Case Study

Artificial intelligence cuts finance costs by 70%

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Who we worked with: 
A financial firm that manages accounts for 45,000 customers in 35 countries. 

What the company needed: Our client’s customer list was growing, but they were still spreading financial statements by hand. So they needed to speed things up and cut costs by automating financial spreading. 

How we helped: 
With our LiveSpread product, we automated and standardized 80% of their processes using Genpact’s patented extraction technology, computational linguistics, and domain expertise.

What the company got:
By processing 80% of their financial statements automatically, they cut costs by 70%. Which means they improved customer satisfaction, compliance, and on-time credit decisions.



Painstaking financial spreading was taking too long

In the fast-paced world of finance, your customers expect you to show them the money. Or they’ll show you the door. No one knows this better than our client, a finance firm with 45,000 customers across 35 countries.

With more and more customers clamoring for their services, they were looking for a better way to scale. Our client needed to quickly extract, interpret, normalize, and spread financials from different customers in different formats and languages, while keeping up with changing demands of local regulations. Their tools and manual efforts couldn’t keep up with the complexity of their global operations. 

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It was taking too many tedious copy-and-pastes and error-prone data entry to get numbers where they needed to be. Employee churn created the additional headaches of onboarding, training, and retraining the team, making it hard to keep everyone following credit policy to meet on-time credit decisions and compliance requirements.

Our client needed to do things differently.

They needed to do things faster. And more consistently.

They needed to automate.

A faster way to spread the numbers

Extract numbers, supporting information, and narratives from anyone, anywhere quickly. That’s what our LiveSpread solution helped this finance firm do. We automated the painstaking part of their financial spreading for both public and private companies, from taking the right numbers out of the right documents to formatting them into the right template and logging each step along the way. All thanks to artificial intelligence and our domain expertise.

Here’s the formula we used to make it work. 

Pull the right numbers 

Our client’s 45,000 customers send their financials in their own formats, from spreadsheets to images. So the first step is to extract the data. To do that, we use patented extraction algorithms that can find the right numbers in a way that’s easy to trace back to the source. They’re even smart enough to pull important content from footnotes. 

Normalize the numbers 

Next, we normalize the numbers, which gets them ready for an analyst. That means putting them into the right format, range, and template. And having every decimal and currency sign right where it’s supposed to be. 

All in a fraction of the time

Because they needed the solution yesterday, we gave them a head start with an out-of-the-box portal. And we helped them go live in under two months, a fraction of the time they expected. 

Everything they needed (and more)

Their new portal checks all the boxes, and then some. It lets them:

  • Pull data from anywhere, in any format 
  • Stay compliant with finance regulations by logging each step 
  • Follow industry rules for handling data for both public and private companies 
  • Upload the final results to their internal financial spreading and credit-scoring tools

80% automated = 70% saved 

The finance firm used our portal to speed through more than 100,000 financial statements from 45,000 companies in 35 countries.

Automation has helped them work exponentially faster—and with fewer errors. So now they’re more nimble with their numbers. And they’re ready to grow even more.

In the first year alone, they have: 

  • Cut spreading costs by 70% 
  • Processed 80% of financial statements automatically 
  • Standardized how their employees work 
  • Set themselves up to grow, without needing to add more people
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