• Cat-intel
  • MedIntelliX
  • Resources
  • About Us
  • Request Free Sample ×

    Kindly complete the form below to receive a free sample of this Report

    Leading companies partner with us for data-driven Insights

    clients tt-cursor

    UK Applied AI in Finance Market

    ID: MRFR/BFSI/57199-HCR
    200 Pages
    Aarti Dhapte
    September 2025

    UK Applied AI in Finance Market Research Report By Component (Solution, Services), By Deployment Mode (On-premise, Cloud), By Application (Virtual Assistants, Business Analytics and Reporting, Customer Behavioral Analytics, Others) and By Organization Size (SME's, Large Enterprises) - Forecast to 2035

    Share:
    Download PDF ×

    We do not share your information with anyone. However, we may send you emails based on your report interest from time to time. You may contact us at any time to opt-out.

    UK Applied AI in Finance Market Research Report- Forecast to 2035 Infographic
    Purchase Options
    $ 4,950.0
    $ 5,950.0
    $ 7,250.0
    Table of Contents

    UK Applied AI in Finance Market Summary

    The United Kingdom Applied AI in Finance market is poised for substantial growth, with projections indicating a rise from 707.4 million USD in 2024 to 4436.2 million USD by 2035.

    Key Market Trends & Highlights

    UK Applied AI in Finance Key Trends and Highlights

    • The market is expected to grow from 707.4 million USD in 2024 to 4436.2 million USD by 2035.
    • A compound annual growth rate (CAGR) of 18.16 percent is anticipated from 2025 to 2035.
    • The increasing integration of AI technologies in financial services is driving market expansion.
    • Growing adoption of AI solutions due to the need for enhanced operational efficiency is a major market driver.

    Market Size & Forecast

    2024 Market Size 707.4 (USD Million)
    2035 Market Size 4436.2 (USD Million)
    CAGR (2025-2035) 18.16%

    Major Players

    Ayasdi, Numerai, Lenddo, FICO, Kensho, Yolt, DeepMind, SAS Institute, DataRobot, IBM, ZestFinance, Tink, ThoughtSpot, OpenAI

    UK Applied AI in Finance Market Trends

    The UK Applied AI in Finance Market is experiencing notable advances driven by the need for enhanced efficiency and risk management within financial institutions. Major banks and fintech companies are increasingly adopting AI technologies to streamline operations, improve customer service, and ensure regulatory compliance. The growing complexity of data management and transaction processing has led to a rise in AI-driven solutions that efficiently analyze large volumes of financial data. 

    Another key market driver is regulatory pressures; institutions are adopting AI to comply with evolving regulations related to fraud detection, money laundering, and customer due diligence as mandated by UK financial authorities. There are substantial opportunities in this market, particularly in the areas of automated customer support and personalized banking. By utilizing AI to offer personalized financial advice and services to customers, financial institutions can capitalize on these opportunities, thereby increasing consumer engagement and loyalty. 

    Furthermore, the demand for AI-driven solutions that can enhance operational performance and user experience has increased as a result of the pandemic-induced surge in digital banking. Institutions have been striving to guarantee that their AI systems are not only efficient but also impartial and transparent in decision-making, which has led to a recent increase in the emphasis on transparency and ethical AI usage. 

    This trend is encouraging the development of ethical AI frameworks that are consistent with the United Kingdom's dedication to financial stability and inclusion. Consequently, the United Kingdom continues to establish itself as a premier center for artificial intelligence (AI) in finance, thereby enabling the cultivation of talent, collaboration, and investment in this sector that is undergoing a rapid transformation.

           

    UK Applied AI in Finance Market Drivers

    Market Segment Insights

    Get more detailed insights about UK Applied AI in Finance Market Research Report- Forecast to 2035

    Regional Insights

    Key Players and Competitive Insights

    The UK Applied AI in Finance Market is characterized by rapid technological advancements and an increasingly competitive landscape, driven by the need for financial institutions to enhance efficiency, improve decision-making, and mitigate risks through data-driven solutions. With the integration of artificial intelligence across various segments of finance, firms are harnessing the power of machine learning and analytics to not only streamline operations but also tailor financial products to meet the specific needs of customers. The heightened adoption of AI technologies is fueled by regulatory requirements, the demand for innovative financial services, and the imperative for better compliance processes.

