The topic of the treasury is currently one of the hottest and most debated in the boards of directors. It seems true that the establishment of a solid “cash culture”, that is, an organization in which cash management is the responsibility of all actors in the customer relationship chain, assisted by technologies, is a priority lever for enable companies to weather the current storm and those to come.

According to a recent study carried out by KPMG in the UK, 75% of the CFOs surveyed rank cash as the main element of their investment programs. This is not a surprise: the locks have exacerbated the duration of the cash collection. According to data from Sidetrade tracker – BFM Business Of the unpaid invoices, the proportion of unpaid invoices ten days after their issuance has skyrocketed in France since the start of the pandemic, doubling in May 2020 to reach 38%. We can estimate that this represented more than € 270 billion of blocked cash, including nearly € 140 billion directly attributable to the impact of the health crisis on companies’ payment behavior.

Faced with this cash flow problem, which has become literally existential, the financial departments of companies have had no choice but to accelerate their “digitization”, and more specifically by resorting to automation technologies based on Artificial Intelligence. But what specifically does AI contribute in this context? How can deep learning algorithms, which are generally praised for driving or facial recognition, literally save companies?

A bit of technique

AI extracts information from different sources like CRM databases (customer relationship management) and ERP (Enterprise resource planning) or open access data files. Combined, this data enables the payment behavior of a given company’s customers to be scored and evaluated, so that collections teams can adopt the appropriate strategy.

In combination with other technologies, such as natural language recognition (NLP), AI automatically collects, identifies and manages all types of electronic data. This technology makes it possible to simplify, accelerate and make the management of the entire customer relationship chain more reliable: purchase orders, invoices, etc., all these documents are automatically recognized and assigned to the correct follow-up file, customer complaint emails. customers. are automatically interpreted and sent to the appropriate managers for quick dispute handling …

Armed with this constantly updated data, AI can, in real time, draw emerging trends, model and anticipate changes in customer behavior to adapt strategy.

A perfect partner?

One of the great advantages of AI is its versatility and ability to take on different roles within the finance team. To stay, a little easily, I admit, in the news, we could compare him to a footballer who, placed in any position on the field, would score every time.

AI helps balance workloads among all team members and automatically generates priority action lists, allowing efforts to focus on the most profitable cash flow opportunities. By doing its part of the work (automating simple tasks, like sending emails, for example) and empowering the team through its recommendations, AI can really be considered, in this case, as one more colleague within “credit management “. team.

In other scenarios, AI can act as a “behind the scenes operator”, whose role is to perform tedious and repetitive but essential recovery tasks, saving considerable time for operational personnel.

Technologies that use artificial intelligence can also be mobilized for “selective collection” and focus on low-risk account collections, in order to free up time for collection officers to focus on the most important accounts.

This flexibility makes life much easier for finance teams. The impact on your stress level and morale is really positive, an important asset in the current context.

The enemy is not the AI, but the time wasted in distrusting it!

But then, is AI, this super-employee, ultimately a danger to existing finance teams?

Let’s put an end to the suspense: my conviction is that, in the world of corporate finance, as in most sectors, opposing humans and AI is not only a pointless debate, but totally deleterious. We could also consider that this particular field of application of Artificial Intelligence, which is corporate finance, is one of those where the benefits are easier to recognize.

On the one hand, we have teams of a few employees in charge of speeding up payments for thousands of customers, most of the time using a totally outdated phone, emails and spreadsheets, because they are not designed to handle such complex processes. It is a laborious task with necessarily random results, regardless of the professionalism and involvement of the teams involved.

On the other hand, intelligent automation can provide detailed analysis of the collection process, in order to reveal trends and recurring patterns in millions of payment experiences and collection actions. AI can predict good and bad payment behavior, significantly reducing business risk by identifying customers with significant payment delays. These items can be used to establish payment schedules for customers in distress.

Eliminating time-consuming manual processes minimizes your risks. Companies that implement automated and intelligent systems help their finance teams reduce payment terms more quickly while better understanding the behavior of their customers. These technologies enable higher employee satisfaction (they can focus on their core business), better cooperation between different departments, with the corollary of better customer retention through a better relaunch experience, accelerated business growth and higher profitability. Finally, the digitization of financial data allows the company to comply with various data protection regulations.

Let humans trust AI, and AI will give it back … a hundred times more!