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市场调查报告书
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1801427

银行市场预测分析报告：趋势、预测与竞争分析（至 2031 年）

Predictive Analytics in Banking Market Report: Trends, Forecast and Competitive Analysis to 2031
出版日期: | 出版商: Lucintel | 英文 150 Pages | 商品交期: 3个工作天内

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全球银行预测分析市场前景广阔，中小企业和大型企业都面临机会。预计2025年至2031年，全球银行预测分析市场的复合年增长率将达到20.6%。该市场的主要驱动力是人工智慧分析的日益普及以及对诈欺检测解决方案日益增长的需求。

  • Lucintel 预测，在预测期内，客户分析将实现类型上的最高成长。
  • 从应用来看，中小企业有望实现高成长。
  • 按地区划分，预计亚太地区将在预测期内实现最高成长。

银行预测分析市场的新兴趋势

当今银行业的预测分析正受到几大趋势的影响，这些趋势正在重新定义银行如何理解客户、处理风险和推动业务。这些趋势的驱动力源自于新兴技术和日益增长的数据量。

  • 即时预测分析：银行正在迅速采用即时预测分析技术，以便做出即时提案、改善客户体验并降低风险，例如即时发放贷款、交易中期诈骗警报以及在客户互动时提供有针对性的优惠。这种即时性提高了反应速度和客户满意度。
  • 可解释的人工智慧促进信任和透明度：随着越来越复杂的人工智慧模型的应用，对可解释的人工智慧的需求日益增长，这种人工智慧能够提供对预测过程的洞察。这对于监管需求、客户信任以及人类监督银行自动化决策的能力至关重要。
  • 联邦学习用于协作数据分析：银行正在探索联邦学习，以克服资料隐私问题和监管障碍。联邦学习允许多家金融机构在不交换敏感客户资料的情况下联合训练人工智慧模型，从而获得更全面、更稳健的预测洞察。这种协作学习方法能够保护资料隐私。
  • 融入自然语言处理：银行越来越多地使用自然语言处理（NLP）来分析来自非传统来源（例如客户服务电话、社交媒体和新闻提要）的非结构化数据，以更深入地了解和更好地预测客户态度、新兴风险和市场发展趋势，从非传统来源解锁大量资讯。
  • 个人化财务健康的预测分析：除了传统银行产品外，利用预测分析提供个人化财务健康指导、预算能力和主动提案的新兴趋势正在超越交易银行业务。

总的来说，这些趋势正在将银行预测分析市场转变为更即时、透明、协作和以客户为中心的解决方案，从而推动更好的决策并改善整体银行体验。

银行预测分析市场的最新趋势

如今，银行业预测分析产业正在经历重大变革，旨在最大限度地提高准确性和效率，并兼顾资料使用的伦理道德。这些进步正在帮助银行获得竞争优势并赢得消费者信任。银行的目标是打造负责任且富有影响力的人工智慧。

  • AutoML 平台的新创新促进了模型的快速部署：AutoML 平台正在呈指数级发展，使银行能够以更少的人力更快地开发预测模型，从而促进了许多银行职能部门快速采用分析技术。
  • 重视特征工程和选择：银行正在加大对高级特征工程技术的投资，以从数据中提取有用的信号，以及高级特征选择技术，以提高预测模型的准确性和可解释性。
  • 开发强大的模型监控和管治模型：了解客户资料和行为不断变化的性质，银行正在开发强大的模型来不断监控其预测模型的效能，并建立治理以控制管治并保持长期准确性。
  • 透过图形资料库整合改进关係分析：银行越来越多地使用图形资料库来更好地分析资料中的复杂关係，例如客户网路和交易模式，以便在诈欺资料库和信用风险分析中做出更准确的预测。
  • 专注于保护隐私的人工智慧技术：随着资料隐私法变得越来越严格，银行正在采用和整合保护隐私的人工智慧技术，例如差异隐私和同态加密，以便在不损害客户资料的情况下使用客户资料进行预测分析。

这些趋势正在影响市场上银行的预测分析，促进更准确、更可靠的模型的快速部署、更好地理解复杂的数据关係以及更合乎道德和隐私意识的数据使用。

目录

第一章执行摘要

第二章 市场概述

  • 背景和分类
  • 供应链

第三章：市场趋势与预测分析

  • 宏观经济趋势与预测
  • 产业驱动力与挑战
  • PESTLE分析
  • 专利分析
  • 法规环境

4. 全球银行市场预测分析（按类型）

  • 概述
  • 吸引力分析：按类型
  • 顾客分析：趋势与预测（2019-2031）
  • 白领自动化：趋势与预测（2019-2031）
  • 信用评分：趋势与预测（2019-2031）
  • 贸易分析：趋势与预测（2019-2031）
  • 其他：趋势与预测（2019-2031）

