Many businesses are constantly searching for ways to simplify and automate their workflows and cut operating costs as the world becomes more digital. Customer identification and verification, often known as KYC, has significantly advanced in recent years.
KYC stands for Know Your Customer which is a procedure for validating a customer’s identification, and it is an essential aspect of any financial business partnership. During the KYC verification process, data is extracted manually by collecting and verifying documents like ID cards or passports.
An effective KYC procedure may help protect your bank or financial institutions against a variety of financial crimes, such as identity theft, fraud, and money laundering. But the problem is that the KYC procedure is time-consuming and complicated. It takes a lot of money, time, and resources to manage a huge volume of data manually.
So, now what is the solution?
Automation is the best solution to this problem. Yes, you heard it right. With modern technological advancements, the data extraction process can be easily automated, making client onboarding and verification procedures much more efficient and effective.
One of our clients also experiences this same situation and wants a solution to this problem. Hence, in this client case study, we demonstrate how we use Google OCR technology and AI techniques to help one of our clients automate their data extraction process for KYC documents.
Problem Statement:
Our client is struggling to handle a huge volume of data that requires the authentication of various types of documents on a daily basis. The data is provided in various formats, and the number of attributes in each document varies. All the necessary information needs to be entered manually and then stored for future verification. This entire procedure will be time-consuming, repetitive, as well as challenging if a document contains a large amount of data to validate.
Hence, to address this issue, the client contacted SmatBot to help automate their entire data extraction and management for the KYC verification process.
Proposed Solution
We propose a solution for automating the data extraction process from KYC documents using Google (Optical character recognition) OCR technology and AI techniques. Our solution automates the data extraction process in real-time, eliminating the need for manual entry and storage of data.
Solution Approach
The following are the steps:
Step 1: The uploaded document will be segmented and then categorized based on the format of the data.
Step 2: In the next step, the Google OCR technology will be used to extract all the available texts that are present in the uploaded document.
Step 3: After extracting the text, the next step is to filter out the necessary fields such as Name, DOB, etc., along with their respective values, from the uploaded document. This process is accomplished using AI techniques. We filter out the required data, and the data is automatically captured along with its respective field and value.
Step 4: The last step, which completes the verification process of KYC documents, is to display the fields that were captured.
Overall, this solution automates document categorization, data extraction, filtering, and capturing processes to expedite the KYC document verification process. This reduces the time and effort required to perform manual data entry.
Conclusion
In a highly regulated sector, onboarding new customers might be challenging and time-consuming. Thankfully, technological advancements are making it possible for financial institutions to employ the right automated solutions like SmatBot that provide a wide range of advantages at a considerably lower cost than conventional operations.
Moreover, automation of KYC document verification may help your company achieve regulatory compliance while lowering costs, increasing productivity, freeing up human resources, and improving efficiency.