Artificial Intelligence (AI) helps in predicting future trends based on analysis of past behavior of customers, and also helps banks to detect patterns in laundering, identify fraud, and make customer recommendations. These advantages are resulting in increasing deployment of AI in banking operations, which is driving revenue growth of the global Artificial Intelligence in BFSI market. AI understands customer behavior and allows banks to customize financial products and services by adding personalized features to build strong relationships with customers. Digital payment advisors, Artificial Intelligence bots, and biometric fraud detection mechanisms result in high quality of services to a wider customer base. AI helps in increasing revenue, reducing costs, and boosting potential of profit.

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The major objective of the Cognitive Systems & Artificial Intelligence In BFSI market report is to help the user understand the market in terms of its definition, segmentation, market potential, influential trends, and the challenges that the market is facing. This research is conducted to understand the current landscape of the market, especially in 2019 up-to the forecast year 2025. The readers will find this report very helpful in understanding the Cognitive Systems & Artificial Intelligence In BFSI market in depth. The data and the information regarding the market are taken from reliable sources such as websites, annual reports of the companies, journals, and others and were checked and validated by the industry experts. The facts and data are represented in the report using diagrams, graphs, pie charts, and other pictorial representations.

Global Artificial Intelligence in BFSI Market size in 2017 is 2.50 million US$ and it is expected to reach 19.80 million US$ by the end of 2026 with a CAGR of 29.52% during 2017 -2026. Artificial intelligence (AI) in BFSI refers to the simulation of human intelligence into machines with the help of sophisticated machine learning, deep learning, chat-bots, cognitive computing, and natural language processing algorithms that help in customer relationship management, communication, and recruitment & wealth management. Artificial intelligence in BFSI is driven mainly by digital data .Artificial Intelligence (AI) is fast evolving as the go-to technology for banks across the world to personalize experience for individuals. Positive rise of AI-based application in BFSI such as customer support, fraud detection, improving employee efficiency, reduce fraud and security risks. Growing adoption of smart devices and growing penetration of internet services across the globe is fuelling amount of the data. A number of financial services institution are already generating value from artificial intelligence.

GNW The global artificial intelligence (AI) in retail market attained $720.0 million in 2018 and is predicted to witness a CAGR of 35.4% during 2019–2024 (forecast period). The factors contributing to the growth of the market include the increasing investments in AI by retail companies and expanding e-retail industry. With AI, retailers have been able to automate their work processes, study consumer behavior, and capture relevant data through the adoption of numerous advanced technologies, such as machine learning, natural language processing (NLP), and computer vision. When technology is considered, the AI in retail market is divided into computer vision, NLP, machine learning, and others (which include gesture recognition and analytics). Machine learning generated the highest revenue during the historical period (2014–2018) and is expected to dominate the market during the forecast period as well.

GNW The global artificial intelligence (AI) in retail market attained $720.0 million in 2018 and is predicted to witness a CAGR of 35.4% during 2019–2024 (forecast period). The factors contributing to the growth of the market include the increasing investments in AI by retail companies and expanding e-retail industry. With AI, retailers have been able to automate their work processes, study consumer behavior, and capture relevant data through the adoption of numerous advanced technologies, such as machine learning, natural language processing (NLP), and computer vision. When technology is considered, the AI in retail market is divided into computer vision, NLP, machine learning, and others (which include gesture recognition and analytics). Machine learning generated the highest revenue during the historical period (2014–2018) and is expected to dominate the market during the forecast period as well.

The need to provide an enhanced customer experience is the primary factor augmenting the growth of the AI in BFSI market. As the competition among the market players is mounting day-by-day, companies have started to focus on providing a better experience to the customers to gain the customer loyalty. This encourages financial institutes to integrate advanced analytics tools and solutions to analyze customer data to fulfil their requirement, understand the customer experience, and to make smarter predictions about their behavior and requirements. Furthermore, companies are also looking forward to connecting with the customers on their choice of channels to provide a more seamless experience. Furthermore, as digitalization is spreading across the globe, customers are becoming more empowered.

The increasing usage of cloud-based solutions in the BFSI industry, rising demand for the data-driven solutions, increasing internet banking penetration, and scope of deriving market risk are fostering the market growth. The market is segmented into technologies, deployment types, verticals and regions. Globally, BFSI is the second most customer data-centric industry, where players have a bundle of new business opportunities from Cognitive Systems and Artificial Intelligence (AI). It is an evolving data driven technology that works on on-premises and cloud-based software. The system replaces the human thought process with a simulated digital model that includes a self-learning system, which derives patterns by using data mining, speech recognition, and language processing techniques. The cognitive systems require AI platform to derive the complicated business issues.