Applied AI in Finance Market Share

Applied AI in Finance Market Overview

Applied AI in Finance Market Size was valued at USD 8.01 billion in 2022. The Applied AI in Finance Market industry is projected to grow from USD 9.62 billion in 2023 to USD 59.70 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 22.5% during the forecast period (2023 - 2032).

Applied artificial intelligence (AI) in finance uses AI and machine learning technologies to solve real-world business problems in the financial industry. For example, AI can be used to automate tasks like processing loans and insurance claims, which can help to reduce costs and improve efficiency. AI can also be used to analyze large amounts of customer data to identify patterns and make predictions, which can help to improve risk management and customer service. Financial services AI involves the incorporation of AI technologies and algorithms in different financial operations to automate tasks, analyze data, make predictions, and offer valuable insights. AI-driven finance, on the other hand, refers to the integration of AI technologies in financial systems, allowing organizations to streamline operations like risk assessment, fraud detection, customer service, and investment management. These AI solutions utilize machine learning, natural language processing, and predictive analytics to process large amounts of data and identify patterns, trends, and anomalies in real-time. Investment AI solutions are revolutionizing the investment landscape by equipping investors with advanced tools to make data-driven decisions.

FIGURE 1: APPLIED AI IN FINANCE MARKET SIZE 2019-2032 (USD BILLION)

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

Applied AI in Finance Market Trends

Integration of AI-powered chatbots and virtual assistants in customer service

The integration of AI-powered chatbots and virtual assistants in customer service is a significant trend in the applied AI in finance market. Financial institutions are leveraging AI technologies to enhance customer interactions, streamline processes, and improve overall customer service experiences. AI-powered chatbots and virtual assistants are intelligent systems that can understand and respond to customer queries and requests in real-time. These systems utilize natural language processing (NLP) algorithms to comprehend customer inputs and provide accurate and relevant responses. In the context of finance, these chatbots and virtual assistants are being used to address customer inquiries related to account balances, transaction histories, loan applications, investment advice, and more. They can assist customers in navigating through complex financial products and services, providing personalized recommendations based on individual preferences and financial goals. By integrating AI-powered chatbots and virtual assistants into customer service, financial institutions can achieve several benefits. Firstly, it enables 24/7 availability, allowing customers to receive assistance and support at any time, thereby enhancing customer satisfaction and convenience. Additionally, AI-powered chatbots and virtual assistants can continuously learn and improve their responses through machine learning algorithms. They can analyze customer interactions, identify patterns, and adapt their responses to provide more accurate and personalized assistance over time. Overall, the integration of AI-powered chatbots and virtual assistants in customer service is a growing trend in the applied AI in finance market. It empowers financial institutions to deliver better customer experiences, increase operational efficiency, and optimize resource allocation, ultimately leading to improved customer satisfaction and loyalty.

Applied AI in Finance Market Segment Insights

Applied AI in Finance Component Insights

The Applied AI in Finance Market has been segmented based on offering into solution, services.

The segment- Solution holds the largest share of the total market share. Solution segment encompasses various AI technologies and software offerings designed specifically for finance, including but not limited to chatbots, virtual assistants, fraud detection systems, risk management tools, algorithmic trading platforms, and predictive analytics models. These solutions are developed by specialized AI vendors and software providers who leverage their expertise to create robust and scalable AI applications that cater to the specific needs of financial institutions. On the other hand, the Services segment primarily includes professional services such as consulting, system integration, implementation, and maintenance provided by AI solution providers or third-party service providers. While these services are crucial for successful adoption and utilization of AI solutions, they typically represent a smaller portion of the market compared to the solution offerings themselves. The higher prominence of the Solution segment can be attributed to the increasing demand for AI technologies in the finance industry. Financial institutions are actively seeking AI-driven solutions to enhance efficiency, improve decision-making, mitigate risks, and deliver personalized customer experiences. As a result, the development and deployment of specialized AI solutions tailored for finance applications have gained significant traction, driving the growth of the "Solution" segment in the applied AI in finance market.

Applied AI in Finance Deployment Mode Insights

The Applied AI in Finance Market has been segmented on the basis of deployment mode into On-premises, Cloud.

Finance organizations benefit greatly from cloud-based AI solutions due to their alignment with core industry characteristics. Firstly, the scalability and flexibility of cloud infrastructure allows financial institutions to efficiently scale their AI resources up and down as needs change. Since the finance industry handles vast amounts of data and complex calculations, the ability to quickly scale processing power is critical. Deploying to the cloud can also help reduce costs. Financial organizations can avoid large upfront expenditures on hardware and software, instead paying only for the resources they use on a flexible subscription basis. This optimized payment model allows companies to carefully manage spending. Overall, the cloud deployment model is poised to gain a substantial market share in applied AI for finance by 2022. Its scalability, flexibility, accessibility, security and cost effectiveness address the unique operational requirements of the industry. The advantages cloud solutions provide are a strong fit for finance's data-heavy and calculation-intensive work.

