Case Study

A financier cashes in on cash applications

Tuned-up technology, a $96 million pay-off—and more to come

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Who we worked with

A major equipment financier.

What the company needed

To get more out of legacy technology and cut back on rejected cash applications.

How we helped

We analyzed and cleansed the company’s data and created a two-layer auto-application algorithm, streamlining the cash application process.

What the company got

A dramatic drop in manual cash applications, amounting to annual savings of $96 million—for starters.

A leading equipment financier was receiving more than half its payments in the form of checks, which were then automatically entered using an algorithm. The auto-application logic was sound, but the rejection rate was still 15%. That meant the company had to manually apply 40,000 open items a month. The system was inefficient, expensive, and caused controllership issues.


Fine-tune a legacy system to stop rejecting checks

Streamlining the cash application process—and the technology involved—was essential, but changing the batch algorithm on the client legacy system was not an option. 

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A deep-dive analysis and a three-pronged attack

Genpact and the company ran a Lean Six Sigma project to tackle the issue. We analyzed more than 40,000 records—100% of the sample—statistically, trend-wise, and from a business perspective. And we captured 36 possible
causes for the rejections in nine different processes. Based on this analysis we suggested a three-step solution.

  • Conduct a one-time data analysis and cleansing
  • Build a second layer to the cash application algorithm without modifying the primary batch algorithm
  • Enhance auto cash application logic, to reduce the cash team’s manual transactions

Internal process flows and hand-offs were streamlined, and policy changes were recommended to deliver even greater impact. 


Great savings, with much more to come 

Since undertaking this project, the company has autoapplied an additional $96 million in cash annually. And as the program expands and the company makes suggested changes to process flows and hand-offs, it could see that amount increase to $384 million annually with reduced manual processing.