5. 全球银行预测分析市场（按应用）

  • 概述
  • 吸引力分析：按用途
  • 中小企业：趋势与预测（2019-2031）
  • 大型企业：趋势与预测（2019-2031）

第六章区域分析

  • 概述
  • 全球银行市场预测分析（按地区）

7. 北美银行市场预测分析

  • 概述
  • 北美银行市场预测分析（按类型）
  • 北美银行预测分析市场（按应用）
  • 美国银行预测分析市场
  • 墨西哥银行预测分析市场
  • 加拿大银行预测分析市场

8. 欧洲银行预测分析市场

  • 概述
  • 欧洲银行预测分析市场（按类型）
  • 欧洲银行预测分析市场（按应用）
  • 德国银行预测分析市场
  • 法国银行业预测分析市场
  • 西班牙银行业预测分析市场
  • 义大利银行预测分析市场
  • 英国银行业预测分析市场

9. 亚太地区银行市场预测分析

  • 概述
  • 亚太地区银行市场预测分析（按类型）
  • 亚太地区银行预测分析市场（按应用）
  • 日本银行业预测分析市场
  • 印度银行业的预测分析市场
  • 中国银行业预测分析市场
  • 韩国银行业预测分析市场
  • 印尼银行预测分析市场

10. 其他地区（ROW）银行市场的预测分析

  • 概述
  • 世界其他地区 (ROW) 银行市场预测分析（按类型）
  • 世界其他地区 (ROW) 银行市场预测分析（按应用）
  • 中东银行预测分析市场
  • 南美银行预测分析市场
  • 非洲银行预测分析市场

第十一章 竞争分析

  • 产品系列分析
  • 营运整合
  • 波特五力分析
    • 竞争对手之间的竞争
    • 买方议价能力
    • 供应商的议价能力
    • 替代品的威胁
    • 新进入者的威胁
  • 市场占有率分析

第十二章机会与策略分析

  • 价值链分析
  • 成长机会分析
    • 按类型分類的成长机会
    • 按应用分類的成长机会
  • 全球银行市场预测分析的新兴趋势
  • 战略分析
    • 新产品开发
    • 认证和许可
    • 企业合併（M&A）、协议、合作与合资企业

第十三章 价值链主要企业概况

  • Competitive Analysis
  • Accretive Technologies
  • Angoss Software Corporation
  • FICO
  • HP
  • IBM
  • Information Builders
  • KXEN
  • Microsoft
  • Oracle
  • Salford Systems

第十四章 附录

  • 图片列表
  • 表格列表
  • 分析方法
  • 免责声明
  • 版权
  • 简称和技术单位
  • 关于 Lucintel
  • 询问

The future of the global predictive analytics in banking market looks promising with opportunities in the small & medium enterprise and large enterprise markets. The global predictive analytics in banking market is expected to grow with a CAGR of 20.6% from 2025 to 2031. The major drivers for this market are the rising adoption of AI-driven analytics, and the growing need for fraud detection solutions.

  • Lucintel forecasts that, within the type category, customer analytics is expected to witness the highest growth over the forecast period.
  • Within the application category, small & medium enterprise is expected to witness higher growth.
  • In terms of region, APAC is expected to witness the highest growth over the forecast period.

Emerging Trends in the Predictive Analytics in Banking Market

The predictive analytics banking industry is today influenced by a range of key trends that are redefining how banks understand customers, handle risk, and drive their operations. These trends tap into the latest technologies and increasingly large pools of data.

  • Real-Time Predictive Analytics: Banks are fast embracing real-time predictive analytics in order to take instant decisions like instant loan disbursements, fraud warnings in the middle of a transaction, and targeted offerings at the moment of engagement, improving customer experience and lowering risk. This in-the-moment nature enhances response and customer delight.
  • Explainable AI for Fostering Trust and Transparency: As more sophisticated AI models find increased application, there is increasing demand for explainable AI that gives insight into how predictions were arrived at. This is imperative for regulatory needs, customer trust, and the ability to exercise human oversight of automated decisions within banking.
  • Federated Learning for Collaborative Data Analysis: Banks are considering federated learning to overcome data privacy issues and regulatory barriers. Federated learning enables multiple institutions to train AI models jointly without exchanging sensitive customer data, facilitating more comprehensive and robust predictive insights. The collaborative method preserves data privacy.
  • Incorporation of Natural Language Processing: NLP is more and more used by banks to analyze unstructured data from non-traditional sources such as customer service calls, social media, and news feeds to develop a better understanding of customer attitudes, emerging risk, and market trends, boosting predictive power. This opens up rich information from non-traditional sources.
  • Predictive Analytics for Personalized Financial Wellness: Aside from legacy banking products, there's a new trend of utilizing predictive analytics to provide personalized financial wellness guidance, budgeting capabilities, and proactive suggestions to empower customers to better manage their finances, creating deeper customer relationships and loyalty. This is beyond transactional banking.

These trends collectively are transforming the predictive analytics in banking market into more real-time, transparent, collaborative, and customer-centric solutions that facilitate better decision-making and improve the overall banking experience.

Recent Developments in the Predictive Analytics in Banking Market

The predictive analytics in banking industry today is undergoing key advancements aimed at maximizing accuracy, efficiency, as well as considering ethical factors of using data. The advancements help the banks achieve competitiveness and obtain trust from consumers. The push is towards AI with responsible as well as significant impact.

  • Emerging Innovations in AutoML Platforms Facilitating Quick Deployment of Models: AutoML platforms are advancing by leaps and bounds, making it possible for banks to develop predictive models faster using less human effort, driving quick adoption of analytics across many bank functions.
  • Greater Emphasis on Feature Engineering and Selection: Banks are putting more money into sophisticated feature engineering methods to draw useful signals out of their data and using advanced feature selection techniques to enhance the accuracy and interpretability of their predictive models.
  • Development of Strong Model Monitoring and Governance Models: Understanding the ever-changing nature of customer data and behavior, banks are developing strong models for constant monitoring of their predictive models' performance and governance to control bias and sustain accuracy over time.
  • Graph Database Integration for Improved Relationship Analysis: Banks are increasingly using graph databases to better analyze intricate relationships in their data, including customer networks and patterns of transactions, to make more precise predictions in fraud detection and credit risk analysis.
  • Focus on Privacy-Preserving AI Methods: As increasing data privacy laws, banks are adopting and integrating privacy-preserving AI methods, including differential privacy and homomorphic encryption, to use data for predictive analytics without compromising customer data.

These trends are influencing the banking predictive analytics in market by facilitating quicker deployment of more accurate and trustworthy models, better understanding of intricate data relationships, and focus on ethics and privacy-driven use of data.

Strategic Growth Opportunities in the Predictive Analytics in Banking Market

The predictive analytics in banking market has significant strategic growth opportunities across different applications based on the prospect of optimizing revenues, lowering costs, and improving customer relationships. Data-driven insights can revolutionize different aspects of banking operations.

  • Improved Customer Acquisition and Retention: Predictive analytics can detect potential high-value customers and forecast churn risk, allowing banks to execute targeted marketing campaigns and proactive retention initiatives, resulting in higher market share and customer loyalty.
  • Better Credit Risk Evaluation and Loan Origination: Using advanced predictive models to evaluate creditworthiness, predict default probabilities, and automate loan origination processes can result in better lending decisions and lower credit losses.
  • Proactive Fraud Detection and Prevention: Predictive analytics in real-time can recognize unusual patterns in transactions and foresee fraudulent activities more accurately, keeping financial losses by the bank as well as customers to a bare minimum.
  • Personalized Product Recommendations and Cross-Selling: Using predictive models, banks can comprehend individual customers' needs and likes and recommend very relevant products as well as opportunities for cross-selling, thus maximizing revenue and satisfaction.
  • Optimized Branch Operations and Resource Planning: Predictive analytics can predict customer traffic, transaction levels, and branch staffing requirements, allowing for optimized resource planning, lower operational expenses, and enhanced customer service efficiency.

These strategic growth prospects demonstrate the value creation potential of predictive analytics throughout the banking value chain, from customer acquisition and retention to risk management and operation optimization, ultimately leading to profitability and competitiveness enhancement.

Predictive Analytics in Banking Market Driver and Challenges

Banking predictive analytics market is driven by a strong synergy of forces highlighting the growing prominence of data-informed decision-making in finance as well as having major challenges capable of limiting widespread and efficient usage. To tackle this dynamic developing landscape, appreciating these drivers is imperative.

The factors responsible for driving the predictive analytics in banking market include:

1. Exponential Growth in Volume and Variety of Data: The huge volumes of data created through banking transactions and customer interactions present a fertile ground for leveraging predictive analytics to extract valuable insights.

2. Improvements in Artificial Intelligence and Machine Learning: Ongoing improvements in AI and ML algorithms make it possible to create more complex and accurate predictive models for numerous banking applications.

3. Growing Regulatory Attention to Risk Management and Compliance: Regulatory demands for strengthening risk management, fraud prevention, and meeting anti-money laundering requirements propel predictive analytics adoption in the interest of better oversight.

4. Rising Customer Expectations of Personalized Services: Customers now increasingly demand personal and relevant financial products and services, which can be effectively offered by banks using predictive analytics.

5. Competitive Pressure from FinTech's and Digital-Native Banks: The emergence of nimble fintech firms and neobanks that use data analytics adds to the pressure on traditional banks to gain similar capabilities in order to be competitive.

