Early Pay Finance Ain’t Easy: Understanding Customer Deductions

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Every industry is affected by customer deductions. Called a variety of names by companies — including deductions, chargebacks or short-pays — from the perspective of a digital lender focused on invoice finance, understanding the nature of deductions is a first start to building smart underwriting and dynamic lending capabilities.

Why? Deductions mean a diluted invoice value. The nature of a deduction can differ dramatically. Trade promotions and allowances are really deductions that are part of doing business, and the issue here is actually about making sure mistakes are not made. On the other hand, companies have various compliance deductions related to everything from how a shipment is packed to on time delivery penalties that can greatly reduce the value of an invoice.

The Credit Research Foundation (CRF) together with the Attain Consulting Group recently conducted a survey of more than 200 companies and found that across all respondents, non-trade-related deductions represent 0.25%–0.5% of sales (so for a $100 million company, that’s $500,000).

The top non-trade deduction types by both number and dollar of deductions taken during the most recent year were concealed shortages or transportation related:

Rank By Volume By Value
1. Concealed Shortages Concealed shortages
2. Transportation, freight, or routing Transportation, freight or routing
3. Early or late delivery Early or late delivery
4. EDI/ASN errors Full carton shortages
5. Full carton shortages EDI/ASN errors

Source: CRF deductions study

Survey Insights

  • While trade-related deductions are part of the cost of doing business, non-trade deductions add significantly to the workflow of any AP department. Companies have varied business practices to assess the costs of these deductions, which can impact future invoice values
  • Retailers are notorious for deductions. With thousands of suppliers and many SKUs to manage, some form of discipline is required for companies to manage all of their inbound traffic. While deductions are a form of financial punishment, they could also be viewed as a revenue source
  • Companies try to reduce the manual processing costs of chargebacks by establishing allowance policies with their customers. The most common allowance reported in the CRF study was for defective returns. I know from shopping at Costco that membership has its privileges (i.e., no questions when returning merchandise for anything), because suppliers must accept the returns decided during the procurement/sales negotiation process
  • The study also found suppliers frequently offer their customers a discount for early payment, such as 2/10 net 30, and find their customers often take this discount even when they do not pay within the required terms and are therefore not entitled to the discount. Seventy-five percent of the companies attempt to get their money back, and 65% of these companies said that they have been fairly successful in collecting them back
  • Companies frequently state that their existing ERP systems or AR packages do not provide the functionality needed to effectively manage deductions. Whether it is the ability to track the status of a deduction throughout the process, edit reason codes or automatically pull customer claim information or signed PODs from portals, many traditional systems fall short

Machine Learning and Dilution Prediction

Today, much of supply chain finance is done off the back of buyer payment guarantees and focused on only very large suppliers. This creates potential accounting issues and events like Abengoa and Carillion. It also limits a buyer’s flexibility to manage adjustments post-invoice approval (called post-confirmation dilution by lenders).

New finance solutions are looking to extend working capital for all suppliers using analytics to predict post-confirmation dilution. Work is now underway to enable the ability to find important patterns for dilution and defaults in invoice payments to critically contribute to improving credit underwriting processes.

This goes well beyond deduction survey data and involves analyzing large data sets of properly prepared, unbiased payment data at a transactional, level including dilution and default data as a key ingredient of success.

Companies like Previse, Flowcast Labs and The Interface Finance Group are leading the way when it comes to work around here, and this in turn will improve the quality of credit scoring with additional components based on the use of machine learning.

It’s still early days, but given the end to a long benign credit cycle, having this data will be critical for digital lenders.

David Gustin runs a research and advisory practice centered on helping financial institutions, vendors and corporations understand the intersection of trade credit, payments and the financial supply chain. This post was written while David worked on a special project with The Interface Financial Group.  He can be reached at dgustin (at) globalbanking.com

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