According to the market study reports, the global market for Artificial Intelligence in BFSI (Banking, Financial Service, and Insurance) is expected to go beyond USD25 million by 2024. The AI in the BFSI market is largely driven by the growing demand among the financial institutes to advance customer experience, achieve customer loyalty, as well as high level of competition among the key market players. Today, financial institutions are seeking cutting-edge technologies to offer a better experience and retain customers.
The study also unveiled that the expansion in the various related industry is also expected to reflect positively on the sales of Global AI in BFSI product over the next few years. Additionally, an increase in the digital data and spending by the venture capitalists in AI and fintech market space are also responsible for driving the market growth. Even, the growing in partnership between financial institutes and fintech companies to incorporate technology into the core financial services will also cultivate the growth of the global market for Artificial Intelligence in BFSI. In the Global AI in BFSI market, the solution segment led the market with over 85 percent stake revenue in the year 2017. From wealth management institutes to banks, and insurance companies are adopting AI solutions to evaluate the customer behavior and meeting their requirements and also offering a personalized experience. The solution market involves Chatbots, customer behavior analytics, CRM, Data Analytics and visualization, and fraud detection solutions.
As per the study report, Machine learning technology accounts for about 40 percent share in the AI in BFSI market, due to the rising demand for the technology in the integration of the intelligent algorithms for risk mitigation and compliance, anti-money laundering, and fraud detection applications. Natural Language Processing (NLP) is also utilized widely in the BFSI sector in the customer contact center to consider the customers for solving their queries. In addition, financial institutions are also using NLP for back-office applications and operations, and text-mining.