Exiger Case Studies Efficiency Improvement in Customer Identification Process through DDIQ

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	Efficiency Improvement in Customer Identification Process through DDIQ Exiger

Efficiency Improvement in Customer Identification Process through DDIQ

Exiger

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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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.

About 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.

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.

Impact #1	The implementation of DDIQ brought about a significant transformation in the company's CIP and Diligence processes. The AI solution automated the processes, making them more efficient and accurate. The company was able to handle the large volume of data more effectively, reducing the risk of errors. The reduction in the volume of relevant files to be reviewed also meant that the company could focus more on other important tasks, improving overall productivity. The significant savings in working hours also led to increased cost savings, contributing to the company's bottom line. Overall, the implementation of DDIQ led to improved operational efficiency and cost-effectiveness.

Impact #1

The implementation of DDIQ brought about a significant transformation in the company's CIP and Diligence processes. The AI solution automated the processes, making them more efficient and accurate. The company was able to handle the large volume of data more effectively, reducing the risk of errors. The reduction in the volume of relevant files to be reviewed also meant that the company could focus more on other important tasks, improving overall productivity. The significant savings in working hours also led to increased cost savings, contributing to the company's bottom line. Overall, the implementation of DDIQ led to improved operational efficiency and cost-effectiveness.

Benefit #1	DDIQ reduced the amount of relevant files to be reviewed by 88.2%
Benefit #2	The company saved 192,233.43 working hours
Benefit #3	The implementation of DDIQ led to significant cost savings

Benefit #1

DDIQ reduced the amount of relevant files to be reviewed by 88.2%

Benefit #2

The company saved 192,233.43 working hours

Benefit #3

The implementation of DDIQ led to significant cost savings

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Overview

Efficiency Improvement in Customer Identification Process through DDIQ

Operational Impact

Quantitative Benefit