With new and rapid technological advances, particularly the advent of AI, credit management has become more precise and predictive than ever before. Currently, 36% of finance professionals see a major influence of big data on financial processes such as budgeting, forecasting and financial analyses, while 45% find AI to be the technology used more and more frequently.
But to know what technologies are useful for company credit checks and credit management, there are a few factors to consider. More than anything, businesses are looking for speed, accuracy, and depth in analysis. But what technologies cover these and other key requirements?
In this blogpost, we explore the latest technologies that businesses can leverage to conduct accurate and in-depth company credit checks. We discuss the following:
Credit management is the strategic process of assessing, extending, and monitoring credit to customers or other businesses. It involves a comprehensive approach to managing credit risk, from initial credit approval to debt collection. Today, credit management is almost entirely automated, with comprehensive checks and procedures in place to verify a vendor’s ability to make payments.
A crucial component of credit management is conducting company credit checks and enhanced due diligence. These processes allow businesses to assess the creditworthiness of potential and existing customers, mitigating the risk of non-payment. This is one of the key risks to assess as currently in the UK, 27% of businesses have admitted to being owed thousands in unpaid invoices.
If informed by the latest technologies and robust enhanced due diligence procedures, businesses can see a 20% reduction in bad debt.
Artificial Intelligence (AI) and Machine Learning are reshaping the landscape of credit management. These technologies offer advanced capabilities to analyse huge datasets, identify patterns, and make data-driven recommendations in a fraction of the time it would take otherwise.
Machine Learning involves training algorithms on large datasets to recognise patterns and make predictions. In the context of credit management, Machine Learning algorithms can analyse historical data on customer behaviour, payment patterns, and economic indicators to identify factors that correlate with creditworthiness. They can also analyse data from social media feeds, market reports, and news articles.
Robotic Process Automation (RPA) is a powerful technology that can significantly streamline and automate repetitive tasks in credit management. By deploying software robots, businesses can automate routine processes such as data entry, invoice processing, and company credit checks.
This frees up valuable time for credit analysts to focus on more strategic tasks, such as analysing complex financial data and making informed credit decisions. According to a report by Gartner, “finance departments can save their teams from 25,000 hours of avoidable rework caused by human errors by deploying RPA.”
Cloud-based solutions are software applications and services that are delivered over the internet, rather than installed on individual computers or servers. Instead of hosting the software and data on your own hardware, you access them through a web browser or mobile app. This means you don't need to worry about managing complex IT infrastructure or software updates.
In recent years, complex cloud-based solutions have revolutionised the way businesses manage their credit operations and conduct company credit checks. By leveraging the power of the cloud, credit teams can access and analyse critical data from anywhere, at any time, significantly improving efficiency and productivity.
Cloud-based solutions offer a range of benefits, including enhanced scalability, improved security, and reduced IT costs.
Company Watch is a cloud-based credit management solution that offers comprehensive financial risk management tools to conduct enhanced due diligence, company credit checks, director checks, and fraud detection. The Company Watch architecture ensures seamless access to its services, enabling credit teams to work efficiently and effectively, regardless of their location.