    This shifting market dynamic poses both opportunities and challenges as different players strive to carve out their niches in an evolving environment.

    Ayasdi has established a noteworthy presence in the UK Applied AI in Finance Market, focusing on developing advanced machine learning solutions. The company excels in creating powerful data analysis tools that help financial institutions detect patterns and enhance their operational capabilities. Strengths include its ability to simplify complex data processing, allowing organizations to interpret vast amounts of data effectively. This capability positions Ayasdi to address various aspects of finance, ranging from fraud detection to risk assessment, making it an appealing choice for banks and financial services looking to leverage sophisticated AI-driven insights.

    The company's technology is noted for its intuitive design and robust analytical features, enabling clients to gain actionable intelligence without extensive data science expertise.

    Numerai is notable within the UK Applied AI in Finance Market for its innovative approach to financial modeling and investing through crowdsourced data science. The firm provides a platform where data scientists globally can submit predictions regarding stock market trends, enabling the aggregation of insights and strategies for hedge fund management. Key services include its unique data science tournament, which incentivizes predictive models, fostering an environment of continuous improvement. Numerai benefits from a strong ecosystem presence, attracting data scientists while maintaining transparency and collaboration. 

    The company's strategic partnerships and ongoing engagements in fintech innovation underline its competitive edge. Numerai is also actively engaged in expanding its capabilities through select mergers and acquisitions, further solidifying its market position within the UK by continuously enhancing its technological offerings and adapting to the dynamic requirements of the financial sector.

    Key Companies in the UK Applied AI in Finance Market market include

    Industry Developments

    Recent developments in the UK Applied AI in Finance Market indicate a growing interest and investment in advanced technologies. Companies such as DeepMind and IBM are increasingly leveraging artificial intelligence for predictive analytics and risk management in financial services. A notable current affair is the expansion of Numerai's hedge fund model, which incorporates machine learning competitions to enhance investment strategies. 

    Additionally, Lenddo is gaining traction by using alternative data for credit scoring, positively impacting underserved demographics. In the domain of mergers and acquisitions, Ayasdi has actively pursued partnerships to integrate its machine learning capabilities into financial institutions, while Tink's acquisition of a competitor in September 2022 has strengthened its position in the payments landscape. 

    The market is also seeing a valuation growth spurring the emergence of new startups focused on innovative financial solutions. Over the last two years, companies such as SAS Institute and ZestFinance have made significant advances in AI-driven compliance and underwriting processes, which have garnered attention from major investors. As these technologies continue to evolve, the UK Applied AI in Finance Market is poised for significant transformation.

    Market Segmentation

    Applied AI in Finance Market Component Outlook

    • Solution
    • Services

    Applied AI in Finance Market Application Outlook

    • Virtual Assistants
    • Business Analytics and Reporting
    • Customer Behavioral Analytics
    • Others

    Applied AI in Finance Market Deployment Mode Outlook

    • On-premise
    • Cloud

    Applied AI in Finance Market Organization Size Outlook

    • SME's
    • Large Enterprises

    Report Scope

    Report Attribute/Metric Source: Details
    MARKET SIZE 2023 577.47 (USD Million)
    MARKET SIZE 2024 707.4 (USD Million)
    MARKET SIZE 2035 4436.2 (USD Million)
    COMPOUND ANNUAL GROWTH RATE (CAGR) 18.164% (2025 - 2035)
    REPORT COVERAGE Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
    BASE YEAR 2024
    MARKET FORECAST PERIOD 2025 - 2035
    HISTORICAL DATA 2019 - 2024
    MARKET FORECAST UNITS USD Million
    KEY COMPANIES PROFILED Ayasdi, Numerai, Lenddo, FICO, Kensho, Yolt, DeepMind, SAS Institute, DataRobot, IBM, ZestFinance, Tink, ThoughtSpot, OpenAI
    SEGMENTS COVERED Component, Deployment Mode, Application, Organization Size
    KEY MARKET OPPORTUNITIES Fraud detection automation, Customer service chatbots, Risk assessment optimization, Algorithmic trading improvements, Regulatory compliance solutions
    KEY MARKET DYNAMICS Regulatory compliance requirements, Growing investment in fintech, Demand for risk management solutions, Advancements in machine learning, Increasing customer personalization needs
    COUNTRIES COVERED UK

