Global Generative AI in Financial Services Market By Type (Solutions and Services), By Application (Credit Scoring, Fraud Detection, and Other ), By Deployment Mode (Cloud and On-premises), By Region and Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends, and Forecast 2023-2032

Report Overview

Global Generative AI in the Financial Services Market size is expected to be worth around USD 9,475.2 Mn by 2032 from USD 847.2 Mn in 2022, growing at a CAGR of 28.1% during the forecast period from 2023 to 2032.

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Generative AI is increasingly used in the financial sector to enhance processes such as fraud detection, risk assessment, investment prediction & customer service. one of the main advantages of generative AI comes from its ability to analyze complex datasets & identify patterns that humans might miss. This allows financial institutions to make better decisions & reduce risk. The growth is fueled by the adoption of generative AI across financial applications as well as a growing demand for accurate and reliable financial services. IBM Corporation, Microsoft Corporation, and Amazon Web Services are among the major players in the generative AI financial services market. These companies are investing heavily in research & development to improve their generative AI abilities and expand their market shares.

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Driving Factors

Increasing Demand for Accurate and Efficient Financial Services

The increasing demand for accurate and efficient financial services is a major factor driving the adoption of generative AI by the financial services industry. Generative AI can analyze large amounts of data to identify patterns & anomalies. This helps financial institutions to make better decisions & reduce risk. Additionally, the increased availability of data as well as advancements in machine learning algorithms have made generative AI a more powerful & effective tool in financial applications. The demand for chatbots and virtual assistance powered by generative AI has also increased due to the growing popularity of mobile banking and the need for faster, more personalized customer service. For example, ARDEN was released in May 2022 by Brightwell Payments, Inc., an American financial services company that obtains financial solutions that allow money to be moved securely anywhere in the world. This AI-powered engine helps fintech protect its cardholders' & financial assets. These factors, as well as others, are driving growth in the generative AI sector.

Restraining Factors

Lack of Trust in AI-Powered Decisions

Despite the increasing adoption of generative AI in the financial services market, several factors limit its growth. One of the biggest challenges is the lack of trust in AI-powered decisions especially in sensitive financial areas like fraud detection & risk assessment. AI algorithms are difficult to understand and if they are not designed and tested properly can lead to unfair or biased outcomes. The high cost of implementing generative AI may be prohibitive to smaller financial institutions. The regulatory landscape for AI in finance continues to evolve which can lead to uncertainty & compliance issues. The lack of AI professionals with the necessary skills and the possibility that AI could replace jobs in the finance sector are all factors that could slow down the adoption.

COVID-19 Impact Analysis

The COVID-19 Pandemic has had an impact on the financial industry. Generative AI is no exception. The pandemic highlighted the importance of digitalization and the need for remote & efficient financial services. Financial institutions have adopted generative AI solutions in order to improve their operational efficiency and enhance their risk management capabilities. They also want to provide better customer service on the digital front. The pandemic also created new challenges in fraud detection and prevention. This has led to an increase in investment in generative AI-powered solutions for fraud detection. The pandemic, however, has also caused economic uncertainty & financial instabilities which have led to reduced resources and budgets for some financial institutions. In some cases, this has slowed the adoption of generative AI, especially for smaller financial institutions that may not have the resources & infrastructure necessary to implement these solutions. While the pandemic created some challenges, the pandemic also accelerated the use of generative AI by financial services highlighting the need to provide more efficient & digital services.

By Type Analysis

The Solutions Segment is Dominant

Based on type, the market for generative ai in financial services is segmented into solutions and services. Among these types, the solution segment is the most lucrative in the global generative ai in financial services market, with a projected CAGR of 32%. The total revenue share of the solutions segment is 76.4% in 2022.  Software tools are responsible for the high share as they help to deploy AI-enabled banking solutions to extract accurate & complete data from a large amount of data on time. Some solutions help businesses to do things like growing retail banking with next-best-action software, detecting and combating financial fraud, or improving client relationships with multichannel customer experiences. In the forecast years, it is expected that it will grow at a significant rate The managed service will grow rapidly due to its ability to administer AI-enabled fintech apps.

By Application Analysis

Forecasting & Reporting is Dominant in Global Generative AI in Financial Services Market

By application, the market is further divided into credit scoring, fraud detection, risk management, forecasting & reporting, and other applications. forecasting & reporting segment is estimated to be the most lucrative segment in the global generative ai in financial services market, with a market share of 30% and a projected CAGR of 29.5%, in 2022. The rise of the segment can be attributed to many factors such as increased operational efficiency, better-informed decision-making, and increased revenue. Business analytics, AI and Big Data are used by many companies to make better decisions. The fintech market is experiencing significant growth which has led to the expansion of AI in this area. Customer behavioral analytics is expected to grow significantly in the next few years.

