Account Receivables with AI can bring a competitive edge to Businesses
Account Receivable (AR) is considered equivalent to cash, but it has its share of problems. Mismanagement or mishandling of invoices or delays in collections could impact businesses of any size negatively. However, few outcomes would be growing operational costs, Cashflow problems, and sometimes having to rely on expensive debt or credit.
Based on the research conducted by PWC, 15% to 29% of Assets of a company are Account Receivables and 17% of the Sales are stuck in AR based on average industry days sales outstanding (DSO).
Though companies have specific collection teams to handle the AR collections, they are mainly driven manually, like communicating with the customers based on the ageing report and the past relationship with the customer. These techniques are outdated.
Delay in the invoice collection process directly negatively impacts the working capital and can push companies to raise debt to finance their operations and, sometimes, at a higher interest rate. So, handling the account receivables best way possible can be a competitive advantage for the company or business.
What’s, is the current problem?
The current systems / ERP software that businesses use works in Silos, which does not communicate in real-time, making the process slower and inefficient for taking decisions.
- Data inconsistency and inaccuracy. For example, much duplication of data across the system.
- Collection strategy is mainly more reactive rather than predictive. Meaning, the collection team only involves or becomes active when a trigger incident or a data point shows a problem in the account. For example, when the invoice is due or near the payment term date.
Current collection teams depend primarily on intuition, experience, and other static parameters like past due, due date, payment terms, invoice amount, and ageing buckets.
The need of the hour — AR Intelligence platform driven by AI/ML
AR intelligence platform uses macro and micro level parameters, such as the number of delinquent invoices, invoice ageing, working capital, loan/ debts, internal changes in the company, macro-economic trends, industry and market trends.
- The platform can analyze historical customer data, gets insights on customer behaviour, and cashflows and provide valuable insights to make a better decision.
- It also predicts the expected payment date of any given invoice at a point in the future. It can also suggest the value of incentives to the customer for paying quick on their invoice, for example, a discount % on the invoice value.
Kredio’s Intelligent platform can help organizations achieve faster collections, reduced credit risk, better forecasts, sharper decisions, and more satisfied customers. It brings intelligent algorithms to accounts receivable management processes to deliver smart suggestions.
References