    Market Highlights

    Author
    Aarti Dhapte
    Team Lead - Research

    She holds an experience of about 6+ years in Market Research and Business Consulting, working under the spectrum of Information Communication Technology, Telecommunications and Semiconductor domains. Aarti conceptualizes and implements a scalable business strategy and provides strategic leadership to the clients. Her expertise lies in market estimation, competitive intelligence, pipeline analysis, customer assessment, etc.

    Leave a Comment

    FAQs

    What is the expected market size of the UK Applied AI in Finance Market by 2024?

    The UK Applied AI in Finance Market is expected to be valued at 707.4 million USD by the year 2024.

    What will the market size be in 2035 for the UK Applied AI in Finance Market?

    By 2035, the UK Applied AI in Finance Market is projected to reach a value of 4436.2 million USD.

    What is the compound annual growth rate (CAGR) of the UK Applied AI in Finance Market from 2025 to 2035?

    The market is expected to experience a CAGR of 18.164 percent from 2025 to 2035.

    What is the market size for the solutions segment in the UK Applied AI in Finance Market in 2024?

    The solutions segment is anticipated to be valued at 300.0 million USD in the year 2024.

    What is the projected market size for services in the UK Applied AI in Finance Market by 2035?

    The services segment is expected to grow to 2636.2 million USD by the year 2035.

    Who are the key players in the UK Applied AI in Finance Market?

    Major players in the market include Ayasdi, Numerai, Lenddo, FICO, Kensho, Yolt, DeepMind, SAS Institute, DataRobot, IBM, ZestFinance, Tink, ThoughtSpot, and OpenAI.

    What are the expected opportunities for growth in the UK Applied AI in Finance Market?

    The market is expected to grow due to increasing demand for automated solutions and data-driven decision-making processes.

    What challenges does the UK Applied AI in Finance Market currently face?

    Challenges include regulatory compliance and data privacy concerns in the financial sector.

    What applications do AI solutions have in the finance sector?

    AI solutions are applied in areas such as risk assessment, fraud detection, customer support, and personalized banking.

    How does the growth rate of the UK Applied AI in Finance Market compare by segment?

    Both solutions and services segments are expected to contribute significantly to the overall growth of the market during the forecast period.

