Nov. 9, 2020, 10:07 a.m.
OCR + Facial Recognition = NextGen e-KYC
The BFSI sector is marred with incidents of money-laundering and nefarious activities. “The estimated amount of money laundered globally in one year is 2 - 5% of global GDP, or $800 billion - $2 trillion in current US dollars.[1]” And one of the major technologies that when implemented effectively, can reduce risk of money laundering, fraudulent activities, identity theft, and financing of malicious activities, is KYC, because it helps identify risks and get a clear understanding of customer behavior.
In fact, in 2018, US agencies, including the Federal Reserve, issued a joint declaration to motivate financial institutions that adopted AI-enabled solutions to enable the KYC process. This further gave a tailwind to the e-KYC technology on a global scale. The COVID-19 pandemic-induced social-distancing norms led the FATF (Financial Action Task Force) to issue an official statement to accelerate the adoption of technologies by financial enterprises. Of the various technologies adopted, two in particular have been transforming and strengthening companies’ e-KYC capabilities: facial recognition technology and OCR (Optical Character Recognition) technology.
Through the course of this article we take a closer look at the various use cases for these technologies, the business opportunities that their fusion can create and the far-reaching impact that can be creating by leveraging a customized e-KYC tool.
The facial recognition market is expected to touch a value of USD 8.5 billion by 2025 [2]. From student attendance tracking to tracking miss people and pets, the technology has widespread use cases, across different industries. It is being leveraged by law enforcement agencies for the detection and prevention of criminals and nefarious activities, schools and offices are leveraging the same to track attendance, banking sector uses it extensively for security and identity validation, and so on and so forth.
Similarly, OCR tech is touted to find increasing adoption with experts opining that the global OCR market would reach a value of over USD 50 million by 2030. OCR enables extensive data digitization, identity verification and can assist visually impaired by reading out printed text, translate languages, help manage and quickly sift through large piles of documents, remotely guide students in the post-pandemic age where there has been a rise in long distance education.
But apart from just leveraging the technologies individually, combining them with complementing tech can create further value-add.
By recognizing this value-add that can brought about by the combined use of facial recognition and OCR technologies, at MathCo, some of the industry’s top minds created the voluntary, app-based digital Know Your Customer (KYC) solution. Adeptly fashioned in our in-house innovation lab, our AI-based authentication can accurately and easily identify the customers that walk into a store. Fueled by a deep neural network, the deep learning model is feed-forward, i.e., information flows through the model.
Here’s a deep dive into the process that goes into creating this tool:
Therefore, by analyzing videos, the tool enables the automation of customer logs and also issues security alerts when a nefarious activity is detected.
The tool can also improve operational efficiency in the banking sector. Consider how banks have enabled customers with the option of performing most banking operations from the comfort of their homes, to tackle prolonged wait times. And this comfort of banking from home has become vital since the outbreak of the COVID-19 pandemic, given the need for social distancing. Setting up a robust e-KYC system can further reduce the number of customers that walk into banks, while still improving levels of customer satisfaction and ensuring operational efficiency, because,
While the advantages are many, there are measures that firms need to be mindful of when looking to leverage e-KYC.
For instance, one of the types of financial fraud that e-KYC tools might be vulnerable to is when fraudsters use their own face but map it to false information, i.e., false IDs and/or manipulated documents. There is the danger that the e-KYC tool might map the fraudster's image to the manipulated document and falsely classify it as verified. Fraudsters can create multiple accounts with the same face, in this manner, and without having proper measures in place, this could even go unnoticed, result in money laundering, and other financial fraud.
Setting up methods such as 1:N identity matching algorithms, can help prevent such fraudulent scenarios from taking place in facial biometrics verification systems. By mapping out similar face matches, organizations can sift through and identify potential fraudsters.
Also, consumer data collated through e-KYC processes, needs to be stored securely, protected from data breach incidents. Regular alerts need to be sent to consumers on cross-verifying identities of anyone posing to be a KYC official, before sharing sensitive information, lest fraudsters dupe/steal their money.
By setting up security measures to guard against e-KYC fraud, companies can derive maximum benefits from setting up a customized e-KYC tool, and ensure high levels of consumer satisfaction.
1. “Overview.” United Nations : Office on Drugs and Crime, n.d. https://www.unodc.org/unodc/en/money-laundering/overview.html#:~:text=The%20estimated%20amount%20of%20money,goes%20through%20the%20laundering%20cycle.
2. “Facial Recognition Market.” Market Research Firm, n.d. https://www.marketsandmarkets.com/PressReleases/facial-recognition.asp.
Ranjith is leading the initiative of building the nextgen innovation lab at MathCo.– incubating viable and cool solutions that can generate long term revenue flow is what he is really passionate about. A Coffee aficionado, F1 and motorsport enthusiast, organic terrace farming has been a new found interest since lockdown. When off work, he spends time learning to learn from his 1.5 year old toddler.
Adithi works as an Analyst at MathCo.'s in-house innovations lab, a perfect fit for her as she loves dabbling with AI, experimenting with new technologies and building analytics problem-solving capabilities. Off work, Adithi loves dogs, movies, and listening to k-pop. On any given day, she can be found wondering about human existence, or as to when she might eat her next pizza.
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