Know Your Customer, Prevent Financial Crimes

Customer Identification in the Indian Banking Industry using AI


Customer Identity Verification


In the Indian banking industry, customer identification refers to the process of verifying the identity of a customer who wishes to open a bank account or avail any banking service. This process is mandated by the Reserve Bank of India (RBI) and is aimed at preventing money laundering, terrorist financing, and other illegal activities.

The customer identification process involves collecting and verifying various types of information and documents, including the customer's name, address, date of birth, PAN (Permanent Account Number) or Aadhaar (Unique Identification Number), and photograph. In addition to these basic details, the bank may also collect additional information about the customer's occupation, income, and source of funds.


The RBI has issued guidelines on customer identification that require banks to adopt a risk-based approach to customer due diligence. This means that the level of scrutiny applied to each customer may vary based on the perceived level of risk associated with their account. For example, a high net worth individual may be subjected to greater scrutiny than a low-income individual.


The process of customer identification in the Indian banking industry typically involves the following steps:


1. Collecting basic information: When a customer approaches a bank to open an account or avail any banking service, the bank collects their basic information such as name, address, date of birth, and contact details.


2. Verifying identity documents: The bank then verifies the customer's identity documents such as PAN card, Aadhaar card, passport, or voter ID card. The bank may also collect additional information about the customer's occupation, income, and source of funds.


3. Risk profiling: Banks in India are required to adopt a risk-based approach to customer due diligence, which involves assessing the level of risk associated with each customer. This is done based on factors such as the customer's background, occupation, and transaction history.


4. Enhanced due diligence: For customers who are identified as high-risk, banks may perform enhanced due diligence measures such as obtaining additional information and documentation, conducting background checks, and monitoring transactions more closely.


5. Record keeping: Banks are required to maintain records of customer identification documents and transaction details for a minimum period of five years.


6. Reporting suspicious transactions: If a bank detects any suspicious transaction or activity, it must report it to the Financial Intelligence Unit (FIU) and take appropriate action.


Problem in Customer Identity Matching using AI

OCR (Optical Character Recognition) technology is dependent on the quality of the image being scanned or captured. Low-quality images can pose a challenge for OCR technology, as the software requires clear and well-defined characters to accurately recognize and extract text.


Some of the common problems faced with OCR capability for low quality images are:


Blurry or distorted text: Images that are out of focus, blurred, or distorted due to image quality issues or poor lighting conditions can lead to inaccurate OCR results.

Handwritten text: OCR technology is designed to recognize printed or typed text, but it may not accurately recognize handwritten text.

Poorly scanned or captured images: Images that are poorly scanned or captured due to low-resolution settings, shadows, or other distortions can also result in incorrect OCR results.

Text in different languages or scripts: OCR technology may not be able to accurately recognize characters in different languages or scripts, particularly if the characters are not well-defined or are stylized.


TeXtCK Capablitity to save resources, time and cost

We are solving the unstructured customer data problem to make it possible to be processed by AI ML programs efficiently to reduce manual tasks and the resources , unlikely majority of the noisy data are often not readable or poorly processed that requires extra burden on these institutions to conduct manual verifications and regular followups.


1. OCR capability can help to improve efficiency, reduce errors, and save time and resources for OVD(Officially Valid Document) as proof of identity and address by the Indian government. Examples of OVDs include Passport, Driving License, Voter ID Card, and PAN Card. OCR technology can be used to extract information such as the name, address, date of birth, document number, and other relevant details from these documents.

2. Our OCR technology enables the quick and accurate capture of text from images, reducing the time and effort required for manual data entry. This can save significant amounts of time and reduce the risk of errors associated with manual data entry.

3. We help to automate the processing of documents, such as invoices, receipts, and forms, by extracting relevant data and metadata. This eliminates the need for manual processing, saving time and resources.

4. Our Customizable search parameters technology provide advanced search options, such as proximity search, Boolean search, and phrase search. These options can help users find specific information faster and more accurately.

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