    1. EXECUTIVE
    2. SUMMARY
    3. Market Overview
    4. Key Findings
    5. Market Segmentation
    6. Competitive Landscape
    7. Challenges and Opportunities
    8. Future Outlook
    9. MARKET INTRODUCTION
    10. Definition
    11. Scope of the study
    12. Research Objective
    13. Assumption
    14. Limitations
    15. RESEARCH
    16. METHODOLOGY
    17. Overview
    18. Data
    19. Mining
    20. Secondary Research
    21. Primary
    22. Research
    23. Primary Interviews and Information Gathering
    24. Process
    25. Breakdown of Primary Respondents
    26. Forecasting
    27. Model
    28. Market Size Estimation
    29. Bottom-Up
    30. Approach
    31. Top-Down Approach
    32. Data
    33. Triangulation
    34. Validation
    35. MARKET
    36. DYNAMICS
    37. Overview
    38. Drivers
    39. Restraints
    40. Opportunities
    41. MARKET FACTOR ANALYSIS
    42. Value chain Analysis
    43. Porter's
    44. Five Forces Analysis
    45. Bargaining Power of Suppliers
    46. Bargaining
    47. Power of Buyers
    48. Threat of New Entrants
    49. Threat
    50. of Substitutes
    51. Intensity of Rivalry
    52. COVID-19
    53. Impact Analysis
    54. Market Impact Analysis
    55. Regional
    56. Impact
    57. Opportunity and Threat Analysis
    58. UK
    59. Applied AI in Finance Market, BY Component (USD Million)
    60. Solution
    61. Services
    62. UK
    63. Applied AI in Finance Market, BY Deployment Mode (USD Million)
    64. On-premise
    65. Cloud
    66. UK
    67. Applied AI in Finance Market, BY Application (USD Million)
    68. Virtual
    69. Assistants
    70. Business Analytics and Reporting
    71. Customer
    72. Behavioral Analytics
    73. Others
    74. UK
    75. Applied AI in Finance Market, BY Organization Size (USD Million)
    76. SME's
    77. Large
    78. Enterprises
    79. Competitive Landscape
    80. Overview
    81. Competitive
    82. Analysis
    83. Market share Analysis
    84. Major
    85. Growth Strategy in the Applied AI in Finance Market
    86. Competitive
    87. Benchmarking
    88. Leading Players in Terms of Number of Developments
    89. in the Applied AI in Finance Market
    90. Key developments
    91. and growth strategies
    92. New Product Launch/Service Deployment
    93. Merger
    94. & Acquisitions
    95. Joint Ventures
    96. Major
    97. Players Financial Matrix
    98. Sales and Operating Income
    99. Major
    100. Players R&D Expenditure. 2023
    101. Company
    102. Profiles
    103. Ayasdi
    104. Financial
    105. Overview
    106. Products Offered
    107. Key
    108. Developments
    109. SWOT Analysis
    110. Key
    111. Strategies
    112. Numerai
    113. Financial
    114. Overview
    115. Products Offered
    116. Key
    117. Developments
    118. SWOT Analysis
    119. Key
    120. Strategies
    121. Lenddo
    122. Financial
    123. Overview
    124. Products Offered
    125. Key
    126. Developments
    127. SWOT Analysis
    128. Key
    129. Strategies
    130. FICO
    131. Financial
    132. Overview
    133. Products Offered
    134. Key
    135. Developments
    136. SWOT Analysis
    137. Key
    138. Strategies
    139. Kensho
    140. Financial
    141. Overview
    142. Products Offered
    143. Key
    144. Developments
    145. SWOT Analysis
    146. Key
    147. Strategies
    148. Yolt
    149. Financial
    150. Overview
    151. Products Offered
    152. Key
    153. Developments
    154. SWOT Analysis
    155. Key
    156. Strategies
    157. DeepMind
    158. Financial
    159. Overview
    160. Products Offered
    161. Key
    162. Developments
    163. SWOT Analysis
    164. Key
    165. Strategies
    166. SAS Institute
    167. Financial
    168. Overview
    169. Products Offered
    170. Key
    171. Developments
    172. SWOT Analysis
    173. Key
    174. Strategies
    175. DataRobot
    176. Financial
    177. Overview
    178. Products Offered
    179. Key
    180. Developments
    181. SWOT Analysis
    182. Key
    183. Strategies
    184. IBM
    185. Financial
    186. Overview