Applied AI in Finance Application Insights

The applied AI in Finance market in this report has been segmented on the basis of application into Virtual Assistants (Chatbots), Business Analytics and Reporting, Customer Behavioral Analytics, Others. The segment of Virtual Assistants (Chatbots) is growing rapidly. Chatbots are computer programs capable of simulating natural human conversations through messaging interfaces. They are gaining widespread adoption in finance due to abilities like personalized customer service and streamlined processes. One driver of chatbots' rising popularity in finance is the increasing demand for seamless, convenient customer support. Using chatbots, financial institutions can aid 24/7 to answer queries and facilitate transactions without human involvement. This automation lowers costs while improving efficiency. Chatbots are also being applied to automate various back-office tasks in finance such as data entry, report generation and compliance operations. By leveraging AI and natural language processing, chatbots can rapidly analyze vast amounts of information and make decisions more quickly and accurately than humans alone, enabling faster decision-making and mitigating error risks.

Applied AI in Finance Organization Size Insights

The Applied AI in Finance market in this report has been segmented on the basis of organization size into SME's, Large Enterprises.

APPLIED AI IN FINANCE MARKET, BY ORGANIZATION SIZE, 2022 VS 2032 (USD BILLION)

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

Large Enterprises is the fastest growing segment in the applied AI in Finance market. The finance market's implementation of artificial intelligence (AI) has been experiencing notable growth, with large enterprises becoming the fastest-growing sector in this industry. These enterprises, known for their substantial financial resources and global presence, are increasingly recognizing the potential of AI technology in revolutionizing their financial operations. One of the main drivers behind the rapid expansion of AI in finance within large enterprises is the desire to improve efficiency and decrease costs. By utilizing AI-powered solutions, various financial processes such as risk assessment, fraud detection, and customer service can be automated and streamlined. This allows large enterprises to optimize their operations, make data-driven decisions, and achieve higher precision in financial analysis. Additionally, large enterprises are leveraging AI to enhance customer experience and provide personalized financial services. Through analyzing vast amounts of customer data, AI algorithms can generate insights that assist in tailoring financial products and services to cater to individual needs. This not only increases customer engagement and satisfaction but also improves customer retention and loyalty. Furthermore, the utilization of applied AI in finance provides large enterprises with a competitive advantage by enabling them to stay ahead of market trends. AI algorithms can analyze financial data, market conditions, and historical patterns to identify profitable investment opportunities. This not only aids large enterprises in making informed investment decisions but also allows them to quickly adapt their strategies in response to changing market dynamics. Overall, the integration of applied AI in finance by large enterprises offers significant benefits in terms of operational efficiency, customer experience, and competitive edge. As a result, this sector is experiencing remarkable growth, and this upward trajectory is expected to continue in the foreseeable future.

Applied AI in Finance Regional Insights

Based on Region, the global Applied AI in Finance is segmented into North America, Europe, Asia-Pacific, Middle East & Africa, and South America. Further, the major countries studied in the market report are the U.S., Canada, Germany, UK, Italy, Spain, China, Japan, India, Australia, UAE, and Brazil.

North America dominated the applied artificial intelligence in Finance market in 2022, this dominance can be attributed to several key factors. Firstly, North America has a well-developed financial sector which consists of numerous banks, insurance companies, and investment firms. These institutions are increasingly adopting AI technologies to streamline their operations, improve customer experience, and enhance decision-making processes. Additionally, North America has a thriving ecosystem for AI innovation, with a multitude of tech startups and established companies focusing on AI solutions in the finance industry. Investments in AI research and development, along with favorable government policies and initiatives, have further facilitated market growth in the region. Another contributing factor is the availability of a skilled workforce. North America is home to leading universities and research institutions that offer specialized programs in both AI and finance, ensuring a consistent supply of qualified professionals in this field. Furthermore, the region benefits from a strong technological infrastructure, including advanced computing capabilities and high-speed internet connectivity, which allows for seamless integration and implementation of AI solutions in financial institutions. Given these factors, it is anticipated that North America will continue to dominate the applied AI in finance market, capturing the largest market share in 2022.

There is significant growth occurring in the Asia-Pacific region regarding the adoption and use of artificial intelligence (AI) in the finance industry. AI is increasingly being utilized to enhance efficiency, accuracy, and decision-making across various financial services, including banking, insurance, investment management, and risk assessment. Within the banking sector, AI is transforming customer service through the use of chatbots and virtual assistants, which provide personalized and real-time assistance, improving the overall banking experience. Through the analysis of large volumes of data, AI algorithms can rapidly evaluate creditworthiness, identify fraudulent activities, and generate precise credit scores. This not only streamlines loan approval processes but also decreases the risk of credit defaults. Similarly, AI is revolutionizing investment management by employing advanced machine learning techniques to analyze historical data and recognize patterns, trends, and correlations in the financial markets. By leveraging AI algorithms, asset managers can make informed investment choices, optimize portfolios, and develop more effective strategies. This not only improves investment performance but also mitigates the negative impact of human biases and emotions on decision-making. Additionally, AI greatly benefits the insurance industry, with insurers utilizing it to automate claim processing for faster and more accurate settlements. AI-powered chatbots handle customer queries and assist with policy purchases and renewals, enhancing customer experience. Moreover, AI algorithms can analyze vast amounts of data to identify potential risks, enabling insurers to better assess premiums and create customized policies. This improves risk assessment and underwriting processes, leading to more efficient and cost-effective insurance operations. The application of AI in finance extends beyond traditional banking and insurance sectors, as fintech startups in the Asia-Pacific region heavily invest in AI technologies to disrupt the financial services industry. These startups develop innovative solutions, including robo-advisors, alternative lending platforms, and blockchain-based payment systems. By leveraging AI algorithms, these startups offer personalized financial advice, automate lending processes, and enhance the security and efficiency of financial transactions.

