By Geralyn Frances
SunGard takes order-to-cash a big step forward with AvantGard GETPAID.
Assessing business risk across the organization is becoming increasingly the responsibility of treasury, and new tools to help quantify and, ultimately, to manage these risks are emerging at a rapid pace.
One such tool is SunGard’s AvantGard GETPAID. By combining collections automation and statistical risk modeling into one robust solution, SunGard is helping to provide efficiency and transparency to the credit and collections process. Their comprehensive order-to-cash system and modeling of customers’ payments provides a window for treasury into the timing and likelihood of real cash generated from trade receivables.
Getting the cash going
For some time now, automation in credit and collections and improving technology has been employed by best-in-class organizations to boost the accounts receivables process (see “Staying on Top of Accounts Receivables” on iTreasurer.com).
The ultimate goal of course is to improve working capital by ensuring that your customer receivables become collectible cash. SunGard’s AvantGard GETPAID takes credit and collections a big step forward; utilizing customers’ credit history and modeling payment behavior to predict the likelihood of future cash flows.
“Treasurers are naturally more active with trade receivables, being that it is (typically) the largest source of cash,” notes CJ Wimley, EVP, Trade Liquidity Solutions at AvantGard. And with Treasurers taking on more of a strategic role in organizations, tools such as AvantGard GETPAID will be necessary for taking the next step to improving cash generation and sharpening liquidity forecasts.
AvantGard GETPAID makes fast and efficient use of customer payment data to enhance the accounts receivable process, including the proactive managing of customer collections and the fine tuning of cash forecasts. With the company’s customer payment history embedded in the statistical model, the tool provides analysis based on your company’s experience, not that of other companies. So, while some external bureau information may be factored into the model, your particular customer payment history is the key ingredient needed to make the cake.
suppliers preferred
It is a given that many business customers prefer suppliers, whether it is because they move more of their product, earn a larger margin on its sale or the goods purchased are more critical for production.
Whatever the case, more often than not, those critical suppliers will get paid first, particularly when credit is tight. Therefore, just how strategic a supplier your company is will often factor into the timing of your receipts.
“Treasurers are naturally more active with trade receivables, being that it is (typically) the largest source of cash.”
— CJ Wimley, AvantGard
While using bureau information is a start, it is certain that it will not be totally reflective of your particular customer payment experience, and by incorporating your own specific customer history into the model, it becomes that much more relevant; and issues can surface earlier.
According to a SunGard white paper, “Business Credit & Collections Risk Analysis,” a statistical credit model should have more than 1,500 customer accounts for it to produce optimal results, including the allocation of limited credit resources to various collection strategies and the quantifying of portfolio risk.
To that end, SunGard recommends that companies with fewer customers are better off utilizing a judgmental/rules-based model supplemented with generic credit scores and external financial and trade information rather than a statistics-based model solution.
A Closer Look
AvantGard GETPAID is a combination of two proven SunGard products: 1) GETPAID and 2) Predictive Metrics. Both products enhance the decision support capabilities within the order-to-cash process, with integrated, automated workflow and statistical modeling which allows organizations to focus on “cash at risk”—those accounts likely to fall delinquent in payment.
According to SunGard, GETPAID can help drive automation and workflow across the order-to-pay cycle. Consolidating and centralizing receivables data improves visibility and collaboration enterprise-wide. System portals and management dashboards provide access across functions such as sales, treasury and shared-service centers, making the managing of credit and collections not only easier but also smarter.
Ultimately, improved working capital is achieved through lower DSO and increased cash flow.
One of the powerful tools embedded in the GETPAID solution is AvantGard Predictive Metrics, a statistically based customer-scoring model that allows companies to prioritize collections and forecast cash based on their customers’ payment history. Aging reports can now be replaced by risk scores; and collections strategies are determined by model results based on actual payment history and not the more traditional-based credit bureau information. Business credit managers will attest that the best indicator of the ability to pay is your own experience with a customer. So beyond the initial credit screening, which often includes bureau data as well as financial statements and bank and trade references for lack of history, their own payment experience is preferred.
prediction Validation
AvantGard’s stat-based scoring models go through a validation process documenting the ability to predict a problem payment, even before the model is implemented. Mr. Wimley notes that the model needs about 18-24 month’s worth of data to run the validation process effectively. And SunGard will prove, in advance, the predictiveness of their scoring technology, comparing against any scoring or data you currently are using to evaluate your customer receivables.
Take the experience of a director of credit services at a $3bn US subsidiary of an industrial MNC who implemented the AvantGard account-receivable tool in her company two years ago. Employing AvantGard Predictive Metrics, she was able to pinpoint one historically credit-sound customer who was starting to extend their payable days outstanding, and increasing it every month. However, this payer was still within its 45-day credit terms. While typically this customer would not even be on the radar screen being that they were not past due, predictive metrics was able to highlight the deteriorating payment trend.
A visit to the customer by the director revealed new ownership and a change in management, allowing for the opportunity for renegotiating contracts and securing more amenable terms. The director was thus able to “stop the bleeding” and act proactively. While preventing a possible future overdue account, she was also able to put certainty back into the likelihood of the timing of the cash flow.
The robust modeling feature also allows this company to offer good-paying customers, with only marginal credit, more favorable terms. A customers inability to obtain sufficient trade credit can limit sales, and because the model follows your customer’s behavior so closely, you can offer increased internal lines to improve sales. The director notes she is comfortable offering “B” level customers more of a credit line if they have a solid payment history because the company has the AvantGard infrastructure in place. Otherwise, “Without these tools, I would not want to manage it,” she says.
For this credit director, the next step is “a bridge to forecasting, a pipeline to treasury.” Knowing the predictability of your receivables provides visibility into real cash flow and its timing, and that can feed liquidity forecasts.
The collaboration between credit and the sales team, as well as treasury, is one of the key successes coming out of the AvantGard product. Accessible, timely and validated information is valuable to all functions. For treasury, the predictability of cash receipts from account receivables is enhanced as the statistical modeling produces the certainty of getting paid by each specific customer in a predictable way. Each customer is scored and monthly updates keep the model current.
These key outputs and features help organizations take B2B trade credit to a new level. By identifying cash at risk, credit managers can proactively manage delinquencies and reduce collection efforts and bad-debt losses. Treasury can increase the accuracy of cash forecasts based on the more detailed trade receivable data. And sales teams are able to increase sales to customers with lower Probability of Bad (PBAD), despite their external credit score or their inability to secure trade finance. A collaborative company effort is achieved with measurable benefits for all functional groups.
Suggested tweak
One area of improvement suggested by the director of credit would be a more robust reporting tool. The ability to customize reports within the SunGard tool, rather than downloading data and creating your own custom report would be an enhancement.
As noted, AvantGard GETPAID does offer good standard reporting of your receivables data; however, fine-tuning the reports to include specific elements and/or a certain layout is currently not available.
In managing customer risk and securing trade receivables, there is no doubt that automation has helped to streamline the once manually intensive effort of credit and collections. SunGard has been an active player in optimizing the order-to-cash process and now, with predictive metrics modeling capability, organizations can take it a step further, utilizing GETPAID to predict real cash expected out of their receivables portfolio. It may be time to incorporate this predictability into your liquidity planning.