About The Customer
The customer in this case study is a global company that was handling a large volume of searches annually as part of their Customer Identification Program (CIP) and Diligence processes. The company was using traditional methods for these searches, such as World-Check and Lexis Nexis, which were manual and time-consuming. The company was looking for a solution that could automate these processes, handle the large volume of data, and improve the efficiency and accuracy of the searches. The company decided to implement DDIQ, an advanced AI solution, to meet these requirements.
The Challenge
The case study revolves around a company that was struggling with the automation of the Customer Identification Program (CIP) and Diligence processes across their global account population. The company was handling approximately 1,000,000 searches annually, which was a significant volume to manage manually. Prior to the implementation of DDIQ, the business was conducting manual searches via World-Check and Lexis Nexis. This traditional approach was not only time-consuming but also prone to errors, leading to inefficiencies in the overall process. The challenge was to find a solution that could automate the process, reduce the volume of relevant files to be reviewed, and save working hours, thereby increasing cost savings.
The Solution
The company decided to implement DDIQ, an advanced AI solution, to automate the CIP and Diligence processes. DDIQ was designed to handle large volumes of data and streamline the search process, making it more efficient and accurate. The AI solution was able to sift through the original documents, identify the relevant files, and significantly reduce the amount of data to be reviewed. This not only automated the process but also improved the accuracy of the searches, reducing the risk of errors. The implementation of DDIQ led to a significant reduction in the volume of relevant files to be reviewed and saved a considerable amount of working hours, leading to increased cost savings.
Operational Impact
Quantitative Benefit
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