Eliminating Subjectivity from the Credit Review Process


How Fortune 1000 companies and SMEs automate credit and accounts receivable operations to improve productivity and reduce DSO and past-due A/R.

Contents

Chapter 01

Executive Summary

Chapter 02

Customer Onboarding and Credit Approval Process

Chapter 03

Eliminating Subjectivity from the Credit Review Process

Chapter 04

Improving the Invoicing and Payment Process

Chapter 05

Deciding Who to Contact on Any Given Day

Chapter 06

Collections Correspondence Strategies

Chapter 07

Doubling Down on Collections by Eliminating Waste from Cash-Application Process

Chapter 08

Eliminating Waste from the Deductions Process

Chapter 09

Leveraging a Connected Platform for All of Credit-to-Cash

Chapter 10

Collaborating with Buyer A/P teams

Chapter 11

Summary
Chapter 03

Eliminating Subjectivity from the Credit Review Process


In the previous section, we discussed how inappropriate assignment of credit limits to new customers could lead to higher bad-debt and DSO. This section is about problems associated with the credit review process for existing customers. Credit analysts are assigned hundreds to thousands of accounts for reviewing credit limits, onboarding new customers and unblocking blocked orders. Since reducing credit risk exposure is a responsibility of the credit team, credit review processes need to be airtight. However, the sheer volume of accounts makes it impossible for credit teams to successfully cover all accounts which are due for periodic reviews. Constantly chasing the backlog of accounts means that credit analysts are often unable to focus on conducting a focused and accurate credit analysis.

2.1. Top Challenges in the Credit Review Process

Only after an objective analysis can a credit manager make an informed decision about extending credit [or continuing the existing credit] to the customer. While inconsistency in periodically reviewing existing customer credit lines is an issue, asynchronous events such as financial results, rating downgrades, and M&A activity could also be responsible for escalating credit risk. Figure 4 illustrates challenges related to both asynchronous events and internal SLA requirements that create a need for credit analysts to manually prioritize accounts for credit review. Challenges with a Manual Credit Analyst Driven Process

Figure 4: Challenges with a Manual Credit Analyst Driven Process

2.2. How Top Organizations Handle the Credit Review Process

The first step that organizations undertake to remove the subjectivity out of the process, is to make sure that all the credit workflows reside within a system. The system generates a worklist for credit analysts for any given day and consists of:

  • New customer onboarding requests
  • Periodic credit reviews
  • Blocked order release requests
  • Alerts from external agencies on bankruptcies and rating downgrades
  • Expiry alerts on internal collateral including bank guarantees, mortgages and credit insurance
  • Process and System Driven Credit Operations

    Figure 5: Process and System Driven Credit Operations

    Figure 5 illustrates how the system automates the above workflows and assigns them to the respected credit analyst or manager and allows them to scale operations to thousands of accounts.

    2.3. Credit Management Success Stories: Air Products and TechData

    Air Products and Chemicals is a Pennsylvania-based global leader for industrial gas and chemicals. The credit team had to deal with a fair amount of wastage in the credit operations – getting approvals on credit limits with credit managers on emails, downloading credit agency data for a large portfolio of customers and was challenged with compliance and inaccurate credit data. The team faced an uphill task of controlling credit risk exposure in the absence of the right tools. Today, the team uses a single solution to employ a global credit policy and automated credit review process for 320,000 customers worldwide. Tech Data Corporation, currently ranked #108 in Fortune 500, is one of the world’s largest wholesale distributors of technology products. The credit team at Tech Data dealt with legacy systems and manual processes for credit reviews. Given a large portfolio of customers worldwide, the team had to daily log in to multiple portals for each geography to fetch data from credit agencies. The team automated credit data aggregation and workflows to achieve a productivity boost of 120% in the credit review process and also saved $160,000 annually through improved efficiencies.

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    HighRadius Integrated Receivables Software Platform is the world's only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway - covering the entire gamut of credit-to-cash.