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Generative AI in BFSI Market Share

ID: MRFR//10661-HCR | 128 Pages | Author: Ankit Gupta| November 2024

In this deeply competitive scene, market share positioning systems are significant for organizations seeking to established areas of strength for an and gain an upper hand in the market. A few key procedures are being utilized to separate offerings and draw in clients. One predominant positioning procedure in the market is the attention on advance items tailored to explicit client fragments. Banks are developing customized advance offerings intended to meet the remarkable requirements of various customer socioeconomics, for example, individuals with varying credit profiles, income levels, and financial objectives. By customizing credit items to take care of explicit client fragments, loan specialists aim to position themselves as suppliers of tailored and adaptable arrangements, thereby attracting a different scope of borrowers seeking customized advancing choices.
With the increasing interest for comfort and effectiveness, moneylenders are prioritizing the improvement of advanced stages that offer consistent and easy to understand credit application encounters. By providing intuitive and dynamic application processes, banks aim to take care of the necessities of debtors seeking a problem free and facilitated credit application process. This emphasis on electronic lending and streamlined application strategies fills in as a vital driver in attracting clients who focus on comfort and openness.
Nevertheless industry-explicit targeting and key associations, client experience and client support are vital elements in market share positioning. Lenders are focusing on providing excellent client care and backing all through the credit application and reimbursement process, aiming to separate themselves by offering a customized and steady borrower experience. By prioritizing consumer loyalty and responsiveness, banks can assemble trust and devotion among borrowers, at last influencing client maintenance and reference business. This approach empowers loan specialists to situate themselves as suppliers of client driven and dependable lending arrangements, catering to the requirements of moneylenders seeking a positive and steady lending experience.

Covered Aspects:

Report Attribute/Metric Details
Growth Rate 26.90% (2023-2032)

Generative AI in BFSI Market Overview


Generative AI in BFSI Market Size was valued at USD 975.8 million in 2022. The Generative AI in BFSI Market is projected to grow from USD 1,205 million in 2023 to USD 10,564.5 million by 2032, exhibiting a compound annual growth rate (CAGR) of 26.90% during the forecast period (2023 - 2032). Ability of Generative AI in analyzing vast amounts of data to provide actionable insights, and capability of creating personalized financial solutions & recommendations to enhance customer experience & engagement is contributing to the growth of the Generative AI in BFSI market. These are just few of the market drivers that are driving the market.


FIGURE 1: GENERATIVE AI IN BFSI MARKET SIZE, 2019-2032 (USD MILLION)

Generative AI in BFSI Market Overview


Source: Secondary Research, Primary Research, MRFR Database and Analyst Review


Generative AI in BFSI Market Drivers


Ability of Generative AI in analyzing vast amounts of data to provide actionable insights is propelling the market growth


The ability of Generative AI to analyze vast amounts of data and provide actionable insights is a significant driver for its adoption in the Banking, Financial Services, and Insurance (BFSI) market. In the BFSI sector, decisions are often complex and need to be made rapidly. Generative AI can process enormous volumes of structured and unstructured data, such as transaction records, customer interactions, market trends, and economic indicators. By analyzing this data, Banking AI Applications can provide valuable insights to decision-makers, aiding in better risk assessment, investment strategies, fraud detection, and personalized customer offerings. Generative AI can identify patterns and anomalies in data that might go unnoticed by traditional methods. In risk assessment, this means more accurate evaluation of creditworthiness and potential loan defaults. For fraud detection, AI-driven Financial Services can quickly recognize unusual transaction patterns, helping to prevent financial losses due to fraudulent activities. Generative AI can analyze customer behavior, preferences, and transaction history to create personalized recommendations and offerings. This level of personalization enhances customer engagement, improves cross-selling and upselling opportunities, and ultimately increases customer satisfaction. Thus, this factor is driving the market CAGR.


Financial Technology AI can assist in creating personalized investment strategies based on an individual's risk tolerance, financial goals, and market trends. These strategies can be dynamically adjusted to reflect changing market conditions and the customer's evolving needs. Generative AI can identify patterns of fraudulent activities by analyzing large datasets. By recognizing anomalies and deviations from established spending patterns, these AI systems can proactively alert both customers and financial institutions about potential fraud, enhancing security. Generative AI-powered chatbots and virtual assistants can engage with customers in real time, providing them with instant responses to queries about account balances, transactions, investment options, and more. These interactions simulate human-like conversations, offering a seamless and responsive customer experience. Overall, Generative AI's ability to analyze vast amounts of data, simulate scenarios, and generate personalized solutions is driving its adoption in the BFSI sector. By offering tailored experiences, relevant recommendations, and innovative solutions, financial institutions can strengthen customer relationships, improve satisfaction, and gain a competitive edge in the market. Thus, it is anticipated that this aspect will accelerate the Generative AI in BFSI market revenue globally.


