Receivables Technology Fit-Gap


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.

Contents

Chapter 01

Executive Summary

Chapter 02

Pre-Implementation Best Practices

Chapter 03

Receivables Technology Fit-Gap

Chapter 04

Implementation Best Practices

Chapter 05

Post Go-Live Best Practices

Chapter 06

Summary
Chapter 03

Receivables Technology Fit-Gap


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.

Receivables Technology Modules and Capabilities

Most ERPs provide some out of the box functionality for the following four processes:

  • Credit Management
  • Electronic Invoice Presentment and Payment(EIPP)
  • Cash Application
  • Collections Management
  • Disputes Management

The following image details the key requirements of credit and A/R leaders in various processes: Technology requirements in O2C

Operations-Specific Best Practices

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.

Credit Management

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:

  • A distributed system landscape and problems associated with consolidating information for credit decisions
  • Large number of customers and scoring, rating and updating of credit limits that could be automated, minimizing laborious credit calculations
  • Need for custom scores that combine internal and external data for calculations
  • Many external information providers coupled with the desire to eliminate third- party products or plug-ins
  • Too much non-value added manual work
Automated Data Aggregation

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. Automated credit data aggregation

Credit Decision Workflows

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:

  • Credit limit approval
  • Credit limit increase requests
  • Blocked orders
  • Bankruptcy alerts
  • Collateral expiries
Online Credit Application

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.

Electronic Invoice Presentment and Payment

EIPP solutions have struggled with low customer adoption because:

  • It requires changes to current processes
  • It introduces manual A/P processing as customers have to login to web portals
  • It removes the float that many organizations count on

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:

  • Start with the smallest customers who are easier to influence and are good candidates for Phase One. Large customers are less likely to want to change their processes
  • Quantify the cost savings upfront, such as the elimination of paper based billing, DSO reduction, lockbox cost reduction, staff realignment due to self-service, etc. to gain an insight into what savings are available for incentives

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

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:

  • A customer has already paid but, because of the delays in applying cash, the collections analyst still calls the customer for payment
  • A customer has short paid but the A/R team could only start working the deduction after calling the customer or receiving the claims file to identify the reason

Manual process in Cash Application Figure 9 highlights the manual steps in cash application. In addition to the above, in case of check payments, the issues are with:

  • Limited information sent on the check stub
  • Data entry from the check stub to ERPs
  • Linking open A/R to payments
  • Bank Lockbox expenses

In case of electronic payments, the issues are with:

  • Multiple sources such as EDI, email and websites from which remittances have to be aggregated
  • Submitting remittances with PO number, partial invoice number instead of invoices
  • Linking open A/R to payments

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.

Collections Management

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.

Rules-Based Correspondence

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. Automated collections correspondence

Collect on Clean Receivables with Prioritized accounts

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:

  • Items with open promise to pay: Items with an open promise to pay, or items with a future payment promised on date, these items should be excluded from the ?To Be Collected? amount
  • Dispute cases not in a ?To Be Collected? status: All open dispute cases which have not been updated with a status that is mapped to the ?To Be Collected? in collections management should be excluded from the ?To Be Collected? amount
  • Items with a current dunning notice: If a line item has recently been dunned, this amount should be excluded from the ?To Be Collected? amount
  • Items arranged for payment: All amounts that are (1) collected with a debit memo procedure or (2) where the account statement balance contains a payment notification from the bank should be excluded from the ?To Be Collected? amount

For more information on identifying clean receivables and prioritizing accounts for collections, watch the on-demand video here.

Deductions Management

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.

Workflows for Collaborative Resolution

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:

  • Define and implement specific workflows for at least the top three to five reason codes that account for more than 80% of deductions
  • Implement a generic workflow for all other reason codes
  • Implement credit memo approval workflow versus a paper-based offline approval process

Workflow For Collaborative Resolution

Rationalize Deduction Reason Codes
  • Create a two-level hierarchy (category and reason code)
  • Create between a minimum of 10 and a maximum 100 reason codes
  • Do not create a customer-specific reason code as a main deduction reason code

Rationalize Deduction Reason Codes

Review Cash Application?s Impact

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 cash application The following is a summary of recommendations to consider:

  • Ensure that deductions are coded and residuals are posted to original invoices where appropriate
  • Ensure that cash application includes all the relevant backup
    • Capture BOL, POD, Payment files
  • Make sure that cash application references invoices, POs and A/R documents within the deductions case
    • Create matching algorithm to help in the linkage

Define Scope

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.

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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.