Revolutionizing India’s Financial Sector: Alok Bansal CEO of Visionet BPS on the Power of AI and ML
The surge in the incorporation of Artificial Intelligence (AI) and Machine Learning (ML) across various economic domains can be attributed to several factors, notably the increasing abundance of digital data and enhanced computational capabilities. Leveraging these tools for delivering financial services holds significant advantages, impacting not only the Banking, Financial Services, and Insurance (BFSI) sector but also benefiting society on a broader scale.
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Alok Bansal, CEO Visionet BPS
Aligned with the expansion of AI and ML, major global banks are actively integrating these into their existing business ecosystem. According to data from the intelligence startup Evident, J P Morgan Chase stands number one in incorporating and advancing AI and machine learning, with an average yearly budget of $12 billion spent on technology, a figure that has surged significantly to a substantial US$15.3 billion in 2023. The report further highlights that not only prominent American banks but also smaller European banks have established their own in-house AI research centres.
The advent of digital tools is also showing a significant impact on Indias banking sector, which is expected to have one of the strongest growth rates, at 6.3 percent in 2024, according to a report by Deloitte on the Banking and Capital Markets Outlook.
“Were observing the influence of AI and ML technologies across different facets of banking operations within the BFSI sector in India. This spans from accelerating the know-your-customer (KYC) process during customer onboarding to enhancing back-office operations. AIs abilities to detect and flag fraudulent transactions, monitor and address regulatory compliance requirements, and predict future trends and customer needs are among the widely accepted solutions already,” says Alok Bansal, CEO Visionet BPS.
Several prominent banks in India have outlined strategies to integrate cutting-edge AI and ML models into their operations. According to recent reports, in August 2023, the Reserve Bank of India (RBI) engaged McKinsey and Accenture to design systems leveraging AI and ML for its supervisory functions. The apex bank aims to harness the potential of artificial intelligence and machine learning to analyse its extensive database, enhancing regulatory oversight over NBFCs.
“The integration of AI and ML has markedly enhanced the precision and effectiveness of risk assessment and management. These technologies handle vast datasets in real time, not only saving time but also minimizing losses. Additionally, they decrease the margin of error. Another noteworthy feature of AI and ML is their ability to continually learn and adapt. These systems evolve, incorporating new data and adjusting their algorithms accordingly,” adds Alok.
Prioritising customer satisfaction, ML algorithms meticulously analyse market trends and economic indicators. This empowers financial institutions to make well-informed investment decisions and dynamically adjust their strategies to introduce more tailored products in real time. Simultaneously, AI-powered tools evaluate customer behaviour to detect potential risks or shifts in spending patterns, facilitating the implementation of personalized risk management strategies.
However, amidst the considerable advantages, AI also poses specific challenges. “Ensuring the ethical use of data and safeguarding customer privacy are crucial. Stringent ethical guidelines and data protection measures are necessary in the BFSI sector to ensure the responsible execution of AI and ML practices,” he said.
Alok believes that India will swiftly establish a comprehensive legal and regulatory framework for AI and ML. “With more refined policies in place, AI and ML will continue to lead the way in innovation, contributing to the creation of a safer and more efficient financial world for the future,” he concludes.