Generative AI in BFSI Market Segment Insights


Generative AI in BFSI Organization Type Insights


The Generative AI in BFSI Market segmentation, based on Organization Type, includes Banks, Insurance Companies, Financial Service Providers, and Others. The Banking segment held the majority share in 2022 in the Generative AI in BFSI Market data and is projected to be the fast-growing segment in the forecast period. Banks deal with massive amounts of data, including transaction records, customer profiles, market trends, and more. Generative AI can effectively analyze and interpret this data, extracting valuable insights that drive informed decision-making. Generative AI automates repetitive tasks, reducing the need for manual intervention in processes such as customer support, fraud detection, and compliance. This increases operational efficiency, reduces errors, and allows bank employees to focus on more strategic and value-added tasks. Generative AI automates repetitive tasks, reducing the need for manual intervention in processes such as customer support, fraud detection, and compliance. This increases operational efficiency, reduces errors, and allows bank employees to focus on more strategic and value-added tasks.


August 2023: Google’s Duet AI assistant now has major generative AI feature updates  aiming to help users with various tasks across Workspace apps. It can create slides, images, summaries, charts, and more, using natural language commands and Google’s influential AI models.


Generative AI in BFSI Application Insights


The Generative AI in BFSI Market segmentation, based on Application, includes Fraud Detection, Risk Assessment, Customer Experience, Algorithmic Trading, and Others. The fraud detection segment dominated the market growth in 2022 and is projected to be the faster-growing segment during the forecast period, 2023-2032. The fraud detection segment within Generative AI in the BFSI (Banking, Financial Services, and Insurance) market is particularly important and holds significant potential for transforming the way fraudulent activities are identified and prevented. Generative AI models can be trained to recognize patterns in normal financial transactions and behaviors. By continuously monitoring transactions and customer activities, these models can identify anomalies that deviate from the established patterns. Unusual transactions, such as large withdrawals, out-of-country purchases, or unusual login attempts, can trigger alerts for further investigation. Generative AI's real-time processing capabilities enable continuous monitoring of transactions and activities. This allows for immediate detection and response to suspicious transactions, reducing the window of opportunity for fraudsters to exploit vulnerabilities.


FIGURE 2: GENERATIVE AI IN BFSI MARKET, BY APPLICATION, 2022 & 2032 (USD MILLION)


GLOBAL GENERATIVE AI IN BFSI MARKET, BY APPLICATION, 2022 & 2032


Source: Secondary Research, Primary Research, MRFR Database and Analyst Review


Generative AI in BFSI Deployment Mode Insights


The Generative AI in BFSI Market segmentation, based on Deployment Mode, includes on-premise, and cloud based. The on-premise segment held the majority share in 2022 in the Generative AI in BFSI Market data and is projected to be the fast-growing segment in the forecast period. The on-premise segment in Generative AI in the BFSI (Banking, Financial Services, and Insurance) sector refers to the deployment of Generative AI solutions within the physical infrastructure of the financial institution itself, as opposed to using cloud-based or off-site solutions. In BFSI, real-time processing is essential for tasks like fraud detection, algorithmic trading, and customer interactions. Keeping Generative AI solutions on-premise can reduce latency since data doesn't need to travel to and from external cloud servers. This ensures faster decision-making and responsiveness to market changes.


Generative AI in BFSI Regional Insights


By region, the study provides the market insights into North America, Europe, Asia-Pacific, Middle East & Africa, and South America. North America Generative AI in BFSI market accounted for USD 310 million in 2022 with a share of around 31.76% and is expected to exhibit a significant CAGR growth during the study period. North America, particularly the United States, has a well-established tech ecosystem that fosters innovation. The availability of AI research institutions, technology companies, and venture capital supports the development and adoption of Generative AI solutions. Financial institutions in the region have access to extensive customer data due to the size and complexity of the market. Generative AI's ability to process and analyze this data fuels its adoption for enhanced customer experiences, risk assessment, and fraud detection.


Further, the major countries studied in the market report are: The U.S, Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.


Figure 3: GENERATIVE AI IN BFSI MARKET SHARE BY REGION, 2022 & 2032 (USD Million)


GLOBAL GENERATIVE AI IN BFSI MARKET SHARE BY REGION, 2022 & 2032


Source: Secondary Research, Primary Research, MRFR Database and Analyst Review


Europe Generative AI in BFSI market accounts for the second-largest market share. European financial markets have seen significant fintech growth. Generative AI supports these fintech companies by enhancing customer experiences, creating personalized services, and improving fraud prevention methods. Europe's interconnected financial markets require advanced risk assessment and fraud detection. Generative AI's real-time analytics and cross-channel analysis capabilities are valuable for identifying suspicious activities across borders. Moreover, Germany Generative AI in BFSI market held the largest market share, and the UK Generative AI in BFSI market was the fastest growing market in the European region.