By Deployment Mode Analysis

The On-premises Mode is Dominant

Based on deployment mode, the market is segmented into cloud and on-premise. Among these modes, the on-premise mode is estimated to be the most lucrative segment in the global generative ai in financial services market, with a market share of 57% and a projected CAGR of 28.3%, in 2022. On-premise deployment helps enterprises install software or services in a financial institution’s systems or premises. The cloud segment will have the fastest CAGR between 2022 and 2032. The growth can be attributed to AI algorithms that learn from historical data within a cloud environment & detect current standards. They also make recommendations. Cloud computing and AI can increase productivity, efficiency, and digital security when it comes to data handling & authenticity. This automated technique also eliminates human error during data processing.

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Global Generative AI in Financial Services Key Market Segments:

Based on Type

• Solutions
• Services

Based on Application

• Credit Scoring
• Fraud Detection
• Risk Management
• Forecasting & Reporting
• Other Applications

Based on the Deployment Mode

• Cloud
• On-premises

Growth Opportunities

Increasing Availability of Data and the Demand for More Accurate Financial Services

The increasing availability of data & the demand for more accurate financial services are two of the main growth drivers. This trend will continue as financial institutions endeavor to improve their fraud detection, risk management, and customer service capabilities. As more investors look for data-driven insights in order to make informed investment decisions the use of generative AI is anticipated to increase. The adoption of AI-powered virtual assistants & chatbots in financial services is another growth opportunity. These can provide faster & more personalized customer service. As the regulatory landscape for AI in finance becomes more clear, it will create new opportunities for generative AI products that can help financial institutions meet regulatory requirements more efficiently.

Latest Trends

Rising Usage of Machine Learning and Natural Language Processing (NLP) to Develop Chatbots

The use of machine learning (ML) and natural language processing (NLP) to create more advanced chatbots is one of the latest trends in the generative AI market in financial services. These AI-powered tools help improve customer service by reducing response times & personalizing interactions with customers. Another trend is to use generative AI for developing predictive models in credit risk assessment, fraud detection, and investment predictions. These models can analyze large amounts of data to provide more accurate predictions. In the financial services sector, explainable AI (XAI), which refers to AI systems that can provide a clear explanation of how they made their decisions is gaining popularity. This is crucial for building trust and reducing the risk of unfair or biased outcomes. The use of generative AI in algorithmic trading which is a growing trend as financial institutions strive to develop more advanced trading strategies is also on the rise.

Regional Analysis

North America is Dominant Region in the Global Generative AI in Financial Services Market

North America is anticipated to be the most dominant region in the global generative ai in financial services market with the largest market share of 40% and is projected to register a CAGR of 29.6% during the forecast period. The region's dominance is due to the strong emphasis placed on R&D-derived innovations in developed economies such as the US & Canada. These countries have the fastest-developing and most competitive AI technology for financial services. Many startups and emerging companies are also providing AI services to the financial sector. Asia Pacific is estimated to register the highest CAGR between 2022 and 2032. This growth is attributed to the rapid adoption of digital payment systems & the increased penetration of internet-based services.

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Key Regions and Countries Covered in this Report:

• North America
  • The US
  • Canada
  • Mexico
• Western Europe
  • Germany
  • France
  • The UK
  • Spain
  • Italy
  • Portugal
  • Ireland
  • Austria
  • Switzerland
  • Benelux
  • Nordic
  • Rest of Western Europe
• Eastern Europe
  • Russia
  • Poland
  • The Czech Republic
  • Greece
  • Rest of Eastern Europe
• APAC
  • China
  • Japan
  • South Korea
  • India
  • Australia & New Zealand
  • Indonesia
  • Malaysia
  • Philippines
  • Singapore
  • Thailand
  • Vietnam
  • Rest of APAC
• Latin America
  • Brazil
  • Colombia
  • Chile
  • Argentina
  • Costa Rica
  • Rest of Latin America
• Middle East & Africa
  • Algeria
  • Egypt
  • Israel
  • Kuwait
  • Nigeria
  • Saudi Arabia
  • South Africa
  • Turkey
  • United Arab Emirates
  • Rest of MEA

Market Share & Key Players Analysis:

Financial service-providing businesses are hindered by the increasing competition in the finance industry owing to the need for improved financial operations, cost savings, and client engagement. These characteristics are responsible for the risk of underperformance in an increasingly competitive business environment. In recent years, participants in the market have formed partnerships & collaborated to gain a dominant position. In April 2022, Gupshup announced the acquisition of Active.Ai a private finance company specializing in AI. The acquisition will enhance Gupshup’s Customer Experience (CX), which is offered to BFSI clients.

Market Key Players:

• IBM Corporation
• Intel Corporation
• com
• Narrative Science​
• Amazon Web Services, Inc.​
• Microsoft
• Google LLC
• Salesforce, Inc.
• Other Key Players

Recent Developments:

• Virgin Money and SurePay will partner in June 2022 to protect consumers from fraud & misdirected payments online. SurePay's Confirmation Of Payee (CoP), a real-time service that checks names in real-time provides UK payers more pledge that their payments go to the intended recipients.
• In April 2022, Cross River and Sardine will build a critical risk and payment infrastructure for Fintech, Web3, Crypto, and Fintech companies. Sardine will use Cross River's payment portal in part of its unified fraud-prevention software for fiat or crypto transactions.

Report Scope: