Smart and efficient credit risk management is critical to the bottom line. It’s especially important if you’re like the many companies that are offering the convenience of B2B e-commerce to customers.
Consider these insightful industry research findings:
- In its 2021 B2B Pulse Report, the McKinsey & Company consulting firm found that 65% of B2B companies across all industries offer e-commerce capabilities.
- In its 2022 report, Statista predicted total B2B e-commerce purchases will exceed $4.6 trillion in 2025. With that kind of money changing hands, any high-dollar orders that can be made easier and quicker can supercharge a company’s cash flow.
- But what about the risk of default? Reducing financial risk is the top enterprise risk management priority for leaders (followed by cyber risk), according to Dun & Bradstreet.
“Credit risk management is a key component within order-to-cash. … So that includes the risk assessment that you do up front, the assignment of a credit limit, the issuing of an invoice, the collections management … to make sure that the customer does pay, (and) the cash that comes in to pay for those invoices,” said Rob Harvey, Chief Product Officer of order-to-cash SaaS company Sidetrade.
Obstacles that have prevented B2B e-commerce from becoming as seamless as B2C e-commerce include a long credit approval decision-making process because of the high-dollar amounts, the process for deciding payment terms and payment dates and complex tech requirements. However, cutting edge, cloud-based, AI-powered technology has emerged that both effectively reduces financial risk and performs credit risk assessments in less than a minute, instead of three or four days, Harvey said.
How real-time credit risk management works
Not having enough up-to-date data can lead to bad credit decisions. While your company’s credit department may already have key pieces of credit data from your business customers, it’s the credit agencies like Experian, Equifax and Creditsafe that hold the big-picture data for more accurate credit scoring and dynamic risk classification.
But that data’s siloed and not easy to access – unless you have a software solution with a layer of credit agency connectivity built in.
Harvey described Sidetrade’s process of determining creditworthiness on the cloud:
- A secure digital online application is filled out by the customer. Oftentimes, it’s either embedded into the supplier’s website or customer relationship management system. Key data is gathered for risk review.
- The application gets processed by AI-powered decision-making software.
- At the same time, more than 20 credit agencies and bureaus are contacted by the software to obtain financial information and contextual data, such as number of years in business and payment history.
- That data gets factored together with the AI engine’s payment term and payment date recommendations and machine learning predictions on the likelihood of default or payment delays. And in the case of Sidetrade, additional information from a proprietary “data lake” informs the decision.
- A payment score is determined.
“An instant decision is kicked out – either instant approval and ‘Here’s your credit line,’ or ‘An analyst needs to look at this,'” he said.
If the latter is the case, an exceptions process would be triggered to check if there’s data missing, or if a referral, balance sheet or bank statement is needed.
Either way, the customer knows where they stand.
AI and machine learning can also be leveraged to decide whether or not to raise a customer’s credit limit. “This is a big win for companies. Because if you’ve got a company that’s paying regularly … and they’re growing and they want to start ordering more (goods and/or services) from you, should you be saying, ‘Whoa, whoa, whoa, we need to go back and do a credit assessment and we need to check everything,’ or should you just be auto-increasing them?” Harvey said.
What do early adopters of AI credit risk management say?
Judging by Gartner’s May 2023 Magic Quadrant for Integrated Invoice-to-Cash Applications, there are just a small handful of fintech platforms that are equipped with credit risk management capabilities.
When asked what feedback companies were giving on having rapid credit risk management capability in their invoice-to-cash tech stack, Harvey said results include:
- Shorter onboarding time for new customers
- Noticeably improved customer experience, and
- Better internal communications between Sales and Finance.
Harvey added that having an AI assistant, such as Sidetrade’s “Aimie,” on your side can also be valuable when credit risk management decisions have to be made amid sudden market changes, interest rate changes, supply chain challenges or employment problems. He gave the “non-essential” business shutdowns of COVID-19 as an example.
Next steps for CFOs
If your organization’s pain points include any of these, it may be time to take a look into either a credit risk management technology module or an invoice-to-cash platform with that capability:
- Credit applications that involve paper or manual data entry, which can be a turn-off for potential customers
- Same-level pricing regardless of credit risk, which can get in the way of business growth, or
- A lack of understanding of what credit risk exposure looks like and what your customer profile should look like.