More and more companies can testify to the benefits to their liquidity of intelligently automating their Order to Cash process.
Accounts receivable account for around 40% of a company’s balance sheet assets, making it one of the most important items on the balance sheet. It is also potentially the riskiest, especially if poorly managed. In fact, today, one in four business failures is due to unpaid receivables. New digitalization technologies offer tremendous leverage for freeing up working capital and reducing risk. They will strongly challenge traditional, repetitive and manual methods of managing accounts receivable, by providing modern uses that are perfectly in tune with the challenges of business dynamism for companies.
Using artificial intelligence to improve customer risk management
Artificial intelligence combines the power of algorithms, Machine Learning and Big Data.
In debt collection software, for example, artificial intelligence makes it possible to use internal and external data to automate customer risk measurements. This enables credit managers to adapt the levels of outstandings granted to customers, or even debt collection scenarios.
These software packages can also be equipped with alert functions to ensure that they are always on the lookout for potential risks of non-payment.
Predict when your bill will be paid thanks to artificial intelligence
Some collection software packages also incorporate machine learning technologies which, coupled with a unique database combining dunning and customer payment data, will enable you to predict your customers’ payment times before they pay your invoice. This enables you to anticipate and implement proactive risk management and collection measures.
By anticipating the behavior of your defaulters, you can take appropriate action.
What’s more, you can estimate your future collections and cash flow forecasts. So you’re much closer to reality than if you were to rely solely on your customer payment schedule.
Machine Learning boosts lettering processes
Lettering also contributes to more efficient dunning. “By automating this process, accounting teams are able to follow up only those customers who have not paid their invoices, thus increasing efficiency”, explains Valérie Konarski, Director of Financial Processes at DIMO Software. As soon as the lettering module embeds artificial intelligence, and in particular Machine Learning, then it is capable of having the same expertise as man through its knowledge of the customer and in particular his payment habits. Using these programs, it automates important tasks that significantly increase the lettering rate. This daily companion facilitates the work of accountants, guiding them, for example, towards the most appropriate lettering proposal.
“In less than a month, thanks to CashOnTime’s self-learning engine, our company’s lettering rate jumped to 90%“, says Bertrand Marat, IT Manager for DUPONT Restauration’s Accounting, Finance and HR departments.
For Laurence Contion, Accounting Manager at Securitas, who also uses CashOnTime, “the major benefit is that by 8:30 in the morning, the customer accounts are up to date for three quarters of the transfers!
In addition to freeing up working time and automating manual, repetitive tasks, artificial intelligence enables finance departments to make the right decisions more quickly.
