The financial services sector has always been at the forefront of innovation, constantly exploring new ways to enhance customer experiences and improve operational efficiency. However, with the digital age in full swing and AI capabilities advancing at an unprecedented rate, the industry is poised for a transformational shift. To stay ahead of the curve, the sector can leverage AI to futureproof itself in many ways.
AI-powered investment and trading decisions
One of the primary advantages of AI in the financial services sector is its ability to transform the decision-making process. AI can be used to analyse market trends and make predictions about the performance of various financial instruments. This can help traders and investors make informed decisions about buying and selling, leading to higher returns and reduced risks. Moreover, AI can be used to identify potential investment opportunities, and optimise funds and portfolios much better than previously used techniques.
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Financial analysts can leverage AI-powered research tools to augment their knowledge about the market. Advanced AI solutions can comb through large volume of structured and unstructured data and summarise findings on the market sentiment and trends. Using AI infused quantitative and algorithmic trading, traders can optimise their strategies to the real-time market changes for better outcomes.
Risk management
With AI, banks can make informed decisions about investments and risks to significantly improve efficiency and accuracy. AI can identify patterns that humans might miss helping banks identify potential risks in services like underwriting and take necessary measures to prevent financial disasters. In the case of lending institutions, it can ascertain creditworthiness of borrowers by analyzing relevant data points. In case of insurance industry, AI can improve operational efficiency by helping in insurance pricing, claims processing, claims adjudication, policy servicing, damage analysis, automating inspection process, and more.
AI-powered hyper-automation for financial processes
AI can automate highly complex workflows that are usually not possible with rule-based automation systems. It can work with large volumes of data and interact with other downstream financial software for approving expenses and processing invoices. AI can help prepare concise reports and accounting statements, calculate various financial metrics, detect financial health, and cash flow, build financial models, run simulations and many such similar activities.
Fraud, anti-money laundering prevention
A significant application of AI in the financial services sector is fraud detection and prevention. For example, AI algorithms can be used to monitor transactions for anomalous patterns and flag suspicious transactions in real-time, thus enabling immediate action. This can help banks prevent financial crimes such as money laundering, credit card fraud, and identity theft.
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By GlobalDataStreamlining compliance and regulations processes
The financial services sector is subject to strict regulations and compliance requirements. AI can be used to automate compliance checks, file mandatory reports, check if reporting is done as per standards, and aid in auditing. Routine processes like KYC, different types of authorisations can be completely automated. This can help banks avoid penalties and legal liabilities, ensuring they comply with regulations while providing high-quality services to customers.
Improving customer experience and robo-advisory
Conversational AI assistants can handle customer queries, provide personalised recommendations, and even complete transactions without human intervention. The rise of generative AI will boost conversational AI as chatbots begin to identify customer intent and context to provide hyper-personalised responses to queries once they get powered by generative AI.
This can significantly reduce waiting times for customers and enhance their overall experience. AI can also analyse customer data to identify their preferences, interests, needs, and even predict customer churn. This can help banks tailor their products and services to meet their customers’ personalised finance needs, improving customer loyalty and retention.
Risk mitigation through responsible AI
However, there are some challenges to consider when implementing AI solutions in the financial services sector. One of the most significant challenges is data privacy and security. Financial institutions handle sensitive information, and any data breaches can have significant consequences.
To mitigate this risk, FSI’s must ensure that their AI systems are designed to be secure and compliant with data protection regulations. Another challenge is ensuring that AI algorithms are transparent and explainable. They must also be able to explain how AI algorithms arrive at their decisions, especially when making critical decisions that can impact customers’ financial well-being. Explainable AI can also help build trust with customers and regulators, which is essential for maintaining a healthy and sustainable financial services sector.
In conclusion, AI has enormous potential to transform and future-proof the financial services sector. It can help banks make informed decisions, prevent financial disasters, detect, and prevent fraud, and enhance customer experiences. However, companies must be mindful of the challenges and risks associated with AI implementation, including data privacy and security and explainability. By developing a clear strategy for AI implementation, financial institutions can reap the benefits of AI while mitigating risks and ensuring compliance.
Balakrishna D. R. (Bali) is Executive Vice President – Global Head AI and Automation and ECS, Infosys
