How does the AI sector regulate the banking and finance ecosystem in India?

Praveen Paulose,  MD & CEO of Celusion Technologies talks about How does the AI sector regulates the banking and finance ecosystem in India?

CIOL Bureau
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India is the second-largest country in the world in terms of population and it needs a robust financial infrastructure to manage the economy. With the increase in access to the internet, the banking and finance ecosystem is finally able to penetrate the underserved segments of the population. India has over 825 million internet users and 750 million smartphone users. Artificial intelligence is a powerful tool that has brought along a new wave of technology that has changed the way the banking and finance ecosystem operates. There are multiple areas where AI plays a major role.


Use of AI in eKYC

One of the key areas where AI has made a valuable contribution is in the development of a robust eKYC process. In January 2020, RBI came out with an amendment that allowed video KYC in lieu of paper KYC. This product gained momentum and wide acceptance in the subsequent months due to the lockdown that limited physical visits to banks/ financial institutions.

The AI-OCR tool captures, extracts, and produces an editable copy of the customer data based on the identification documents which are run against the databases to complete the KYC. The eKYC made it very convenient to digitally onboard customers whether it was opening a bank account or demat or trading account or a loan or insurance.


The replacement of paper KYC with eKYC has resulted in creating cost and time efficiencies and the elimination of paperwork. Most private banks and fintech lenders have switched to eKYC for digital onboarding. Whether you open a Demat account with Kotak securities or get a personal loan from LoanTap, eKYC is used to complete the onboarding process.

AI in automated credit checks to aid instant disbursement

With the proliferation of smartphones, lending platforms have gone digital to provide credit to the unserved segments of the population. Instant personal loans have become a popular short-term financing option.


These platforms make use of AI to run credit checks and confirm the creditworthiness of borrowers. These platforms usually complete the lending process in 15 minutes or less and require powerful decision-making engines. AI helps them to make the right decisions by studying the customer’s background, spending habits, and lifestyle from data available in the public domain.

Based on this an alternate lending data score is created based on which the loan is approved or rejected. Fintech lenders like KreditBee offer personal loans as low as Rs 1000 to borrowers with a net monthly income of Rs 10,000 in just 15 minutes. They use AI-based algorithms to assess the repayment capacity of their borrowers.

Use of AI technology like NLP to automate and regulate customer queries


The use of AI technology like NLP helps businesses to obtain a deeper understanding of customer needs by reading signals to understand the customer’s intent and guide them accordingly. This is the technology used by chatbots in banking systems to automate and regulate customer queries.

It is a transparent tool that allows you to present tailored offers to specific customers without any bias. This makes the entire process smooth as AI extracts meaningful information via NLP to move the customer in the right direction. This is the reason why chatbots can figure out what you want and guide you in the right direction.

AI-enabled biometric and visual analytics for authorization and authentication


 The use of AI-enabled biometric authentication technology is essential to prevent security breaches due to compromised credentials. According to a study by IBM over 20% of data breaches are on this account and it can take more than 9 months to identify and react to a data breach.

The use of AI-based security has gathered momentum and it is essential to remain competitive in the banking and finance ecosystem. Businesses that have not switched to AI-based security are putting their client data at risk for data breaches.

Investing in AI-based security solutions can save businesses millions of dollars. Identifying and implementing the right AI security solution for your business will help to protect your business data and save the company's reputation as well without any compromise on efficiency and accessibility.


Machine learning to detect frauds and cybersecurity

Machine Learning Algorithms have the capability to remember historical fraud patterns and identify them in future transactions. It can scan through humongous mounds of data at great speed to identify sophisticated fraud patterns that a human eye will not be able to detect. This makes ML extremely important to the banking and finance ecosystem where frauds are prevalent and need to be prevented. If we recall the frauds in the last few years that have roiled the banking industry in India, we will agree that the application of Machine Learning could have helped to prevent them by identifying the fraud much earlier.

Transaction analysis for risk monitoring


The use of AI in transaction monitoring allows financial institutions to manage their risk better. These solutions track customer transactions in real-time on a daily basis. They scrutinize current transactions as well as historical data and account profiles to arrive at the risk level of the customer.

This allows the financial entities to adopt a risk-based approach towards customers. The risk level of a customer would depend on several factors like the country and city of residence, nature of employment, the status of current debts, number of dependents, etc.

Based on the customer risk level, the entity can tweak the monitoring of the customer. Low-risk clients would require less monitoring compared to high-risk clients. The entity can take a call based on the market segment and the nature of the products on offer.

Big data analytics and machine learning tracking money laundering and malpractices

The banking and financial services industry is required to comply with anti-money laundering regulations. Money laundering is used by criminals to hide illegal funds derived from criminal activities like drug trafficking, flesh trade, terrorist financing, etc.

If any business is caught aiding or abetting these transactions, the punishment could involve fines and prison sentences for stakeholders as well the loss of goodwill. Using AI-based KYC, fraud detection mechanisms, and daily transaction monitoring help to identify these transactions early and weed them out. Such transactions need to be reported to the regulatory authorities immediately.

Artificial Intelligence is playing a pivotal role in the Banking and Financial Services Ecosystem by providing businesses with more information about their customers that can help to created tailored solutions for them.

The speed at which this information is collected, analyzed, and actioned in real-time is improving cost and time efficiencies on one hand and helping to address risks faster on the other. This is primarily responsible for the runaway success of fintech lending platforms. They have been able to harness the power of technology to onboard customers faster without compromising on the risk.

Most of the private and some of the large public sector banks In India have already adopted AI in their daily operations by way of chatbots and robotics software that manage millions of transactions on a daily basis. With growing customer expectations businesses have to aim at delivering superlative customer experiences to stay ahead of the competition and artificial intelligence provides them with the necessary tools to achieve this objective.