking and customer transfer blocking, and use the credit control systems to engage more in customer marketing, such as offering higher credit limits to customers who have demonstrated excellent payment trends.

By integrating an AI-driven credit control system into other enterprise systems such as sales, accounts receivable and collections, executives are provided access to robust set of analytics and dashboards. Without the need for customization, these dashboards can display customer payment patterns and patterns of customer disputes or query resolution. Executives may then monitor and analyze customer payment performance, identify payment preferences and better predict revenue cycles.

Improved visibility into customer payment trends over the long-term allows for the adjustment to operational policies and processes in an effort to capitalize on customer trends and maximize performance throughout the order-to-cash cycle. Automation of tactics such as payment remindings, statements, dunning letters and collection notifications can be adjusted depending upon customer score, payment preference, payment frequency, credit limit and other customer-specific metrics. This allows credit control teams to prioritize goals, including collection efforts and customer relationship building, as well as increase efficiencies and throughput.

AI-driven credit control systems provide an automated platform that captures data from all customer payments, settlements and disputes while increasing control and traceability of operational performance across all order-to-cash activities. With the use of high-level analytics, C-suite financiers can proactively improve the order-to-cash cycle and establish the financial stability and competitive advantage of the business for years to come.