Genpact's Contract Assistant uses built-in artificial intelligence to extract, analyze, and reconcile contracts with a high degree of accuracy. It applies computational linguistics, pattern recognition, and machine learning to extract contract terms and validate them against invoices and other data.
The Genpact team used a structured assessment process to adapt this solution to our client's specific trade promotion requirements. Key steps included:
- A business readiness assessment for the deployment of digital tools
- A recommended target operating model, governance model, and implementation plan
- A 10-week proof-of-concept exercise that automated the trade promotion process for two retailers
We used the Genpact Cora platform—and a holistic end-to-end approach—to automate each part of the process. Genpact Cora features a modular, interconnected mesh of technologies that tackles each business challenge and automates the following steps.
- Contract creation: The system receives promotion information from an online portal, interprets the information, creates a contract, reviews it and finalizes it.
- Trade pay: The system receives each customer invoice, extracts data from it and its associated contract, and interprets this information to identify validation criteria.
- Proof of performance: The system retrieves third-party market research data (from a separate application), performs price and quantity validation, and uploads the contract, invoice, and compliance template.
- Payment: On successful three-point validation, the system triggers payment.
Our proprietary data extraction, pattern recognition, and language correction capabilities helped overcome input issues such as poor-quality scans and damaged documents. That minimized exceptions.
In the end, we successfully demonstrated how the system would not only improve efficiency and accuracy, but also how the new centralized data repository would support predictive analysis. Even better, machine learning means the system will improve continuously.