6th June 2024
Artificial Intelligence (AI) has made transformative changes across industries- automotive, pharmaceutical, retail, music, and many more. Its impact on financial services sector across the world is profound. AI has influenced various aspects of financial services sector, ranging from improving customer experience, strengthening risk mitigation mechanisms, better credit assessment techniques, devising new trading strategies and tapping new market segments. Given the dynamic business environment and rapid evolvement of technology, it is important to assess the benefits and challenges posed by AI to financial services sector.
AI refers to development of intelligent machines who are able to learn, identify, organize and analyse data, and thereby are able to predict based on the data driven insights. AI includes technologies like machine learning (ML), natural language processing (NLP), predictive analytics and robotic automation. According to International Data Corporation, the sales of software and hardware of AI systems will witness a steep increase from USD 166 billion in 2023 to USD 400 billion in 2027.
Financial Institutions worldwide are heavily investing on acquisition and deployment of AI technologies. Technavio expects the market share of AI in Banking, Financial Services and Insurance (BFSI) sector to grow at CAGR of 37 percent and reach the size of USD 32 billion by 2026. According to IMF, more than 50 percent of Hedge Funds across the world use ChatGPT for professional work. BNP Paribas Survey finds that about 67 percent of Hedge Funds use ChatGPT for preparing their reports and presentations. According to a recent EY report, more than 90 percent of European financial service institutions have integrated AI in their capital allocation decisions. Amundi SA, Europe’s largest asset management company, has announced that it will launch its suite of AI based financial products in the year 2025. HSBC has formed AI division early this year, which will integrate its customer data, analytics and customer relationship management division. Deutsche Bank is planning to employ generative AI to automate all its manual processes.
AI has brought about many positive changes in financial service sector. The below segment highlights the different ways by which AI has brought about paradigm changes in the financial services sector.
Improved Consumer Experience: Many banks, insurance firms and mutual funds are using AI powered chatbots and virtual assistants that offer customized financial solutions to the consumers. Financial institutions have effectively utilized AI to reduce response time and improve the consumer satisfaction level. For example, Tata Mutual Fund partnered with Haptik to offer AI powered chatbot to offer personalized financial services to the demanding market segment of digital first millennials.
Better assessment of credit worthiness: Many banks are using AI algorithms to analyse data from transaction records, utility payments, educational background, employment history and social media activity to better assess the creditworthiness of individuals. Such improved credit assessment has enabled banks to offer financial services to untapped and underserved market segments like immigrants, small and medium enterprises, college students and many others. Scotiabank, a Canadian multinational bank and financial services firm, is known for effectively using AI in improving its credit risk assessment process.
Automation of back-office operations: Financial institutions worldwide are using AI to automate day to day operations like invoice handling, KYC process, trade confirmation and settlement, reconciliation of financial records, approval of expense records, tax computation and payments, and many others. Such AI driven automation has improved operational efficiency, enhanced compliance and resulted in better services to customers. JP Morgan Chase, one of the renowned financial services firm, is known for using machine learning and robotic process automation to automate its backend operations work like data entry and reconciliation of transactions.
Devising new trading and investment strategies: AI algos use historical stock price data to identify patterns and make a better data driven trading decision. AI is better able to evaluate huge quantity of data in real time basis and are better able to time the market. Such decisions are free from human emotions and biases. Goldman Sachs has AI driven investment tool which uses data related to price, volume and economy to predict market movements and mitigate market risks effectively.
Improved regulatory compliance: Financial firms are using AI algorithms are utilized to scrutinize regulatory documents and extract relevant information. This ensures that the firms are able to adhere to regulatory rules and regulations. HSBC has collaborated with Silent Eight in using AI to automate regulatory compliance related issues. This collaboration has been ongoing since the year 2021.
Central banks and regulatory bodies have also taken an accommodative stand towards the use of AI. The Bank of Canada is using machine learning to detect irregularities in regulatory compliance by firms. Central Bank of Brazil launched a SupTech – Natural Language Processing Applications for Supervision project (SupTech-NLP) in 2020. Within the framework of SupTech NLP, the Central Bank of Brazil is working on developing a prototype which retrieves online financial consumer complaints and categorizes them. This enables the bank to have a better regulatory control over its financial system. In its recent project, the Bank for International Settlements (BIS) has found that AI can be effectively used to find out anomalies in financial transactions and detect money laundering. The European Central Bank is contemplating on using AI to have a better understanding of pricing behavior and inflation dynamics in the European Union market. Reserve Bank of India is also using AI in generating banking statistics.
However, the use of AI in financial services sector is not fraught from any kind of risks. There are growing concerns regarding privacy, transparency and data bias. It is important that the regulators are proactive and take steps to rule out any kind of discrimination. The intense use of AI brings with it the risk of cyber attacks. Financial institutions and the regulators must work together to strengthen their systems against any kind of cyber security risks. Limited digital knowledge and low level of financial literacy may entrap consumers and they may take up financial services without having a complete comprehension of its risk adjusted returns. It is important that regular consumer awareness campaigns are held in which the consumers are educated about fraudulent financial apps and deep fakes.
In summary, AI is transforming the financial services sector by enhancing efficiency, improving decision-making processes, and enabling new levels of personalization. However, adoption of AI also poses a lot of challenges and ethical concerns. Hence it is important that the financial institutions and the regulators across the world ensure fairness, accountability, and transparency in their AI deployments to maintain trust in the financial system.