Asia-Pacific Generative AI in BFSI market accounts for the third-largest market share and is projected to continue increasing due to rapid technological adoption and diverse consumer base. Countries like China, Japan, and Singapore have shown a willingness to embrace emerging technologies. Generative AI is leveraged for algorithmic trading, risk management, and customer engagement in these markets. Asia-Pacific has a large and diverse customer base with varying preferences and needs. Generative AI's ability to personalize services is crucial for addressing the diverse demands of this region. Further, the China Generative AI in BFSI market held the largest market share, and the India Generative AI in BFSI market was the fastest growing market in the region.


The Middle East & Africa Generative AI in BFSI market is rapidly growing due to digital transformation and increasing need for fraud prevention. The region is undergoing a digital transformation in the BFSI sector. Generative AI is adopted to modernize processes, improve customer engagement, and enhance operational efficiency. The Middle East & Africa region experiences specific fraud challenges. Generative AI helps detect irregular activities and combat fraud patterns unique to this market.


Also, The South America Generative AI in BFSI market is growing due to growing fintech landscape and increasing digital payments. Countries like Brazil and Mexico have expanding fintech ecosystems. Generative AI supports fintech companies in offering innovative financial products, improving customer experiences, and enhancing fraud detection. The adoption of digital payment methods is rising in South America. Generative AI is used to analyze transaction data for fraud detection and enhance customer security.


Generative AI in BFSI Key Market Players & Competitive Insights


Major market players are spending a lot of money on R&D to increase their product lines, which will help the Generative AI in BFSI market grow even more. Market participants are also taking a range of strategic initiatives to grow their worldwide footprint, with key market developments such as new product launches, mergers and acquisitions, contractual agreements, increased investments, and collaboration with other organizations. Competitors in the Generative AI in BFSI industry must offer cost-effective items to expand and survive in an increasingly competitive and rising market environment.


One of the primary business strategies adopted by manufacturers in the global Generative AI in BFSI industry to benefit clients and expand the market sector is to manufacture locally to reduce operating costs. In recent years, Generative AI in BFSI industry has provided Technology segment with some of the most significant benefits. The Generative AI in BFSI market major player such as Quantifind, OpenAI, Accenture, DataRobot, SAS, IBM, Microsoft, Adobe, NVIDIA, Intel, Google, and other market players.


OpenAI is an artificial intelligence research laboratory and organization that aims to promote and develop friendly AI for the betterment of humanity. OpenAI is known for its contributions to AI research, including the development of state-of-the-art language models like GPT-2 and GPT-3. These models are designed to generate human-like text and have demonstrated impressive capabilities in various natural language processing tasks. In June 2020, OpenAI released GPT-3, and marked a significant milestone in Generative AI. GPT-3 is one of the largest language models with exceptional capabilities in understanding and generating text, making it highly versatile across various language-related tasks.


Key Companies in the Generative AI in BFSI Market include



Generative AI in BFSI Industry Developments


August 2023: Google has launched its Search Labs in India & Japan, which will enable people in using generative AI capabilities in their respective local languages, by typing a query or using voice input.  


August 2023: Domo has launched Domo AI, a set of generative AI tools, that includes integrations with ChatGPT and other large language models to assist customers manage & deploy artificial intelligence models & improve decisions.


Generative AI in BFSI Market Segmentation


Generative AI in BFSI Organization Type Outlook (USD Million, 2019-2032)




  • Banks




  • Insurance companies




  • Financial service providers




  • Other Organization Types




Generative AI in BFSI Application Outlook (USD Million, 2019-2032)




  • Fraud detection




  • Risk assessment




  • Customer experience




  • Algorithmic trading




  • Other Applications




Generative AI in BFSI Deployment Mode Outlook (USD Million, 2019-2032)




  • On-premise




  • Cloud-based




Generative AI in BFSI Regional Outlook (USD Million, 2019-2032)




  • North America






  • US




  • Canada






  • Europe






  • Germany




  • France




  • UK




  • Italy




  • Spain




  • Rest of Europe






  • Asia-Pacific




    • China




    • Japan




    • India




    • Australia




    • South Korea




    • Rest of Asia-Pacific






  • Middle East & Africa




    • South Africa






  • South America




    • Brazil





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