Challenges in the predictive analytics in banking market are:

1. Data Privacy and Security Concerns: The confidential nature of financial information calls for severe data privacy and security protocols that make data access and use more challenging for predictive analytics.

2. Legacy IT Infrastructure and Data Silos: Most conventional banks are plagued by legacy IT systems and isolated data silos, which prevent smooth integration and analysis of data to support effective predictive modeling.

3. Lack of Qualified Data Scientists and Analysts: Insufficient experts with the right skills in data science, machine learning, and banking domain knowledge can slow the creation and deployment of sophisticated analytics solutions.

Strong forces of data growth, technology breakthroughs, and regulatory requirements are driving predictive analytics adoption in the banking sector. But to benefit fully from predictive analytics' disruptive power, it is essential that banks overcome barriers to data privacy, legacy, and talent onboarding.

List of Predictive Analytics in Banking Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. With these strategies predictive analytics in banking companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the predictive analytics in banking companies profiled in this report include-

  • Accretive Technologies
  • Angoss Software Corporation
  • FICO
  • HP
  • IBM
  • Information Builders
  • KXEN
  • Microsoft
  • Oracle
  • Salford Systems

Predictive Analytics in Banking Market by Segment

The study includes a forecast for the global predictive analytics in banking market by type, application, and region.

Predictive Analytics in Banking Market by Type [Value from 2019 to 2031]:

  • Customer Analytics
  • White-Collar Automation
  • Credit Scoring
  • Trading Insight
  • Others

Predictive Analytics in Banking Market by Application [Value from 2019 to 2031]:

  • Small & Medium Enterprises
  • Large Enterprises

Predictive Analytics in Banking Market by Region [Value from 2019 to 2031]:

  • North America
  • Europe
  • Asia Pacific
  • The Rest of the World

Country Wise Outlook for the Predictive Analytics in Banking Market

The global predictive analytics in banking industry is increasingly using predictive analytics to better understand customer behavior, streamline operations, and manage risks. Advances in artificial intelligence, machine learning, and big data technologies over the past few years are powering major trends in how banks in leading economies are applying predictive analytics to improve their competitive advantage and respond to changing market conditions.

  • United States: Emphasis on fraud detection and custom individual experiences. The latest innovations involve advanced AI-driven systems for real-time fraud detection and the application of prediction models in providing highly customized products and services to enhance customer retention and acquisition in a competitive marketplace.
  • China: Accelerating adoption in digital banking and credit scoring. China's banks are fast embracing predictive analytics, specifically digital banking platforms for risk assessment, credit scoring for an extensive unbanked population, and targeted marketing in their expansive digital ecosystems.
  • Germany: Regulatory compliance and risk management focus. Current developments in Germany center on using predictive analytics for more effective risk management, such as credit risk measurement and anti-money laundering initiatives, while meeting strict data privacy rules and compliance measures.
  • India: Expansion of digital lending and financial inclusion programs. India is experiencing greater application of predictive analytics to the growing space of digital lending to determine creditworthiness and extend financial inclusion to underpenetrated markets, frequently relying on alternative sources of data.
  • Japan: Customer retention and operational effectiveness in a saturated market. New trends in Japan highlight the deployment of predictive analytics to enhance customer retention in an established banking industry and operational efficiency through forecasting and resource management.

Features of the Global Predictive Analytics in Banking Market

  • Market Size Estimates: Predictive analytics in banking market size estimation in terms of value ($B).
  • Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.
  • Segmentation Analysis: Predictive analytics in banking market size by type, application, and region in terms of value ($B).
  • Regional Analysis: Predictive analytics in banking market breakdown by North America, Europe, Asia Pacific, and Rest of the World.
  • Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the predictive analytics in banking market.
  • Strategic Analysis: This includes M&A, new product development, and competitive landscape of the predictive analytics in banking market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

This report answers following 11 key questions:

  • Q.1. What are some of the most promising, high-growth opportunities for the predictive analytics in banking market by type (customer analytics, white-collar automation, credit scoring, trading insight, and others), application (small & medium enterprises and large enterprises), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
  • Q.2. Which segments will grow at a faster pace and why?
  • Q.3. Which region will grow at a faster pace and why?
  • Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
  • Q.5. What are the business risks and competitive threats in this market?
  • Q.6. What are the emerging trends in this market and the reasons behind them?
  • Q.7. What are some of the changing demands of customers in the market?
  • Q.8. What are the new developments in the market? Which companies are leading these developments?
  • Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
  • Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
  • Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Market Overview

  • 2.1 Background and Classifications
  • 2.2 Supply Chain

3. Market Trends & Forecast Analysis

  • 3.1 Macroeconomic Trends and Forecasts
  • 3.2 Industry Drivers and Challenges
  • 3.3 PESTLE Analysis
  • 3.4 Patent Analysis
  • 3.5 Regulatory Environment

