Prominent Predictive Analytics in Banking Market Trend for 2025: AI-Powered Data Analytics Platform Revolutionizing Predictive Analytics in Banking

Which drivers are expected to have the greatest impact on the over the predictive analytics in banking market's growth?
The growth of predictive analytics in the banking sector is likely to be fueled by the escalating prevalence of fraudulent activities. Such activities encompass deliberate schemes or actions aimed to mislead, deceive, manipulate organizations or individuals for personal or monetary advantage. The banking sector is witnessing a surge in such fraudulent activities, amplified by increasing cyberattacks and the burgeoning usage of digital banking services. Predictive analytics in banking serves as a deterrent to these illegal activities by employing sophisticated algorithms to recognize and alert about irregular patterns and behaviours in real time, facilitating proactive fraud detection and prevention. As an illustration, the Federal Trade Commission, a US government agency, reported in February 2024 that consumers had fallen victim to fraud amounting to over $10 billion in 2023, signifying a 14% hike from the losses recorded in the preceding year. Thus, the mounting prevalence of fraudulent activities is pushing the growth of predictive analytics in the banking industry.

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What is the future CAGR of the predictive analytics in banking market, and how will it impact industry expansion?
The market for predictive analytics in banking has seen a significant growth spurt in recent times, and it's expected to increase from $3.84 billion in 2024 to a projected $4.64 billion in 2025, demonstrating a compound annual growth rate (CAGR) of 21.0%. The boost witnessed during the historic period can be traced back to aspects such as credit risk evaluation, fraud detection and prevention measures, customer categorization and customization, regulatory adherence and improvements in operational efficiency.

The market for predictive analytics in banking is projected to experience substantial growth in the coming years, with its value estimated to reach $9.85 billion by 2029, clocking a compound annual growth rate (CAGR) of 20.7%. The expansion during the forecast period is largely due to the increased use of artificial intelligence and machine learning, the rise of big data and real-time analytics, regulatory demands and compliance, customer demand for personalized services, and measures to prevent cybercrime and fraud. Key trends for the forecast period include improved customer interaction through personalization, the application of AI and machine learning in advanced predictive systems, instantaneous decision-making through real-time predictive analytics, a heightened emphasis on cybersecurity and fraud deterrence, and regulatory compliance and risk management.

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What are the most significant trends transforming the predictive analytics in banking market today?
Leading companies in the predictive analytics in banking market are advancing with inventive solutions like artificial intelligence (AI) infused data analytics platforms to evaluate businesses and decode data, enabling expedited insights and better-informed decision-making. AI-facilitated data analytics platforms amplify banking via the utilisation of sophisticated data processing, predictive modelling, and pattern recognition to enhance risk management, customise customer experiences, combat fraud, simplify operations, and reveal new avenues for growth. For instance, in March 2024, TransUnion, a US-based IT firm, introduced OneTru, an AI-driven data analytics platform, aimed at augmenting data accessibility and decision-making for financial institutions. This cloud-powered platform blends data analytics, credit risk management, and fraud detection solutions into a consolidated gateway, capitalizing on artificial intelligence and machine learning. OneTru unites disjointed data sources, granting users the ability to access credit bureau, consumer identity, and marketing data in a streamlined way. This integration is devised to enhance the speed and quality of analytics, hastening insights and client decision-making procedures.

Which key market segments comprise the predictive analytics in banking market and drive its revenue growth?
The predictive analytics in banking market covered in this report is segmented -

1) By Type: Marketing; Sales; Finance; Human resource; Operations
2) By Component: Solution; Services
3) By Deployment Model: On-Premise; Cloud
4) By Application: Small And Medium Enterprises (SMES); Large Enterprises

Subsegments:
1) By Marketing: Customer Segmentation And Targeting; Campaign Management And Optimization; Customer Lifetime Value Prediction; Churn Prediction and Retention Strategies; Market Trend Analysis; Brand Sentiment Analysis
2) By Sales: Lead Scoring and Opportunity Management; Sales Forecasting And Trend Analysis; Cross-Selling And Up-Selling Strategies; Sales Performance Optimization; Conversion Rate Prediction; Territory Management
3) By Finance: Credit Scoring And Risk Assessment; Fraud Detection And Prevention; Financial Forecasting and Budgeting; Loan Default Prediction; Asset Management And Investment Analysis; Regulatory Compliance Analytics
4) By Human Resource: Employee Attrition Prediction; Talent Acquisition And Recruitment Optimization; Workforce Planning And Optimization; Employee Performance Analytics; Learning and Development Needs Prediction; Compensation And Benefits Analysis
5) By Operations: Process Efficiency Optimization; Operational Cost Prediction And Management; Resource Allocation And Scheduling; Transaction Monitoring And Anomaly Detection; Supply Chain Management Optimization; Automation Of Operational Tasks

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What regions are at the forefront of predictive analytics in banking market expansion?
North America was the largest region in the predictive analytics in banking market in 2024. The regions covered in the predictive analytics in banking market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Who are the leading players fueling growth in the predictive analytics in banking market?
Major companies operating in the predictive analytics in banking market are Microsoft Corporation, Amazon Web Services Inc., International Business Machines Corporation, Oracle Corporation, SAS Institute Inc., Turing Analytics, Databricks Inc., Alteryx Inc., H2O.ai, EdgeVerve Systems Limited, Google Cloud, Dataiku, Datarobot Inc., Feature Labs, KNIME, Altair Engineering Inc., Rasa, Peltarion, Auger.AI, BigML, Big Squid Inc, dotData Inc., Determined.ai Inc., Turi

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What Is Covered In The Predictive Analytics in Banking Global Market Report?

•Market Size Forecast: Examine the predictive analytics in banking market size across key regions, countries, product categories, and applications.
•Segmentation Insights: Identify and classify subsegments within the predictive analytics in banking market for a structured understanding.
•Key Players Overview: Analyze major players in the predictive analytics in banking market, including their market value, share, and competitive positioning.
•Growth Trends Exploration: Assess individual growth patterns and future opportunities in the predictive analytics in banking market.
•Segment Contributions: Evaluate how different segments drive overall growth in the predictive analytics in banking market.
•Growth Factors: Highlight key drivers and opportunities influencing the expansion of the predictive analytics in banking market.
•Industry Challenges: Identify potential risks and obstacles affecting the predictive analytics in banking market.
•Competitive Landscape: Review strategic developments in the predictive analytics in banking market, including expansions, agreements, and new product launches.

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With over 15,000+ reports from 27 industries covering 60+ geographies, The Business Research Company has built a reputation for offering comprehensive, data-rich research and insights. Our flagship product, the Global Market Model delivers comprehensive and updated forecasts to support informed decision-making.

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