By Uday ChaudhariThe fourth Industrial Revolution has taken over the old school business models all over the world. Businesses across industries and verticals are currently turning to Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Big Data, and other modern technologies to streamline operations. Global banking and financial sectors are no exceptions when it comes to transforming their business models to offer a digital-first experience to customers.
The banking sector in India has also experienced a radical shift, and the very definition of banking has changed. The country has witnessed the emergence of numerous FinTech Non-Banking Financial Companies (NBFCs). The four different variants of analytics – Descriptive, Diagnostics, Predictive, Prescriptive Analytics are speedily becoming an integral part of India’s BFSI Industry, and ML is immensely supporting to set the benchmark. It is applying the learning, based on the historical data to suggest plans and analyse different consequences.According to IDC estimates, the global machine learning market was valued at $1.58B in 2017 and is expected to reach $20.83B in 2024, growing at a Computed Annual Growth Rate (CAGR) of 44.06% between 2017 and 2024. Numerous versatile sectors, along with BFSI, are relying on machine learning algorithms to derive insights from the data that will help improve business outcomes, personalize customer experiences, and run a robust cybersecurity strategy.
One of the business houses of the Indian economy has launched its latest mutual fund, powered by AI and ML This fund is proactively supported by quant models that can be linked together to form a whole automated process. It combines multiple rule engines and predictive models to create portfolios for investment that maximize returns and minimize losses during the market’s downtrend.
Its machine language is powered with predictive algorithms to decide the prevailing market conditions and macro-economic conditions to portfolio what is likely to outperform during every next month. The long position in the selected portfolio is taken only for months where the predicted return is positive. On the other hand, during months when negative returns are predicted, the strategy uses derivatives to hedge the previously held gross long-equity position. The ML algorithm ran in real-time for the prediction and then was flashed through the mobile app for a better update on every situation. Machine learning supports acceleration to run various other models as well for a speedy and more accurate solution.It is not that only the major business players are taking such initiatives. More and more companies are slowly adapting the use of ML for more accurate credit decision models on the data collection to regulate the credit valuation of the customers to help them avail loans. A leading Fintech that accelerates digital transformation for leading names in the BFSI, embraced ML, is investing heavily in R&D through its Financial Innovation Labs for futuristic growth.Thanks to technological support, cloud technology has been built out rapidly by various IT companies, enabling various organisations to rethink their cloud strategy. Organisations today can, therefore, buy further into the open-source arena, and adopt APIs to develop microservices for topics, such as ESG. The gen-Z cloud-based services will also encourage banks and financial institutions to embrace better machine learning and other analytics tools for the smart handling of money.
An enabling, simple, and efficient solution has always been the call of the hour. When the technological aspects of the market scenario were reflecting a growth trend, the 2020 pandemic forced to take a plunge to make the ML its priority to conduct the business. While all the industries are trying their best to keep up with the unforeseen situation, BFSI was no exception.
Indian banks have taken measures to focus on maintaining several situations, such as taking care of the critical staff at branches, temporarily redeploying staff to manage online or phone inquiries from customers. The Covid situation has added several other restrictions, to follow social distancing norms by implementing video collaboration tools, messaging, and chat software, and other fintech innovations to continue live interactions with customers.
The BFSI industry can leverage machine learning for better services and solutions. It has stretched its arms in various directions and is potential to grow in the form of:
* Risk management and fraud detection * Credit management * Algorithm-based marketing * Comply with every changing regulation * Enhance customer satisfaction, and so on.
The possibilities and the scope are infinite when it comes to the support of machine learning to upgrade BFSI in India. It will be a game-changer for organizations that are looking to remain competitive and profitable. It has already proved its worth, and it promises to help banks cut costs and drive efficiencies. As anticipated, ML has indeed carved the path to ensure support in any future storm and redefine their value to customers in an ever-shifting Indian BFSI industry.
The author is Senior Director, Technology, SynechronDISCLAIMER: The views expressed are solely of the author and ETCIO.com does not necessarily subscribe to it. ETCIO.com shall not be responsible for any damage caused to any person/organisation directly or indirectly.