AI in BFSI Market Overview
Artificial intelligence (AI) in banking, financial services and insurance (BFSI) is projected to grow significantly in the coming years. Positive rise of AI-based application in BFSI such as customer support, fraud detection, and improving employee efficiency, buoyed the AI in BFSI market.
Based on technology, the AI in BFSI market is segmented into machine learning (ML), natural language processing (NLP), predictive analytics, and machine vision. Of these, machine learning to witness highest adoption in the BFSI industry in the coming years, owing to its ability to conduct thorough due diligence for approving loans, creating interactive user interface (UI), and chatbots. Machine learning is also being used to derive algorithms to build an optimum financial portfolio, which is critical for wealth management. Also, NLP is projected to register fastest growth during the forecast period, attributed to its application in speech processing which is used for secured bank authentication and transaction.
Based on solution, AI in BFSI market is categorized into chatbots, customer behaviour analysis, customer relationship management (CRM), data analytics and visualization, and fraud detection. Chatbots is the most commonly used solution in the BFSI industry. Chatbots learn from past interactions and experiences with customers, by collecting and analysing the data. AI analyses this data to learn the behaviour of the users and in turn helps to adapt to the needs of the end users. Furthermore, CRM is projected to be the fastest growing category during the forecast period, owing to benefits of AI-based CRM such as establishing customer-centric business model, increase in lead conversion, and overall improved customer experience.
Based on end use, AI in BFSI market is categorized into banking, insurance, and wealth management. Among these categories, banking was the largest adopter of AI technologies. Globally, growing population and economic prosperity led to surge in customer base in the banking sector. This has enforced banks to provide high level of service quality to customers round the clock. However, providing 24*7 service could be tedious task incurring high human resource cost, high capital expenditure on infrastructure, resulting in small/negligible profit margins for the banks. With the adoption of AI, banks are able to offer personalized assistance, without incurring heavy expenditure.
Globally, several governments ledfinancial institutions are using AI for understanding money laundering patterns, in order to trace down the flow of money which is earned illegally or via unethical practices. As the banking system is shifting from rule-based to AI-based computing, financial institutions would be able to detect fraudulent transactions accurately and at a faster pace. This would significantly reduce frauds in BFSI industry which would reduce bank’s cost, and also safeguard bank’s reputation. Therefore, the need to curb cybercrime and AML set to drive the AI in BFSI market.
AI in BFSI Market Dynamics
The need to provide enhanced customer experience to stay competitive is a major factor driving AI in BFSI market. AI extracts data from data silo, which provides customer insights and further helps in creating personalized experience at every possible customer touchpoint. As individual banking varies from person to person, AI is being used for creating personalized content. For instance, mobile app-based personalized notifications are build based on past interactions with the customers. Hence, BFSI companies are aggressively investing in AI in order to enhance end user experience.
Market players are investing in technologies such as NLP and deep learning, which are considered as crucial technologies for image and voice recognition, to develop a system that can understand human emotions and recognize or anticipate intentions, all while having a conversation with the customer. This would make banking more efficient and safer. Furthermore, NLP is a key technology for building an intelligent virtual assistant and chatbots. Also, by using NLP and deep learning technologies, automation of key workflows across the BFSI industry can be achieved, which would offer key insights into customer needs & preferences. Therefore, NLP and deep learning technologies poses wide range of opportunities for the market players in AI in BFSI market.
AI in BFSI Market Competitive Landscape
Major players in AI in BFSI market such as Google Inc., and Microsoft Corporation, are focusing on mergers and acquisitions in order to gain market share, and also increasing their spending on R&D activities to stay competitive. For instance, Google Inc., a subsidiary of Alphabet Inc, acquired Halli Labs, an AI and machine learning based solution provider, in 2017; this would enhance company’s expertise in the field of deep learning and machine learning technologies.
Some of the other key players operating in the AI in BFSI market are Amazon Web Services Inc, IBM Corporation, Avaamo Inc, Baidu Inc, Cape Analytics LLC, Oracle Corporation, Intel Corporation, Lexalytics Inc, SAP SE, and Salesforce.com Inc.
The report will also provide a country-wise analysis. Some of the major countries that are covered in the report include the U.S., Canada, Germany, France, U.K., Spain, Switzerland, Italy, China, Japan, India, Singapore, South Korea, Australia, Brazil, Mexico, Saudi Arabia, U.A.E.