Predicting Dilution is key for Invoice Finance Solutions

Trade Financing Matters welcomes this guest post from Sabeen Ahmed, COO  and Chief Credit Officer of Interface Finance Group

There are few truisms left anymore especially in this era where Trust is at a premium and everything appears to be a product of Fake or Fiat news. But in terms of the risk, funding receivables based on Seller’s data or funding receivables based on Buyer’s data, there is truth and that truth is Buyer data is more reliable. Why?  The simple reason is that helps in predicting dilution.  In this day where new forms of invoice finance are the rage, there are many things that can go wrong with financing receivables. One of Trade Financing Matter’s more popular posts is 12 Risks to Manage when Financing Domestic Trade Receivables.

Naturally, there are a number of differences between traditional and digital invoice finance services when it comes to onboarding, processing, underwriting and funding. Digital invoice finance players are designed to provide funding during a single (sometimes two) online session(s). As such, they don’t really have the ability to fully address invoice quality and verifiable deliverables, which are important components of invoice finance underwriting and risk mitigation.

In addition, simply pulling invoices from the sellers accounting systems (ie seller centric approach of the like of Bluevine and Fundbox who are integrated with 3 or 4 cloud accounting systems or IFG who is integrated with 11 and has the ability to instantly pulling data from the majority of desktop accounting systems), may help speed up the process but can’t really tell you if the invoices have been approved and scheduled for payment by the buyers (account debtors).

Obviously, integration with the buyers account payable system either directly or via third party platforms offers the ability to pull a lot of additional information about approved invoices.

But even when invoices have been approved and scheduled for payment, the risk of dilution still exists. Post-confirmed invoice dilution can take a number of forms including credit memos, nonspecific invoice related chargebacks, withholdings, counterclaims, tax issues, judgments and so on.

Some of the more advanced players are trying to address this issue in a number of ways. IFG, for instance, does so through a fully automated Digital Supply Chain Finance service based on fast data and a Dynamic Credit Limit engine. Previse’s data scientists have opted for big data and machine learning.

Clearly, this critical issue is getting more attention and the rate of progress is quite exciting but, as of yet, no single solution has been tested on a large scale in the market.

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Voices (2)

  1. Glenn D Blackman:

    Understanding and managing dilution levels is why invoice financiers always tend to be able to recover their money in a failure situation, making it a very attractive place to invest your money. Unfortunately lending that is unsecured or secured by personal guarantees is likely to face many more problems recovering their funds, when we face the next economic downturn.

  2. Ken So:

    Good insights, Sabeen. There is indeed a growing emphasis from banks and non-banks to evaluate/deploy innovative approaches to predict dilution. We at Flowcast have built out a solution that is based on a machine-learning based approach harnessing transaction data beyond buyer systems. We are deploying that at a large institution…so stay tuned.

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