New York, June 12, 2023 (GLOBE NEWSWIRE) -- According to MarketResearch.Biz, the Generative AI in Financial Services Market reached a valuation of 847.2 Million in 2022 and is expected to grow at a CAGR of 28.1% from 2022 to 2032, surpassing USD 9,475.2 Million by 2032.
Generative AI has become an invaluable asset in the financial industry for enhancing processes such as fraud detection, risk analysis, investment prediction and customer service. One major benefit of generative AI is its ability to quickly analyze large datasets & recognize patterns humans might miss - helping financial institutions make more informed decisions and reduce risk.
Adopting Generative AI into financial applications and satisfying demand for accurate and dependable services has propelled its rapid adoption. IBM Corporation, Microsoft Corporation, and Amazon Web Services are major players in this generative AI financial services market and invest heavily in R&D to advance their capabilities and expand market share.
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Key Takeaway:
- By type, in 2022, the generative ai in financial services market was dominated by the solutions segment due to extracting accurate & complete data from a large amount of data.
- By application, the forecasting & reporting segment dominated the largest market share in application analysis
- By deployment mode, the on-premises segment dominated the largest market share
- In 2022, North America dominated the market with the highest revenue share of 40%.
- APAC is anticipated to have the highest CAGR among all the regions.
- APAC is expected to grow at a greater pace owing to the rapid adoption of digital payment systems & the increased penetration of internet-based services.
Factors affecting the growth of Generative AI in Financial Services Market?
There are several factors that are affecting the growth of generative AI in financial services industry. These include:
- Data Accessibility: Generative AI relies on accessing large data sets. Without enough quality data or having enough of it at hand, its use becomes significantly limited and could interfere with the development and adoption of Generative AI models.
- Regulatory environment: Financial services are heavily regulated, and any new technologies including Generative AI must adhere to regulatory requirements. This may affect its adoption and implementation timeline.
- Cost: Generative AI solutions can be expensive to develop and deploy, especially for smaller Financial Services firms with tighter budgets. Cost can act as an impediment to adoption and implementation.
- Trust and transparency: Black-box models can be difficult to interpret, which requires financial services companies and customers alike to have confidence in them and understand how their data will be utilized. A lack of trust could hinder adoption and implementation.
- Skilled workforce: To effectively develop and deploy Generative AI models, skilled labor is needed. Unfortunately, however, there is a shortage of people possessing the necessary skills for creating these models which could impede adoption and implementation processes.
- Competition: Financial services is a highly competitive industry and businesses must stand out to be successful. Generative AI may offer companies an edge but if other firms adopt similar models this advantage could quickly fade.
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Top Trends in Global Generative AI in Financial Services Market
One of the latest trends in the generative AI market for financial services is the use of machine learning (ML) and natural language processing (NLP) in order to create more advanced bots. These AI-powered tools improve customer service through a reduction in response times & personalization of interactions with customers. Another trend is using generative AI to develop predictive models for credit risk assessment & fraud detection. These models can analyze a large amount of data in order to provide more accurate forecasts. Explainable AI (XAI), or AI systems that can explain their decisions, is gaining in popularity in the financial services industry. This is important for building trust and reducing the risk of unfair or biased results. The use of generative AI is also increasing in algorithmic trading; as financial institutions try to develop more advanced trading strategies.
Market Growth
The market for Generative AI in Financial Services will grow rapidly in the next few years. This growth is driven by the increasing adoption of AI and the growing availability and volume of data as Financial Services companies strive to improve their efficiency, lower risk, and offer better customer experience. The models can be used to analyze large amounts of data & identify patterns and insights which can help inform decisions. The models can automate processes and free up employees' time to focus on more complex work. Financial Services companies are investing more in AI-based fraud detection, risk assessment, investment prediction, and customer service. Financial Services companies are also expected to benefit from the development of advanced Generative AI models such as Natural Language Generation and Image Recognition.
Regional Analysis
North America will be the leading region in the global generative AI in financial services market with a market share of 40%. It is also estimated to have a CAGR of 29.6% over 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 and 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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Scope of the Report
| Report Attribute | Details |
| Market Value (2022) | US$ 847.2 Mn |
| Market Size (2032) | US$ 9,475.2 Mn |
| CAGR (from 2023 to 2032) | 28.1% |
| North America Revenue Share | 40.00% |
| Historic Period | 2016 to 2022 |
| Base Year | 2022 |
| Forecast Year | 2023 to 2032 |
Market Drivers
The financial services industry is increasingly requiring accurate and efficient services. Generative AI is able to analyze large amounts of data in order to identify patterns & anomalies. This allows financial institutions to reduce risk and make better decisions. The increased availability of data and advances in machine learning algorithms have made generative AI an even more powerful tool for financial applications. The growing popularity of mobile banks & the need for more personalized and faster customer service has led to an increase in the demand for chatbots powered by generative AI. Brightwell Payments, Inc., a financial services company in the United States released ARDEN in May 2022. This financial solution allows money to be transferred securely anywhere in the world. This AI-powered engine protects the financial assets and cardholders of fintech. These factors, along with others are driving the growth of the generative AI industry.