    187. Products Offered
    188. Key
    189. Developments
    190. SWOT Analysis
    191. Key
    192. Strategies
    193. ZestFinance
    194. Financial
    195. Overview
    196. Products Offered
    197. Key
    198. Developments
    199. SWOT Analysis
    200. Key
    201. Strategies
    202. Tink
    203. Financial
    204. Overview
    205. Products Offered
    206. Key
    207. Developments
    208. SWOT Analysis
    209. Key
    210. Strategies
    211. ThoughtSpot
    212. Financial
    213. Overview
    214. Products Offered
    215. Key
    216. Developments
    217. SWOT Analysis
    218. Key
    219. Strategies
    220. OpenAI
    221. Financial
    222. Overview
    223. Products Offered
    224. Key
    225. Developments
    226. SWOT Analysis
    227. Key
    228. Strategies
    229. References
    230. Related
    231. Reports
    232. LIST
    233. OF ASSUMPTIONS
    234. UK Applied AI in Finance Market SIZE ESTIMATES
    235. & FORECAST, BY COMPONENT, 2019-2035 (USD Billions)
    236. UK
    237. Applied AI in Finance Market SIZE ESTIMATES & FORECAST, BY DEPLOYMENT MODE,
    238. 2035 (USD Billions)
    239. UK Applied AI in Finance Market
    240. SIZE ESTIMATES & FORECAST, BY APPLICATION, 2019-2035 (USD Billions)
    241. UK
    242. Applied AI in Finance Market SIZE ESTIMATES & FORECAST, BY ORGANIZATION SIZE,
    243. 2035 (USD Billions)
    244. PRODUCT LAUNCH/PRODUCT DEVELOPMENT/APPROVAL
    245. ACQUISITION/PARTNERSHIP
    246. LIST
    247. Of figures
    248. MARKET SYNOPSIS
    249. UK
    250. APPLIED AI IN FINANCE MARKET ANALYSIS BY COMPONENT
    251. UK
    252. APPLIED AI IN FINANCE MARKET ANALYSIS BY DEPLOYMENT MODE
    253. UK
    254. APPLIED AI IN FINANCE MARKET ANALYSIS BY APPLICATION
    255. UK
    256. APPLIED AI IN FINANCE MARKET ANALYSIS BY ORGANIZATION SIZE
    257. KEY
    258. BUYING CRITERIA OF APPLIED AI IN FINANCE MARKET
    259. RESEARCH
    260. PROCESS OF MRFR
    261. DRO ANALYSIS OF APPLIED AI IN FINANCE
    262. MARKET
    263. DRIVERS IMPACT ANALYSIS: APPLIED AI IN FINANCE
    264. MARKET
    265. RESTRAINTS IMPACT ANALYSIS: APPLIED AI IN FINANCE
    266. MARKET
    267. SUPPLY / VALUE CHAIN: APPLIED AI IN FINANCE MARKET
    268. APPLIED
    269. AI IN FINANCE MARKET, BY COMPONENT, 2025 (% SHARE)
    270. APPLIED
    271. AI IN FINANCE MARKET, BY COMPONENT, 2019 TO 2035 (USD Billions)
    272. APPLIED
    273. AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2025 (% SHARE)
    274. APPLIED
    275. AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2019 TO 2035 (USD Billions)
    276. APPLIED
    277. AI IN FINANCE MARKET, BY APPLICATION, 2025 (% SHARE)
    278. APPLIED
    279. AI IN FINANCE MARKET, BY APPLICATION, 2019 TO 2035 (USD Billions)
    280. APPLIED
    281. AI IN FINANCE MARKET, BY ORGANIZATION SIZE, 2025 (% SHARE)
    282. APPLIED
    283. AI IN FINANCE MARKET, BY ORGANIZATION SIZE, 2019 TO 2035 (USD Billions)
    284. BENCHMARKING
    285. OF MAJOR COMPETITORS

    UK Applied AI in Finance Market Segmentation

     

    • Applied AI in Finance Market By Component (USD Million, 2019-2035)

      • Solution
      • Services

     

    • Applied AI in Finance Market By Deployment Mode (USD Million, 2019-2035)

      • On-premise
      • Cloud

     

    • Applied AI in Finance Market By Application (USD Million, 2019-2035)

      • Virtual Assistants
      • Business Analytics and Reporting
      • Customer Behavioral Analytics
      • Others

     

    • Applied AI in Finance Market By Organization Size (USD Million, 2019-2035)

      • SME's
      • Large Enterprises

     

     

     

     

     

     

    Report Infographic
    Free Sample Request

    Kindly complete the form below to receive a free sample of this Report

    Customer Strories

    “I am very pleased with how market segments have been defined in a relevant way for my purposes (such as "Portable Freezers & refrigerators" and "last-mile"). In general the report is well structured. Thanks very much for your efforts.”

    Victoria Milne Founder
    Case Study

    Chemicals and Materials