4. Global Predictive Analytics in Banking Market by Type

  • 4.1 Overview
  • 4.2 Attractiveness Analysis by Type
  • 4.3 Customer Analytics: Trends and Forecast (2019-2031)
  • 4.4 White-Collar Automation: Trends and Forecast (2019-2031)
  • 4.5 Credit Scoring: Trends and Forecast (2019-2031)
  • 4.6 Trading Insight: Trends and Forecast (2019-2031)
  • 4.7 Others: Trends and Forecast (2019-2031)

5. Global Predictive Analytics in Banking Market by Application

  • 5.1 Overview
  • 5.2 Attractiveness Analysis by Application
  • 5.3 Small & Medium Enterprises: Trends and Forecast (2019-2031)
  • 5.4 Large Enterprises: Trends and Forecast (2019-2031)

6. Regional Analysis

  • 6.1 Overview
  • 6.2 Global Predictive Analytics in Banking Market by Region

7. North American Predictive Analytics in Banking Market

  • 7.1 Overview
  • 7.2 North American Predictive Analytics in Banking Market by Type
  • 7.3 North American Predictive Analytics in Banking Market by Application
  • 7.4 United States Predictive Analytics in Banking Market
  • 7.5 Mexican Predictive Analytics in Banking Market
  • 7.6 Canadian Predictive Analytics in Banking Market

8. European Predictive Analytics in Banking Market

  • 8.1 Overview
  • 8.2 European Predictive Analytics in Banking Market by Type
  • 8.3 European Predictive Analytics in Banking Market by Application
  • 8.4 German Predictive Analytics in Banking Market
  • 8.5 French Predictive Analytics in Banking Market
  • 8.6 Spanish Predictive Analytics in Banking Market
  • 8.7 Italian Predictive Analytics in Banking Market
  • 8.8 United Kingdom Predictive Analytics in Banking Market

9. APAC Predictive Analytics in Banking Market

  • 9.1 Overview
  • 9.2 APAC Predictive Analytics in Banking Market by Type
  • 9.3 APAC Predictive Analytics in Banking Market by Application
  • 9.4 Japanese Predictive Analytics in Banking Market
  • 9.5 Indian Predictive Analytics in Banking Market
  • 9.6 Chinese Predictive Analytics in Banking Market
  • 9.7 South Korean Predictive Analytics in Banking Market
  • 9.8 Indonesian Predictive Analytics in Banking Market

10. ROW Predictive Analytics in Banking Market

  • 10.1 Overview
  • 10.2 ROW Predictive Analytics in Banking Market by Type
  • 10.3 ROW Predictive Analytics in Banking Market by Application
  • 10.4 Middle Eastern Predictive Analytics in Banking Market
  • 10.5 South American Predictive Analytics in Banking Market
  • 10.6 African Predictive Analytics in Banking Market

11. Competitor Analysis

  • 11.1 Product Portfolio Analysis
  • 11.2 Operational Integration
  • 11.3 Porter's Five Forces Analysis
    • Competitive Rivalry
    • Bargaining Power of Buyers
    • Bargaining Power of Suppliers
    • Threat of Substitutes
    • Threat of New Entrants
  • 11.4 Market Share Analysis

12. Opportunities & Strategic Analysis

  • 12.1 Value Chain Analysis
  • 12.2 Growth Opportunity Analysis
    • 12.2.1 Growth Opportunities by Type
    • 12.2.2 Growth Opportunities by Application
  • 12.3 Emerging Trends in the Global Predictive Analytics in Banking Market
  • 12.4 Strategic Analysis
    • 12.4.1 New Product Development
    • 12.4.2 Certification and Licensing
    • 12.4.3 Mergers, Acquisitions, Agreements, Collaborations, and Joint Ventures

13. Company Profiles of the Leading Players Across the Value Chain

  • 13.1 Competitive Analysis
  • 13.2 Accretive Technologies
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.3 Angoss Software Corporation
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.4 FICO
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.5 HP
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.6 IBM
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.7 Information Builders
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.8 KXEN
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.9 Microsoft
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.10 Oracle
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.11 Salford Systems
    • Company Overview
    • Predictive Analytics in Banking Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing

14. Appendix

  • 14.1 List of Figures
  • 14.2 List of Tables
  • 14.3 Research Methodology
  • 14.4 Disclaimer
  • 14.5 Copyright
  • 14.6 Abbreviations and Technical Units
  • 14.7 About Us
  • 14.8 Contact Us

