By Marieke Saeij, CEO, Onguard
Covid-19 has forced the world to adapt to a new normal. For finance teams this means shifting some of their focus from long-term growth to chasing payments that were put on hold earlier in the pandemic.
Much of 2020 has seen businesses turning to digital transformation to ensure business continuity through the pandemic. With the current lack of certainty, finance teams must now focus on future-proofing their credit management. Having always been a key component, good credit management is now critical to business survival in these uncertain times. This must start with the right data.
Data is key to future-proofing
The advantages of being a data-driven organisation are increasingly recognised. Digital transformation projects to ensure this are well underway in many organisations, with over three-quarters (68%) of finance professionals in the Onguard 2020 FinTech Barometer stating their organisation is already undergoing digital transformation.
Data insights can help to reduce the days sales outstanding (DSO) and allow credit managers to create a better understanding of risk profiles. Identifying payment patterns from the data produces better risk analysis and the ability to anticipate trends. The finance team is more rapidly alerted to the first signs that a customer will not pay, for example. Staff can then step in to resolve the situation. Data analysis will also predict a prospective customer’s expected growth, chance of bankruptcy or payment behaviour. This is not a capability many organisations currently have without laborious manual methods.
With these insights, finance departments can better advise management at the strategic level, elevating their role within organisations. But finance professionals’ insights may also help other colleagues. For example, sharing risk information with account managers will allow them to better calculate whether or not to approach a customer for upselling or new business, which could make all the difference.
Yet despite all the discussion of digital transformation, most organisations still only use a portion of their available business data. This is as true in credit management as any other area. According to the Barometer, only 7% of executives think their own organisation is already data-driven. It means the focus in credit management, as in other departments, must be on exploiting an organisation’s existing data riches because this is the most efficient and cost-effective route to becoming data-driven.
Put your data before third party data
Businesses should start by using data from their own consumer base, such as their customers’ payment behaviour. This is not only more cost-effective, but risk profiles based on an organisation’s own customers can reveal more about future customers than data from other companies. The risk profile scores based on internal data will therefore have greater predictive value.
External data can be expensive, as highlighted by McKinsey, but it shouldn’t be discounted entirely. Its use can strengthen an organisation’s own data resources, bringing a wider understanding of the market that makes for better decision-making. An organisation can combine internal and external sources as it evolves to best suits its needs.
The gains from this hybrid approach are tangible and come as enhanced sales, improved products, better finances and more targeted marketing, supplying a better service that boosts satisfaction levels and leads to improved relationships.
Automation and AI
Robotic process automation (RPA) automates the repetitive manual tasks in credit management that involve collection and collation of masses of data and divert skilled employees from more valuable work. Artificial intelligence (AI), however, is the group of technologies with more far-reaching potential, making smart use of all available data. It links everything from CRM and ERP system data, to all the cogs in the order-to-cash process. This includes linking accounts receivables management with data about customer acceptance and e-invoicing. AI integrates these processes, transforming efficiency and delivering new insights through its analytical power. For finance departments it will also link with recognised parties that provide credit information, as well as payment service-providers and an automatic payment processing solution.
AI’s predictive capabilities help minimise non-payment risk, support the forecasting of cashflow and advise on follow-up actions. This includes, for example, whether individual customers will respond better to phone calls, or when there is no alternative to commencement of collection proceedings.
Using individual insights based on consumer history, AI can even help identify the best time to contact specific customers. This will this dramatically improve operational efficiency and if customers are approached in the right way, at the right time, will enhance relationships and bolster retention.
The personal touch
Although the future of credit management will hinge on the right technology, the importance of personal relationships must not be neglected. A future in which all contact with customers is automated will soon become unprofitable in credit management, where personal relationships are all-important.
Although data provides insight into overall payment patterns, it does not reflect the totality of the relationship with the customer. A credit manager might know that a single call is all it takes to trigger payment from a certain customer. Yet as much as AI will achieve, it still lacks the emotional intelligence to pick up on these kinds of nuances and subtle differences in character that make a difference. This matters because customers will soon switch providers when service-levels drop or if they start to feel they are just being treated as a number.
One of the ironies is that if an organisation has the right credit management solution, it will understand more about the customer and have a firmer basis for effective person-to-person interaction. If you know more about a customer, saying the right things to obtain the outcome you want is easier.
Looking ahead
It’s clear that the future of credit management will be driven by data. Data insights drive far better decision-making and outcomes, providing organisations not only with an edge on competitors, but also the agility to survive a fast-moving landscape.
Agility is key now more than ever. The last six months have shown that organisations must be prepared and ready to meet the challenges with credit management that is already future-proof. That requires becoming data-driven and the adoption of fully-tested automation and AI.
Yet, as we have explored, reliance on technology alone is not enough, and will lead to one-dimensional relationships. The personal touch continues to be important to building long lasting customer relationships, particularly in fraught times.
Alongside the implementation of solutions that deliver results quickly and cost-effectively, organisations need to embrace this hybrid approach that blends the best of conventional methods whilst preparing them for the data-driven future.
