Credit and A/R projects are large, complex, expensive and fraught with risks. This e-book demystifies technologies such as Robotic Process Automation and Artificial Intelligence to help finance leaders transform operations.
After the assessment, the information needed to address the issues and start filling in the gaps is collected. The next step is to understand the capabilities of various ERPs to achieve TO-BE processes and the deployment options.
Most ERPs provide some out of the box functionality for the following four processes:
The following image details the key requirements of credit and A/R leaders in various processes:
Each process in credit and A/R is heavily customized to suit business needs as per the fit-gap analysis. Additionally, there are many automation opportunities in the credit and A/R processes beyond the basic ERP capabilities, which are enhanced by 3rd party solutions.
Many organizations already have some form of credit management out of the box in ERP systems. The presence of more than a few of the following within an organization might be an indicator that the upgraded credit management technology might be worth evaluating:
Credit decisions are complex and involve the manual data aggregation from 3rd party sites including credit agencies (Dunn & Bradstreet, Experian etc.), public financials aggregators and insurance firms. Automating the credit data capture process will save time and improve productivity of credit teams. Figure 8 explains the above pictorially.
Credit processes require collaboration for teams within and outside the organization to arrive at credit decisions. Empowering credit teams with set workflows and streamlining the processes will greatly improve the productivity of all the stakeholders. It is recommended to create workflows for the following cases:
Many organizations process hundreds of credit applications every month while onboarding new customers. In that process, there is a lot of back and forth between sales, customer support and customer teams to put together a credit application. Providing a standard online application where customers can fill out all the required details will significantly speed up customer onboarding time. The online credit application will also increase the productivity of sales personnel for they don?t have to get involved in data collection.
EIPP solutions have struggled with low customer adoption because:
Having a phased roll out and a strong incentive plan are critical for ensuring that the implementation of EIPP solutions is a success. Here are some best practices:
Apart from the above, choosing the right payment solution that is compliant with PCI DSS norms is important. To learn more about the differences between payment platforms and the how to risk associated with credit card data theft view the video here.
Cash application is one of the most manual operations in the credit to cash process. There are many reasons for this ? various payment modes, non-standard remittance formats, electronic remittance decoupled from payment, many channels of remittance delivery, including email, portal and paper, just to name a few. This inherently inefficient process then becomes a bottleneck for most accounts receivable operations teams because it slows down downstream processes like deductions and collections. Consider the following scenarios:
Figure 9 highlights the manual steps in cash application. In addition to the above, in case of check payments, the issues are with:
In case of electronic payments, the issues are with:
All of the above steps including aggregation of remittances, linking and matching remittance and open A/R could be automated by artificial intelligence and Robotic Process Automation(RPA) powered systems.
A collections analyst?s primary responsibility is correspondence with customers. And yet, according to many findings, an analyst spends only 20% of his/her time on correspondence and rest of the time organizing who to call, collecting backup and engaging in other activities including composing emails. Some best practices for the collections management are outlined in the following section.
A McKinsey study stated that more than 70% of collections calls are made to customers who would have paid anyway. This statistic seems to indicate a redundancy in the process, and unnecessary work being done, especially considering there is technology available that could analyze and prioritize the collections workflow. For example, dunning notices (outlined in Figure 9) could be sent through RPA by configuring rules and linking the correspondence technology with accounts receivable module in the ERP.
Prioritized accounts in a worklist is the single most important feature for collections analysts. However, a collections agent usually transacts with many kinds of open A/R items, including those that are disputed, that have promises to pay and so forth and ageing list doesn?t capture all these attributes. Often such A/R items are deemed ?uncollectible? on that particular day and a collector?s worklist should not contain any of these uncollectible items. While configuring the collections worklist, make sure to exclude the following AR items from a collector?s worklist:
For more information on identifying clean receivables and prioritizing accounts for collections, watch the on-demand video here.
Deductions Management is process intensive and requires cross departmental collaboration between Credit, Collections, Accounts Receivables, Customer Service, Logistics, Sales and others. In a recent study conducted by the Credit Research Foundation (CRF) on customer deductions, lack of cross-departmental cooperation and inefficient processes were identified as the top two internal challenges for controlling deductions. Here are some of the best practices while transforming deductions operations.
RPA is the key technology to implement workflows for deductions management. Configuring rules for routing deductions cases to appropriate roles is done through RPA. Some of the best practices are:
As discussed earlier, cash application has a significant impact on deductions operations as lot of deductions could be identified while applying cash. Review cash application processes for opportunities to improve the postings that significantly enhance the deductions resolution process. The artificial intelligence technology available today could automate the aggregation, linking and matching remittance information with payments to automatically post cash and open deductions cases if applicable. Figure 11 shows the cash application process. The following is a summary of recommendations to consider:
Clearly define the scope of each module and the level of customization required. The common pitfall here is planning a Phase 1 with out-of-the-box features of ERPs with the anticipation of Phase 2 for enhancements and customization. Even though some companies manage to get budgets for a Phase 2, most FSCM implementations do not have a follow-on Phase 2 and end with what was implemented in Phase 1. A separate, consequent phase for enhancements and customization will cost significantly more compared to including customizations as part of Phase 1.
HighRadius Credit Software automates the credit management process, enabling credit managers to make highly-accurate credit decisions 2X faster and enable faster customer onboarding with 4 primary components: configurable online credit application, customizable credit scoring engines, credit agency data aggregation engine, and collaborative credit management workflow. Along with that, there are a lot of key features that should definitely be explored some of which are online credit application, credit information aggregation, automated credit scoring & risk assessment, credit management workflows, approval workflows, and automated bank & trade reference checks. The result is faster customer onboarding, better internal collaboration, higher customer satisfaction, more targeted periodic reviews, and lower credit risk across the company’s customer portfolio.