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How AI in finance is delivering smarter investments and faster decisions

How AI in finance is delivering smarter investments and faster decisions

We are at the end of the era where people would speculate about how Artificial Intelligence (AI) will make a difference everywhere. AI is now an integral part of our everyday life, with its applications visible in smart assistants, fraud detection, healthcare research, farming, self-driving cars, and a host of other areas.

AI in finance, too, is no longer a futuristic concept; it is a reality. The use of AI is rapidly transforming the operations and services of banks, NBFCs, and other financial institutions. From reducing market timing errors to boosting performance, AI in financial services is facilitating faster decision-making and investments.

AI in financial services

In recent years, AI has been a driver of innovation in the financial services sector. Here is a look at all the areas where the clear influence of AI in finance can be seen –

  • Security – AI has enabled financial institutions to take a significant leap forward in security and fraud detection processes. By installing AI-powered systems, institutions can now ensure that millions of transactions are processed in real-time. With built-in red flags and indicators, these systems can identify patterns, analyze spending habits, and detect and prevent fraud even before the transaction is complete. 
  • Customer experience – Financial institutions are now able to do away with ‘one size fits all’ solutions, thanks to AI. With big data analysis, organizations can now zero in on customer preferences more efficiently. The use of advanced AI assistants with Natural Language Processing (NLP) capabilities can establish an almost human-like understanding of customer interests. This has helped financial institutions deliver a hyper-personalized customer experience.
  • Wealth management for all – With AI tools and platforms, financial institutions can now provide wealth management solutions at minimal costs. Once reserved for the rich and famous, wealth management services such as optimal portfolio diversification and tax planning are now accessible through AI-enabled robo-advisors.
  • Credit assessment – Using AI, financial institutions can now quickly get data on debt repayment patterns, employment history, and other online patterns. This helps these institutions assess credits more quickly, leading to faster loan approvals and broader applicant coverage.
  • Decision-making – AI in financial services has also made budgeting and forecasting processes more dynamic. AI tools can now analyze market trends, geopolitical developments and internal data in real-time. The use of AI models has enabled financial companies to get a better view of outcomes, resulting in more agile and informed decision-making.

The benefits of AI in finance have transformed the sector, making a significant impact on both internal and external affairs of financial institutions.

AI tools and technologies in finance

Different AI models, tools and technologies are used to deliver the benefits of AI in finance. Here is a look at some of them –

  • Machine learning and predictive analysis – Machine learning models are at the core of essential financial operations, such as fraud detection, credit scoring, portfolio optimization, and default prediction. AI time series models can analyze and predict future values in sequential data sets using Recurrent Neural Networks (RNNs). This is used in trend analysis and forecasting of stock movements, interest rates and liquidity needs.
  • NLP – The use of NLP is evident in the ever-increasing efficiency of chatbots and virtual assistants. NLP is also used to mine news and social media for sentiment analysis and build trading strategies.
  • Generative AI – The evident use of generative AI can be seen in customer support copilots, whether it be in email drafting or in chat responses. However, generative AI is also used in the financial sector to summarize business and market reports and create balanced datasets to detect fraud while maintaining confidentiality.
  • Robotic Process Automation (RPA) – RPA has simplified labor-intensive tasks in financial operations like KYC verification, compliance reporting and reconciliations.
  • Trading tools – Algorithmic and quantitative trading models use techniques like reinforcement learning and deep neural networks. These enable the models to generate trading signals, execute trades and re-optimize portfolios, all in a matter of milliseconds.
  • Cloud AI platforms – Whether using AWS Financial Services Cloud for fraud detection, or the Google Cloud AI for real-time payments monitoring, cloud AI platforms are now embedded into the inner workings of most financial institutions. Many Indian banks use Azure AI for compliance and analytics purposes.

AI for smarter investments and faster decisions

From the uses and benefits of AI in finance mentioned above, it is apparent that investments and decisions are faster and smarter with AI. The financial services industry is expected to increase its AI budget from $35 billion in 2023 to $97 billion by 2027. The use of AI will indeed aid the pursuit of smarter investments and faster decisions.

  • Perpetual data analysis – AI can be used to tap into live streams of market data, gaining real-time insights on stock prices, bond yields, crude and bullion prices, etc. This data can be gathered from sources such as news feeds, social media patterns, and macroeconomic indicators.
  • Risk and return modelling – The real-time analysis also extends to risk and return modelling. Unlike the traditional investment approach, which rebalances the portfolio periodically, AI-driven investment management operates in real-time. Sectoral correlation with index performances and volatility indicators is continually monitored in these systems, enabling investors to make faster and more informed decisions.
  • Auto-trade/auto-recommend – Investors can grant autonomy to algorithmic trading systems, which can then place trades automatically. Besides, these systems recommend trades and can also adjust your asset allocation in real time across equities, bonds, derivatives, ETFs, etc.
  • ​Simulation – AI tools can visualize millions of ‘what-if’ scenarios for market movement in a matter of seconds. This helps investors to make real-time decisions and manage risks more efficiently. For instance, if the Rupee depreciates now, there are AI tools that can tell you how your portfolio will be affected and what you can do to hedge the risk.

Building the finances of the future

With AI in finance, there are skepticisms about data privacy and algorithmic bias. Besides, integration costs may seem high for big enterprises. But it seems certain that AI is making finance more responsive, sharper and faster in all aspects. You can see this while reaching out to Tata Capital, across its mobile app, chatbot, phone and even Alexa. 

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FAQs

How does AI improve fraud detection in finance?

AI’s contribution to improving fraud detection is holistic. AI can process a large volume of data and still identify any deviation in patterns. It can detect anomalies that normally bypass the rules, thanks to machine learning and neural networks. AI tools consider multiple signals, such as device, location, amount, and time, which in turn reduces false positives in fraud detection.

What ethical considerations affect AI adoption in financial institutions?

AI adoption in India should be free from bias, which can be inherited from training data. Therefore, while AI is expected to bring about greater financial inclusion, poorly designed tools can exacerbate the disparity. Besides, AI adoption should respect the data privacy and consent rules, as financial data is highly sensitive in nature.  

Which Indian fintechs are leading in AI innovation?

Various Indian fintech companies are involved in different aspects of AI innovation. Companies like Skydo are recognized for their AI-driven cross-border compliance and payments solutions, while Laraware offers an end-to-end AI-powered banking platform. Cashfree provides real-time AI transaction risk scoring, while Signzy has innovated around AI onboarding, verification and anti-fraud APIs.

How is AI used in finance?

AI in finance is utilized in various areas, including fraud detection and security, credit scoring and lending decisions, investment and portfolio management, customer service and personalization, algorithmic trading, regulatory technology, and insurance claims processing, among others.

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