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How We Built an Intelligent Automation Solution for KYC Validation

By Sriram Sitaraman Feb 15, 2019
How We Built an Intelligent Automation Solution for KYC Validation
How We Built an Intelligent Automation Solution for KYC Validation

Financial institutions sift through a huge volume of documents as a key part of their operational processes. More importantly, the need for regulatory compliance means there is very low tolerance for error in these tasks.

However, document verification and processing for KYC validation, insurance claims, customer onboarding etc. are time-consuming processes across enterprises. By recent estimates, 26 days is the average customer on-boarding time for financial institutions. Organizations are also spending a lot on these processes, as they retain large teams to do the work manually. And scaling up operations just means employing more people.

Is there a way around these challenges?

Intelligent Automation Solution

While Robotic Process Automation (RPA) has a mainstream role in automating many of the manual processes in the BFSI sector. But this particular task requires AI with advanced Machine Learning algorithms to understand the documents in context. This is Intelligent Automation solution - blending AI with automation, which can create solutions that can read the documents, understand the content in context, and find patterns in the data.  

At Srijan, we created a POC for an Intelligent Automation solution for (KYC) validation, that can automate a key portion of the process. The solution employs deep-learning algorithm to scan documents and images uploaded by end-users, and classify them into pre-programmed categories.

Here’s a look.



The solutions is designed using the following technologies:

  • Convoluted Neural Network (CNN) using Python and TensorFlow
  • OpenCV for Computer Vision
  • OCR and MRZ packages

How It Works

The solution uses a combination of deep-learning based image recognition and classification models as well as Optical Character Recognition (OCR).  It is capable of:

  • understanding given text or image material

  • acting upon it according to a pre-trained set of rules

Let’s say we are working with passports submitted during the KYC process. Here’s what the solution does:

  • Scanning - to extract personal details and passport expiry dates

    • “Read” the passport, extract different sections of the main page, using OCR to read certain sections

    • Computer Vision solutions leveraging OpenCV are used to read the machine-readable zones in the passport

    • Deep Learning algorithms leveraging Tensorflow framework and OpenCV extract the photograph from the passport, as well as identify any “Cancellation” or other stamps

  • Compare extracted information with information available in the database, to validate submitted proof document

  • Based on the above comparison and validation, the solution can classify the document submitted, in this case the passport, as verified, expired, cancelled, or a data mismatch.

  • Cases that cannot be categorized with appropriate degree of accuracy or confidence are marked for manual classification

  • In case of manual intervention, a workflow is created where the operations team can validate manually and classify them

  • The model learns from manual classification, and over time can spot patterns and closely mirror the manual results. This is accomplished by automated retraining of the model including the newer data and manual classification data

How This Helps

With the KYC validation solution, enterprises can automate repetitive manual processes, achieving:

  • Speed: Faster turnaround at most stages of manual processes, to solve scalability challenges and time-critical needs. For example: document verification in 1/10th of the time taken manually

  • Accuracy: Rule-based algorithms executed by software makes sure that there is near-zero margin of error in processes

  • Efficiency: Intelligent automation means tasks are done efficiently, compliant to standard processes, and with minimal need for manual intervention. For example: reduce manual efforts for KYC verification by 70%

  • Resource Management: As repetitive processes are automated, organizations have the freedom to utilize their human resources for more value-added tasks.

Automation just a segment of the KYC validation can bring in a host of significant benefits, as outlined above. But the solutions can be extended to other BFSI operations, or even other industry use cases to deliver similar gains:

  • Passport checks at airports

  • Processing insurance claim documents

  • Reconcile financial statements

  • Resolve credit card disputes

  • Any other manual & repetitive processes that require documents to be validated or reviewed

Have repetitive manual processes that you think can be automated? Looking to increase cost saving on operations without compromising quality and productivity?

Let’s start the conversation on how Srijan’s experts teams can help identify key opportunities to deploy intelligent automation for your business.

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