Artificial intelligence (AI) has transformed the financial services sector over the past decade. From automated transactions to high-end analytics and customised financial offerings, AI now forms a core part of the financial services domain. With technological advancements, the future of AI in finance holds even more positivity in the form of breakthroughs and innovation. For Indian companies, this presents the potential to enhance efficiency, customer experience, and profitability. But it is also accompanied by challenges that must be tackled with care to ensure the ethical use of AI in finance.
AI-driven automation in finance
One of the biggest contributions that AI has made in finance is the automation of monotonous and time-consuming processes. Financial institutions that adopt AI-powered automation, as per a report by PwC, can cut operational expenses by as much as 30%. This not only improves productivity but also enables businesses to deploy resources better.
Banks are implementing AI-driven systems to perform tasks like data input, reconciliation, and compliance reporting. RPA software is assisting banks in automating back-office functions, reducing the chance of human errors and speeding up transactions. AI chatbots are also revolutionising customer support by delivering real-time support for common inquiries, allowing human representatives to work on more sophisticated problems.
Personalised customer experience
Accenture, in a study, discovered that 67% of the customers of financial services businesses expect personalised experiences. They are now able to get their expectations fulfilled due to AI tools. For instance, AI systems are able to monitor customers’ spending habits and give them customised budget tips or recommend investments based on their risk profile and objectives. In wealth management as well, robo-advisors use AI to create personalised investment portfolios, providing high-quality financial advice.
Predictive analytics for better decision-making
Predictive analytics is another strong use of AI in finance. Through the analysis of past data and trend identification, AI systems can predict market trends, evaluate credit risk, and aid strategic decision-making.
Stock exchange platforms are applying AI to forecast the movement of stock prices through market data, sentiment analysis from news, and macroeconomic variables. Lenders are also using AI models to accurately assess creditworthiness, reducing the risk of defaults and enhancing loan approval procedures.
A Deloitte study indicated that banks and financial institutions utilising predictive analytics to manage credit risk saw a 20% reduction in loan rejection or approval error rates. The facility is of more use in growing markets such as India, where access to classical credit scores and related information is limited.
Fraud detection and cybersecurity
The growing adoption of online transactions and online banking means that a great deal of attention needs to be paid to avoiding cyber fraud. AI is essential in improving security as it can identify suspicious transactions in real time. AI-based fraud detection platforms scan patterns of transactions to recognise signals of fraudulent activity. The systems employ machine learning (ML) algorithms that learn from new information continuously and get better at identifying threats in advance. As per IBM’s 2024 Cost of a Data Breach Report, businesses employing AI-driven security solutions see 29% quicker breach detection and containment, resulting in major cost savings.
Various banks employ AI-powered software to screen real-time transactions and instantly raise alarms for suspect fraud. The RBI has also promoted using AI to carry out risk management, leading to a more secure financial system.
AI in investment management
The investment management sector makes use of AI for portfolio optimisation and market analysis. Quantitative analysis is a very technical field that employs AI to interpret market data and formulate strategies for maximising returns and minimising risk. Software can carry out trades at high frequency with accuracy, taking advantage of market conditions quicker than any human would have been able to. They also take emotion out of the equation, resulting in greater consistency when investing.
AI-based investment platforms are also making financial markets more accessible to the masses. Individual investors can employ robo-advisors to create personalised portfolios without having to possess an in-depth market understanding. AI is helping with narrowing the gap between professional and individual investors, enhancing financial inclusion.
Regulatory compliance and reporting
Regulatory compliance is a vital element of the financial sector. Banks have to follow strict rules concerning anti-money laundering (AML), know your customer (KYC), and data privacy. AI simplifies compliance procedures by automating data analysis and reporting.
In India, the RBI has issued guidelines promoting the use of AI in compliance to ensure higher transparency and lower the risk of regulatory violation. Financial institutions that embrace AI solutions can lower compliance costs and avoid regulatory scrutiny.
Conclusion
The future of AI in finance is full of possibilities. Thanks to automation, personalisation, predictive analytics, and enhanced security, AI is revolutionising the financial industry, opening up new business opportunities and delivering greater value to consumers.
For Indian commerce, including NBFCs, the utilisation of AI-based technologies will contribute to greater operation efficiency and will allow for upgraded credit assessment procedures. For the online marketplace enterprise, AI utilisation is possible to provide secure transactions and personalised services, leading to customer faith and engagement.