FIGURE 3: APPLIED AI IN FINANCE MARKET SIZE BY REGION 2022 VS 2032, (USD BILLION)

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

Applied AI in Finance Key Market Players and Competitive Insights

The applied AI in finance market sees intense competition between established financial institutions and startup fintech companies, all seeking an advantage through sophisticated artificial intelligence. Major banks such as Citi, JPMorgan and Wells Fargo have significantly invested in developing extensive in-house AI teams and capabilities. At the same time, specialized fintech vendors focused solely on AI/ML solutions - like Anthropic, Blacksky and YayData - are creating solutions for finance applications like trading, risk management and customer service. Emerging rivals include technology heavyweights like Microsoft, Google and IBM, leveraging vast data and computing to build comprehensive AI platforms that the financial sector has widely adopted. As the uses of AI proliferate, partnerships have grown between banks, fintechs and tech vendors collaboratively designing and deploying AI-powered products and services.

Applied AI in Finance Market Key Companies Include

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  Anthropic PBC

  
  


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  BlackRock, Inc.

  
  


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  The Charles Schwab Corporation

  
  


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  Citigroup Inc.

  
  


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  Credit Suisse Group AG

  
  


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  Goldman Sachs Group, Inc.

  
  


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  HSBC Holdings plc

  
  


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  JPMorgan Chase & Co.

  
  


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  Morgan Stanley

  
  


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  Nasdaq, Inc.

  
  


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  Other players

  
  

Applied AI in Finance Industry developments

March 2023, the applied AI in finance market sees intense competition between established financial institutions and startup fintech companies, all seeking an advantage through sophisticated artificial intelligence. Major banks such as Citi, JPMorgan and Wells Fargo have significantly invested in developing extensive in-house AI teams and capabilities. At the same time, specialized fintech vendors focused solely on AI/ML solutions - like Anthropic, Blacksky and YayData - are creating solutions for finance applications like trading, risk management and customer service. Emerging rivals include technology heavyweights like Microsoft, Google and IBM, leveraging vast data and computing to build comprehensive AI platforms that the financial sector has widely adopted. As the uses of AI proliferate, partnerships have grown between banks, fintechs and tech vendors collaboratively designing and deploying AI-powered products and services.

Jan 2023, inscribe raised USD 25 million to fight financial fraud with artificial intelligence. Inscribe parses, classifies, and data-matches financial onboarding documents, emphasizing any inconsistencies between the papers provided and documents recovered using its AI-powered fraud detection. Individual customer risk profiles, which include snapshots of bank statements and transactions, are generated automatically using document details such as names, addresses, and bank statement transactions.

Applied AI in Finance Market Segmentation

Applied AI in Finance Component Outlook

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  Solution

  
  


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  Services

  
  

Applied AI in Finance Deployment Mode Outlook

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  On-premises

  
  


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  Cloud

  
  

Applied AI in Finance Application Outlook

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  Virtual Assistants (Chatbots)

  
  


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  Business Analytics and Reporting

  
  


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  Customer Behavioral Analytics

  
  


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  Others

  
  

Applied AI in Finance Organization Size Outlook

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  SME's

  
  


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  Large Enterprises

  
  

Applied AI in Finance Regional Outlook

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  North America

  
  
  
  
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    US

    
    
  
  
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    Canada

    
    
  
  
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    Mexico

    
    
  
  
  
  


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  Europe

  
  
  
  
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    Germany

    
    
  
  
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    France

    
    
  
  
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    UK

    
    
  
  
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    Italy

    
    
  
  
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    Spain

    
    
  
  
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    Rest of Europe

    
    
  
  
  
  


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  Asia-Pacific

  
  
  
  
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    China

    
    
  
  
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    Japan

    
    
  
  
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    India

    
    
  
  
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    South Korea

    
    
  
  
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    Australia

    
    
  
  
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    Rest of Asia-Pacific

    
    
  
  
  
  


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  Middle East & Africa

  
  
  
  
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    Saudi Arabia

    
    
  
  
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    UAE

    
    
  
  
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    South Africa

    
    
  
  
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    Rest of the Middle East & Africa

    
    
  
  
  
  


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  South America

  
  
  
  
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    Brazil

    
    
  
  
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    Argentina

    
    
  
  
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    Chile

    
    
  
  
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    Rest of South America

    
    
  
  
  
  

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