Market Restraints
Despite the growing adoption of generative AI in the financial services market, numerous factors limit growth. One of the biggest problems is the lack of trust in AI-powered decision-making, especially in sensitive financial fields like fraud detection & risk assessment. AI algorithms can be difficult to understand and if not designed and tested correctly they can lead to unfair and biased outcomes. The high cost to implement generative AI could be prohibitive for smaller financial institutions. The regulatory landscape of AI in finance is constantly evolving which can cause uncertainty and compliance issues. The lack of AI professionals who have the necessary skills, and the possibility that AI will replace jobs in the financial sector are all factors that could slow down adoption.
Market Opportunities
Two of the main growth factors are the increasing availability of data and the demand for more precise financial services. This trend will continue as financial institutions strive to improve their fraud detection & risk management capabilities along with customer service. The use of generative artificial intelligence is expected to surge as more investors seek data-driven insights to make informed investment decisions. Another growth opportunity is the adoption of AI-powered chatbots & virtual assistants in financial services. These can provide faster and more personalized customer service. As the regulatory landscape of AI in finance becomes clearer, new opportunities will arise for generative AI products to help financial institutions meet regulatory needs more efficiently.
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Report Segmentation of the Generative AI in Financial Services Market
Type Insight
The market for Generative AI Financial Services can be divided into two distinct segments based on type: solutions and services. Of the two categories, solutions represent the more lucrative type, with projected annual growth rates of 32% projected. 2022 will see solutions reach 76.4% of the total revenue share for banking solutions. This high figure can be attributed to software tools that facilitate AI-enabled bank solutions that extract accurate and complete data quickly from vast quantities. Solutions offered by some businesses can assist businesses in increasing retail banking with next-best-action software, combat financial fraud and improve client relationships using multichannel customer experiences. It is anticipated that the services segment will experience rapid expansion over the coming years, driven by its ability to administer AI-enabled Fintech apps more effectively.
Application Insight
The market is further segmented by application into credit scoring, fraud prevention, risk management, and forecasting & reporting. The forecasting & Reporting segment is estimated as the most lucrative segment of the global generative AI in financial services market. this segment is expected to be the most lucrative with a market share of 30% in 2022. The growth of this segment can be ascribed to several factors such as improved operational efficiency, better-informed decision-making, and increased revenue. Many companies use business analytics, AI, and Big Data to make better decisions. Fintech is experiencing rapid growth which has led AI to expand in this field. Customer behavioral analytics will grow in importance over the next few decades.
Deployment Mode Insight
The market is segmented based on the deployment mode. The on-premise mode, which is estimated to have the largest market share in the global generative AI in financial services market with a projected CAGR of 28.3% in 2022 is the most lucrative. On-premise deployment allows enterprises to install software or services on a financial institution’s systems or premises. The cloud segment will have the fastest CAGR from 2022 to 2032. AI algorithms can be credited with growth. They learn from historical data in a cloud environment & detect current standards. They can also make recommendations. Cloud computing and AI can increase productivity, efficiency, and digital security in data handling and authenticity. This automated technique eliminates human errors during data processing.
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Market Segmentation
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
Key Regions
- 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
Competitive Landscape
The increasing competition in the financial industry is a barrier to businesses that provide financial services. This is owing to the need for better financial operations, cost savings, and client engagement. These characteristics are the cause of underperformance within an increasingly competitive business environment. In recent years, market participants have formed partnerships & collaborated to acquire a dominating position. Gupshup announced in April 2022 that it would acquire Active.Ai, a private finance firm specializing in AI.
Some of the major players include:
- IBM Corporation
- Intel Corporation
- Narrative Science
- Amazon Web Services, Inc.
- Microsoft
- Google LLC
- Salesforce, Inc.
- Other Key Players
Recent Development of the Generative AI in Financial Services Market
- In June 2022, Virgin Money and SurePay will partner 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.
Related Reports
- Generative AI in Insurance Market size is expected to be worth around USD 5,543.1 Mn by 2032 from USD 346.3 Mn in 2022, growing at a CAGR of 32.9% during the forecast period from 2023 to 2032.
- Generative AI in Supply Chain Market size is expected to be worth around USD 10,284 Mn by 2032 from USD 269 Mn in 2022, growing at a CAGR of 45.3% during the forecast period from 2023 to 2032.
- Generative AI in Pharma Market size is expected to be worth around USD 2258.1 Mn by 2032 from USD 159.9 Mn in 2022, growing at a CAGR of 31.2% during the forecast period from 2023 to 2032.
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