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AI In The Credit-Scoring Market

AI In The Credit-Scoring Market Size, Share & Trends Analysis Report By Component (Software and Service), By Application (Personal Credit Scoring and Corporate Credit Scoring), By Industry Vertical (BFSI (Banking, Financial Services, Insurance), Retail, Healthcare, Telecommunications, Utilities, and Real Estate), By Region, And By Segment Forecasts, 2024-2031

Report ID : 2578 | Published : 2024-09-25 | Pages: 170 | Format: PDF/EXCEL

The AI In The Credit-Scoring Market Size is predicted to grow at a 25.9% CAGR during the forecast period for 2024-2031.

ai in credit score

The AI in the credit scoring market is revolutionizing traditional credit assessment processes with the help of advanced machine learning algorithms to analyze a vast array of data. Alternative data sources are being utilized to enhance the accuracy of credit scoring models, allowing for a deeper and more accurate assessment of credit risk behaviours. This transformation has led to the development of AI-driven credit scoring applications offered by companies to banks and enterprise creditors, providing more accurate evaluations of a borrower's creditworthiness. The market is experiencing growth and expansion into various domains, with the potential to transform credit evaluation by providing more accurate, efficient, and inclusive assessments.

The COVID-19 pandemic accelerated the adoption of AI in the credit-scoring market. As traditional credit assessment methods struggled with economic uncertainty, AI's ability to analyze alternative data sources became crucial. Financial institutions turned to AI for more accurate risk assessments, enhanced fraud detection, and to manage the surge in digital transactions.

Competitive Landscape

Some Major Key Players In The AI In The Credit-Scoring Market:

  • FICO (Fair Isaac Corporation)
  • Experian
  • Equifax
  • TransUnion
  • Zest AI
  • LenddoEFL
  • Kreditech
  • CreditVidya
  • CreditXpert
  • Upstart
  • Pagaya
  • Underwrite.ai
  • Kensho Technologies
  • Scienaptic
  • DataRobot
  • Datrics
  • ClearScore
  • ScoreData
  • CredoLab
  • Trust Science
  • Other Market Players

 

Market Segmentation:

The AI in the credit scoring market segmentation includes the basis of component, application, and industry vertical. On the basis of component the market is segmented into Software and Service. The Application segment consists of Personal Credit Scoring and Corporate Credit Scoring. According to the Industry Vertical, the market is categorized into BFSI (Banking, Financial Services, Insurance), Retail, Healthcare, Telecommunications, Utilities, and Real Estate.

The Banking Segment Witnessed Growth At A Rapid Rate.

The banking segment in the AI credit scoring market has seen to have significant growth attributed to the need for accurate and efficient credit risk assessment. Banks leverage AI to analyze vast amounts of data, including non-traditional sources, to improve the accuracy of credit scores. This adoption enhances decision-making, reduces default rates, and increases financial inclusion. Additionally, AI helps detect fraud and improve operational efficiency, making it an important tool for modern banking operations.

In The Region, North American AI In The Credit Scoring Market Holds A Significant Revenue Share.

The North American AI in the credit scoring market is to be seen to have the highest market share. The AI in the credit scoring market in North America is transforming traditional credit scoring models by leveraging artificial intelligence and alternative data sources. AI-based credit scoring provides a more comprehensive assessment of credit risk by analyzing a broader range of data sources. Several companies offer AI-based credit scoring applications to banks and enterprise creditors, helping them better understand risk and make informed decisions. The market is growing, with AI applications expanding into various domains, including credit scoring. Asia Pacific is to be seen to grow at a fast rate in the global AI credit scoring market due to growing concerns about rapid industrialization, including government initiatives and increasing funding in various industries.

 

Recent Developments:

  • In Jan 2024, Intuit Inc., the worldwide financial technology platform responsible for Intuit TurboTax, Credit Karma, QuickBooks, and Mailchimp, has declared that Credit Karma members and QuickBooks Online customers now have the ability to complete and submit their 2023 tax returns using TurboTax directly within the Credit Karma and QuickBooks Online product interfaces.

