Rethinking B2B Risk, Part 4: Lowering Risk Exposure With Decision Analytics
Automation is taking every industry by storm, and many creditors are finding that it can improve their businesses while lowering risk. By automating credit risk management, organizations can more easily incorporate decision analytics into their workflow to help them gain deeper insights and allow them to extend credit to customers with confidence.
The approach is simple: Process automation software that integrates decision analytics helps creditors assess each potential transaction by analyzing internal and external data behind the scenes and returning the relevant information needed to make a decision. Trade providers want to know how long a firm has been in business, the status of its cash flow, how well it pays other trade providers, and whether they will get paid for the goods they ship or the services they provide. Automated analytics can help businesses find answers to these questions by drawing on big data sets that may otherwise be difficult to obtain and time consuming to review.
Getting lost in analysis
For instance, imagine you are a B2B creditor looking at a logging company whose assets are mostly in equipment and buildings, but that has little cash on the books. With no previous experience in the logging industry, how can you value the company?
One way would be to trust the applicant, but that could end in grief. More responsible creditors will cross-reference the firm’s books with one or two competing businesses to uncover the full market value of the firm’s total assets. If you go this route, the more competitors you can compare, the better. However, the further afield you go, the more you begin to compare apples to oranges. So, what can you do?
Analytics to the rescue
This is where decision analytics comes in. By accessing more data sources and taking into account more factors, analytics tools do the heavy lifting for you while also providing a deeper level of insight about the business. This information can be aggregated and analyzed with minimal time investment, thanks to automation software.
Some companies resist automating this aspect of due diligence, especially in cases where manual hands-on processes are relied upon to ensure greatest control. The issue here is that these ad-hoc processes can introduce errors because they may lack standardization and objectivity. With automated decision analytics, you can minimize errors and fine tune your process to help you come to the right decision and quickly respond to your customers.
To learn about other potential barriers to effective B2B credit risk management, check out Rethinking B2B Risk, Part 3.
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