List of Figures

  • Figure 1.1: Trends and Forecast for the Global Predictive Analytics in Banking Market
  • Figure 2.1: Usage of Predictive Analytics in Banking Market
  • Figure 2.2: Classification of the Global Predictive Analytics in Banking Market
  • Figure 2.3: Supply Chain of the Global Predictive Analytics in Banking Market
  • Figure 2.4: Driver and Challenges of the Predictive Analytics in Banking Market
  • Figure 3.1: Trends of the Global GDP Growth Rate
  • Figure 3.2: Trends of the Global Population Growth Rate
  • Figure 3.3: Trends of the Global Inflation Rate
  • Figure 3.4: Trends of the Global Unemployment Rate
  • Figure 3.5: Trends of the Regional GDP Growth Rate
  • Figure 3.6: Trends of the Regional Population Growth Rate
  • Figure 3.7: Trends of the Regional Inflation Rate
  • Figure 3.8: Trends of the Regional Unemployment Rate
  • Figure 3.9: Trends of Regional Per Capita Income
  • Figure 3.10: Forecast for the Global GDP Growth Rate
  • Figure 3.11: Forecast for the Global Population Growth Rate
  • Figure 3.12: Forecast for the Global Inflation Rate
  • Figure 3.13: Forecast for the Global Unemployment Rate
  • Figure 3.14: Forecast for the Regional GDP Growth Rate
  • Figure 3.15: Forecast for the Regional Population Growth Rate
  • Figure 3.16: Forecast for the Regional Inflation Rate
  • Figure 3.17: Forecast for the Regional Unemployment Rate
  • Figure 3.18: Forecast for Regional Per Capita Income
  • Figure 4.1: Global Predictive Analytics in Banking Market by Type in 2019, 2024, and 2031
  • Figure 4.2: Trends of the Global Predictive Analytics in Banking Market ($B) by Type
  • Figure 4.3: Forecast for the Global Predictive Analytics in Banking Market ($B) by Type
  • Figure 4.4: Trends and Forecast for Customer Analytics in the Global Predictive Analytics in Banking Market (2019-2031)
  • Figure 4.5: Trends and Forecast for White-Collar Automation in the Global Predictive Analytics in Banking Market (2019-2031)
  • Figure 4.6: Trends and Forecast for Credit Scoring in the Global Predictive Analytics in Banking Market (2019-2031)
  • Figure 4.7: Trends and Forecast for Trading Insight in the Global Predictive Analytics in Banking Market (2019-2031)
  • Figure 4.8: Trends and Forecast for Others in the Global Predictive Analytics in Banking Market (2019-2031)
  • Figure 5.1: Global Predictive Analytics in Banking Market by Application in 2019, 2024, and 2031
  • Figure 5.2: Trends of the Global Predictive Analytics in Banking Market ($B) by Application
  • Figure 5.3: Forecast for the Global Predictive Analytics in Banking Market ($B) by Application
  • Figure 5.4: Trends and Forecast for Small & Medium Enterprises in the Global Predictive Analytics in Banking Market (2019-2031)
  • Figure 5.5: Trends and Forecast for Large Enterprises in the Global Predictive Analytics in Banking Market (2019-2031)
  • Figure 6.1: Trends of the Global Predictive Analytics in Banking Market ($B) by Region (2019-2024)
  • Figure 6.2: Forecast for the Global Predictive Analytics in Banking Market ($B) by Region (2025-2031)
  • Figure 7.1: Trends and Forecast for the North American Predictive Analytics in Banking Market (2019-2031)
  • Figure 7.2: North American Predictive Analytics in Banking Market by Type in 2019, 2024, and 2031
  • Figure 7.3: Trends of the North American Predictive Analytics in Banking Market ($B) by Type (2019-2024)
  • Figure 7.4: Forecast for the North American Predictive Analytics in Banking Market ($B) by Type (2025-2031)
  • Figure 7.5: North American Predictive Analytics in Banking Market by Application in 2019, 2024, and 2031
  • Figure 7.6: Trends of the North American Predictive Analytics in Banking Market ($B) by Application (2019-2024)
  • Figure 7.7: Forecast for the North American Predictive Analytics in Banking Market ($B) by Application (2025-2031)
  • Figure 7.8: Trends and Forecast for the United States Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 7.9: Trends and Forecast for the Mexican Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 7.10: Trends and Forecast for the Canadian Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 8.1: Trends and Forecast for the European Predictive Analytics in Banking Market (2019-2031)