 

AI In The Credit-Scoring Market Report Scope

Report Attribute

Specifications

Growth Rate CAGR

CAGR of 25.9% from 2024 to 2031

Quantitative Units

Representation of revenue in US$ Million and CAGR from 2024 to 2031

Historic Year

2019 to 2023

Forecast Year

2024-2031

Report Coverage

The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends

Segments Covered

By Component, Application, And Industry Vertical

Regional Scope

North America; Europe; Asia Pacific; Latin America; Middle East & Africa

Country Scope

U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; Southeast Asia; South Korea

Competitive Landscape

FICO (Fair Isaac Corporation), Experian, Equifax, TransUnion, Zest AI, LenddoEFL, Kreditech, CreditVidya, CreditXpert, Upstart, Pagaya, Underwrite.ai, Kensho Technologies, Scienaptic, DataRobot, ClearScore, ScoreData, CredoLab, and Trust Science, and others

Customization Scope

Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape.

Pricing And Available Payment Methods

Explore pricing alternatives that are customized to your particular study requirements.

 

Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global AI in Credit Scoring Market Snapshot

Chapter 4. Global AI in Credit Scoring Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: By Component Estimates & Trend Analysis
5.1. By Component & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Component:

5.2.1. Software
5.2.2. Service

Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:

6.2.1. Personal Credit Scoring
6.2.2. Corporate Credit Scoring

Chapter 7. Market Segmentation 3: by Industry Vertical Estimates & Trend Analysis
7.1. by Industry Vertical & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Industry Vertical:

7.2.1. BFSI
7.2.1.1. Banking
7.2.1.2. Financial Services
7.2.1.3. Insurance
7.2.2. Retail
7.2.3. Healthcare
7.2.4. Telecommunications
7.2.5. Utilities
7.2.6. Real Estate

Chapter 8. AI in Credit Scoring Market Segmentation 4: Regional Estimates & Trend Analysis

8.1. North America
8.1.1. North America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts By Component, 2024-2031
8.1.2. North America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.1.3. North America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Industry Vertical, 2024-2031
8.1.4. North America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.2. Europe
8.2.1. Europe AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts By Component, 2024-2031
8.2.2. Europe AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.2.3. Europe AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Industry Vertical, 2024-2031
8.2.4. Europe AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.3. Asia Pacific
8.3.1. Asia Pacific AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts By Component, 2024-2031
8.3.2. Asia Pacific AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.3.3. Asia-Pacific AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Industry Vertical, 2024-2031
8.3.4. Asia Pacific AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.4. Latin America
8.4.1. Latin America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts By Component, 2024-2031
8.4.2. Latin America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.4.3. Latin America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Industry Vertical, 2024-2031
8.4.4. Latin America AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.5. Middle East & Africa
8.5.1. Middle East & Africa AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts By Component, 2024-2031
8.5.2. Middle East & Africa AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.5.3. Middle East & Africa AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by Industry Vertical, 2024-2031
8.5.4. Middle East & Africa AI in credit scoring Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles

9.2.1. FICO (Fair Isaac Corporation)
9.2.2. Experian
9.2.3. Equifax
9.2.4. TransUnion
9.2.5. Zest AI
9.2.6. LenddoEFL
9.2.7. Kreditech
9.2.8. CreditVidya
9.2.9. CreditXpert
9.2.10. Upstart
9.2.11. Pagaya
9.2.12. Underwrite.ai
9.2.13. Kensho Technologies
9.2.14. Scienaptic
9.2.15. DataRobot
9.2.16. Datrics
9.2.17. ClearScore
9.2.18. ScoreData
9.2.19. CredoLab
9.2.20. Trust Science
9.2.21. Other Prominent Players

Segmentation Of AI In Credit Scoring Market-

AI In Credit Scoring Market By Component

  • Software
  • Service

ai in credit score

AI In Credit Scoring Market By Application

  • Personal Credit Scoring
  • Corporate Credit Scoring

AI In Credit Scoring Market By Industry Vertical

  • BFSI
    • Banking,
    • Financial Services,
    • Insurance
  • Retail,
  • Healthcare,
  • Telecommunications,
  • Utilities,
  • Real Estate

AI In Credit Scoring Market By Region-

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

 

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Frequently Asked Questions

What is the AI In Credit-Scoring Market Growth?

FICO (Fair Isaac Corporation), Experian, Equifax, TransUnion, Zest AI, LenddoEFL, Kreditech, CreditVidya, CreditXpert, Upstart, Pagaya, Underwrite.ai,

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