AI Powered Contract Management

CASE STUDY

CLIENT | CONFIDENTIAL
INDUSTRY | INSURANCE
DATE | 2017 - 2019

Overview

This case study highlights the successful implementation of a contract management and analytics system utilizing Machine Learning (ML) and Natural Language Processing (NLP) for a confidential client in the insurance industry. The solution enabled the client to modernize their contract management process, improve analytics capabilities, and streamline operations.

The client is a global insurance company with a strong presence in the industry. They manage a vast number of insurance contracts, in paper form or as scanned documents. Due to the nature of these documents, extracting information and answering crucial questions was a time-consuming and labor-intensive task.

Challenge

The company faced several challenges with their existing contract management processes:

• Inefficient contract management: Contracts were either stored in paper archives or as scanned documents, making it difficult to access and analyze information.
• Limited analytics capabilities: Answering important questions, such as identifying risks, locating specific clauses, and quantifying the number of contracts containing specific terms, required extensive manual effort.
• High operational costs and delays: The manual nature of the process led to increased operational costs and delays in decision-making.

Approach

To address these challenges, the client decided to modernize their contract management and analytics capabilities by implementing a system that leveraged Machine Learning and Natural Language Processing. The approach involved:

• Digitizing paper-based contracts using Optical Character Recognition (OCR) technology to enable text-based searches and data extraction.
• Development of a contract index that combined both structured and unstructured data about contracts
• Implementing a Machine Learning (ML) algorithm to automatically classify contracts based on various factors, such as risk level, policy type, and coverage details.
• Utilizing Natural Language Processing (NLP) techniques to extract essential information from the contracts, including clauses, terms, and conditions.
• Developing search methods to match specific types of clauses in the database, when looking for specific wordings
• Developing a user-friendly interface for employees to access and analyze contract data efficiently.

Results

After implementing the AI-powered contract management and analytics system, the insurance company achieved the following results:

• Enhanced contract management: The digitization of contracts enabled the company to efficiently manage and access their documents, leading to streamlined operations.
• Improved analytics capabilities: The use of ML and NLP allowed for quick and accurate identification of risks, specific clauses, and the number of contracts containing specific terms, without manual intervention.
• Reduced operational costs and delays: The automation of contract analysis and data extraction reduced labor costs and sped up decision-making processes.
• Increased compliance and risk mitigation: The ability to quickly identify and assess contract risks enabled the company to address potential issues proactively and maintain compliance with industry regulations.

Conclusion

By implementing an AI-powered contract management and analytics system, the insurance company effectively modernized their operations, leading to improved efficiency, reduced costs, and enhanced risk management. This case study demonstrates the potential of leveraging advanced technologies like Machine Learning and Natural Language Processing to transform contract management processes in the insurance industry, ultimately leading to more informed and effective decision-making.