  • Figure 8.2: European Predictive Analytics in Banking Market by Type in 2019, 2024, and 2031
  • Figure 8.3: Trends of the European Predictive Analytics in Banking Market ($B) by Type (2019-2024)
  • Figure 8.4: Forecast for the European Predictive Analytics in Banking Market ($B) by Type (2025-2031)
  • Figure 8.5: European Predictive Analytics in Banking Market by Application in 2019, 2024, and 2031
  • Figure 8.6: Trends of the European Predictive Analytics in Banking Market ($B) by Application (2019-2024)
  • Figure 8.7: Forecast for the European Predictive Analytics in Banking Market ($B) by Application (2025-2031)
  • Figure 8.8: Trends and Forecast for the German Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 8.9: Trends and Forecast for the French Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 8.10: Trends and Forecast for the Spanish Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 8.11: Trends and Forecast for the Italian Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 8.12: Trends and Forecast for the United Kingdom Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 9.1: Trends and Forecast for the APAC Predictive Analytics in Banking Market (2019-2031)
  • Figure 9.2: APAC Predictive Analytics in Banking Market by Type in 2019, 2024, and 2031
  • Figure 9.3: Trends of the APAC Predictive Analytics in Banking Market ($B) by Type (2019-2024)
  • Figure 9.4: Forecast for the APAC Predictive Analytics in Banking Market ($B) by Type (2025-2031)
  • Figure 9.5: APAC Predictive Analytics in Banking Market by Application in 2019, 2024, and 2031
  • Figure 9.6: Trends of the APAC Predictive Analytics in Banking Market ($B) by Application (2019-2024)
  • Figure 9.7: Forecast for the APAC Predictive Analytics in Banking Market ($B) by Application (2025-2031)
  • Figure 9.8: Trends and Forecast for the Japanese Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 9.9: Trends and Forecast for the Indian Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 9.10: Trends and Forecast for the Chinese Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 9.11: Trends and Forecast for the South Korean Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 9.12: Trends and Forecast for the Indonesian Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 10.1: Trends and Forecast for the ROW Predictive Analytics in Banking Market (2019-2031)
  • Figure 10.2: ROW Predictive Analytics in Banking Market by Type in 2019, 2024, and 2031
  • Figure 10.3: Trends of the ROW Predictive Analytics in Banking Market ($B) by Type (2019-2024)
  • Figure 10.4: Forecast for the ROW Predictive Analytics in Banking Market ($B) by Type (2025-2031)
  • Figure 10.5: ROW Predictive Analytics in Banking Market by Application in 2019, 2024, and 2031
  • Figure 10.6: Trends of the ROW Predictive Analytics in Banking Market ($B) by Application (2019-2024)
  • Figure 10.7: Forecast for the ROW Predictive Analytics in Banking Market ($B) by Application (2025-2031)
  • Figure 10.8: Trends and Forecast for the Middle Eastern Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 10.9: Trends and Forecast for the South American Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 10.10: Trends and Forecast for the African Predictive Analytics in Banking Market ($B) (2019-2031)
  • Figure 11.1: Porter's Five Forces Analysis of the Global Predictive Analytics in Banking Market
  • Figure 11.2: Market Share (%) of Top Players in the Global Predictive Analytics in Banking Market (2024)
  • Figure 12.1: Growth Opportunities for the Global Predictive Analytics in Banking Market by Type
  • Figure 12.2: Growth Opportunities for the Global Predictive Analytics in Banking Market by Application
  • Figure 12.3: Growth Opportunities for the Global Predictive Analytics in Banking Market by Region
  • Figure 12.4: Emerging Trends in the Global Predictive Analytics in Banking Market

List of Tables

  • Table 1.1: Growth Rate (%, 2023-2024) and CAGR (%, 2025-2031) of the Predictive Analytics in Banking Market by Type and Application
  • Table 1.2: Attractiveness Analysis for the Predictive Analytics in Banking Market by Region
  • Table 1.3: Global Predictive Analytics in Banking Market Parameters and Attributes
  • Table 3.1: Trends of the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 3.2: Forecast for the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 4.1: Attractiveness Analysis for the Global Predictive Analytics in Banking Market by Type
  • Table 4.2: Market Size and CAGR of Various Type in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 4.3: Market Size and CAGR of Various Type in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 4.4: Trends of Customer Analytics in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 4.5: Forecast for Customer Analytics in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 4.6: Trends of White-Collar Automation in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 4.7: Forecast for White-Collar Automation in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 4.8: Trends of Credit Scoring in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 4.9: Forecast for Credit Scoring in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 4.10: Trends of Trading Insight in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 4.11: Forecast for Trading Insight in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 4.12: Trends of Others in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 4.13: Forecast for Others in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 5.1: Attractiveness Analysis for the Global Predictive Analytics in Banking Market by Application
  • Table 5.2: Market Size and CAGR of Various Application in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 5.3: Market Size and CAGR of Various Application in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 5.4: Trends of Small & Medium Enterprises in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 5.5: Forecast for Small & Medium Enterprises in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 5.6: Trends of Large Enterprises in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 5.7: Forecast for Large Enterprises in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 6.1: Market Size and CAGR of Various Regions in the Global Predictive Analytics in Banking Market (2019-2024)
  • Table 6.2: Market Size and CAGR of Various Regions in the Global Predictive Analytics in Banking Market (2025-2031)
  • Table 7.1: Trends of the North American Predictive Analytics in Banking Market (2019-2024)
  • Table 7.2: Forecast for the North American Predictive Analytics in Banking Market (2025-2031)
  • Table 7.3: Market Size and CAGR of Various Type in the North American Predictive Analytics in Banking Market (2019-2024)
  • Table 7.4: Market Size and CAGR of Various Type in the North American Predictive Analytics in Banking Market (2025-2031)
  • Table 7.5: Market Size and CAGR of Various Application in the North American Predictive Analytics in Banking Market (2019-2024)
  • Table 7.6: Market Size and CAGR of Various Application in the North American Predictive Analytics in Banking Market (2025-2031)
  • Table 7.7: Trends and Forecast for the United States Predictive Analytics in Banking Market (2019-2031)
  • Table 7.8: Trends and Forecast for the Mexican Predictive Analytics in Banking Market (2019-2031)
  • Table 7.9: Trends and Forecast for the Canadian Predictive Analytics in Banking Market (2019-2031)
  • Table 8.1: Trends of the European Predictive Analytics in Banking Market (2019-2024)
  • Table 8.2: Forecast for the European Predictive Analytics in Banking Market (2025-2031)
  • Table 8.3: Market Size and CAGR of Various Type in the European Predictive Analytics in Banking Market (2019-2024)
  • Table 8.4: Market Size and CAGR of Various Type in the European Predictive Analytics in Banking Market (2025-2031)
  • Table 8.5: Market Size and CAGR of Various Application in the European Predictive Analytics in Banking Market (2019-2024)
  • Table 8.6: Market Size and CAGR of Various Application in the European Predictive Analytics in Banking Market (2025-2031)
  • Table 8.7: Trends and Forecast for the German Predictive Analytics in Banking Market (2019-2031)
  • Table 8.8: Trends and Forecast for the French Predictive Analytics in Banking Market (2019-2031)
  • Table 8.9: Trends and Forecast for the Spanish Predictive Analytics in Banking Market (2019-2031)
  • Table 8.10: Trends and Forecast for the Italian Predictive Analytics in Banking Market (2019-2031)
  • Table 8.11: Trends and Forecast for the United Kingdom Predictive Analytics in Banking Market (2019-2031)
  • Table 9.1: Trends of the APAC Predictive Analytics in Banking Market (2019-2024)
  • Table 9.2: Forecast for the APAC Predictive Analytics in Banking Market (2025-2031)
  • Table 9.3: Market Size and CAGR of Various Type in the APAC Predictive Analytics in Banking Market (2019-2024)
  • Table 9.4: Market Size and CAGR of Various Type in the APAC Predictive Analytics in Banking Market (2025-2031)
  • Table 9.5: Market Size and CAGR of Various Application in the APAC Predictive Analytics in Banking Market (2019-2024)
  • Table 9.6: Market Size and CAGR of Various Application in the APAC Predictive Analytics in Banking Market (2025-2031)
  • Table 9.7: Trends and Forecast for the Japanese Predictive Analytics in Banking Market (2019-2031)
  • Table 9.8: Trends and Forecast for the Indian Predictive Analytics in Banking Market (2019-2031)
  • Table 9.9: Trends and Forecast for the Chinese Predictive Analytics in Banking Market (2019-2031)
  • Table 9.10: Trends and Forecast for the South Korean Predictive Analytics in Banking Market (2019-2031)
  • Table 9.11: Trends and Forecast for the Indonesian Predictive Analytics in Banking Market (2019-2031)
  • Table 10.1: Trends of the ROW Predictive Analytics in Banking Market (2019-2024)
  • Table 10.2: Forecast for the ROW Predictive Analytics in Banking Market (2025-2031)
  • Table 10.3: Market Size and CAGR of Various Type in the ROW Predictive Analytics in Banking Market (2019-2024)
  • Table 10.4: Market Size and CAGR of Various Type in the ROW Predictive Analytics in Banking Market (2025-2031)
  • Table 10.5: Market Size and CAGR of Various Application in the ROW Predictive Analytics in Banking Market (2019-2024)
  • Table 10.6: Market Size and CAGR of Various Application in the ROW Predictive Analytics in Banking Market (2025-2031)
  • Table 10.7: Trends and Forecast for the Middle Eastern Predictive Analytics in Banking Market (2019-2031)
  • Table 10.8: Trends and Forecast for the South American Predictive Analytics in Banking Market (2019-2031)
  • Table 10.9: Trends and Forecast for the African Predictive Analytics in Banking Market (2019-2031)
  • Table 11.1: Product Mapping of Predictive Analytics in Banking Suppliers Based on Segments
  • Table 11.2: Operational Integration of Predictive Analytics in Banking Manufacturers
  • Table 11.3: Rankings of Suppliers Based on Predictive Analytics in Banking Revenue
  • Table 12.1: New Product Launches by Major Predictive Analytics in Banking Producers (2019-2024)
  • Table 12.2: Certification Acquired by Major Competitor in the Global Predictive Analytics in Banking Market