The global predictive analytics in banking market size reached US$ 3.7 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 11.2 Billion by 2028, exhibiting a growth rate (CAGR) of 18.7% during 2023-2028. The increasing volume of data, the surging need to adhere to regulatory compliance and the rising incidences of fraudulent activities represent some of the key factors driving the market.
|Market Size in 2022
||US$ 3.7 Billion
|Market Forecast in 2028
||US$ 11.2 Billion
|Market Growth Rate (2023-2028)
Predictive analytics has become an integral part of the banking industry, allowing banks to make data-driven decisions to improve customer experience, minimize risk, and maximize profits. It involves using statistical models and machine learning algorithms to analyze large data sets to identify patterns and predict future events. It is also used for a variety of purposes, including fraud detection, customer acquisition and retention, risk management, and marketing. Banks use these solutions to identify unusual patterns and flag potentially fraudulent activity in real time, preventing losses to the bank and customers. They can also be employed to identify which customers are most likely to leave the bank or take out a new loan, allowing banks to tailor their marketing efforts and improve customer retention. In addition, predictive analytics can be used to assess the creditworthiness of customers, helping banks make informed lending decisions and minimize the risk of default. Moreover, banks can identify high-risk borrowers and set appropriate interest rates to reduce the likelihood of default. Owing to these properties, predictive analytics has become an essential tool for banks to make data-driven decisions, improve customer experience, and manage risk effectively.
Predictive Analytics in Banking Market Trends:
The market is primarily driven by the increasing volumes of data in the banking sector. The amount of data generated by the banking industry is growing rapidly, including transactional data, customer data, and market data. Predictive analytics can help banks make sense of this data and turn it into actionable insights. In addition, the growing competition among banking companies and the entry of new players are escalating the demand for predictive analysis to stay ahead of the competition by identifying new market opportunities and predicting customer behavior. Besides this, the banking industry is highly regulated, and banks must comply with a range of regulations, such as anti-money laundering (AML) and know-your-customer (KYC) regulations. This surging need to adhere to regulatory compliances is accelerating the product adoption rate to identify potential compliance issues. Moreover, the rising incidence of fraudulent activities such as money laundering, payment card fraud, and fraudulent loans is also contributing to market growth. Furthermore, the increasing adoption of various competitive strategies by the leading market players, such as product portfolio expansion, mergers and acquisitions (M&As), agreements, geographical expansion, and collaborations, are also creating a favorable market outlook across the globe.
Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each segment of the global predictive analytics in banking market report, along with forecasts at the global, regional, and country levels for 2023-2028. Our report has categorized the market based on component, deployment model, organization size, and applications.
- Procure- to- Pay Solutions
- Supply and Risk Management
- Travel and Expense Management
- Contract and E-Tender Management
- Spend Management/Spend Analytics
- Managed Services
- Professional Service
The report has provided a detailed breakup and analysis of the predictive analytics in banking market based on the component. This includes solution (procure- to- pay solutions, supply and risk management, travel and expense management, contract and e-tender management, spend management/spend analytics, others) and services (managed services, professional services). According to the report, solutions represented the largest segment.
Deployment Model Insights:
A detailed breakup and analysis of the predictive analytics in banking market based on the deployment model has also been provided in the report. This includes cloud-based and on-premises. According to the report, on-premises accounted for the largest market share.
Organization Size Insights:
- Large Enterprises
- Small and Medium-sized Enterprises
The report has provided a detailed breakup and analysis of the predictive analytics in banking market based on the organization size. This includes large enterprises and small and medium-sized enterprises. According to the report, large enterprises represented the largest segment.
- Fraud Detection and Prevention
- Customer Management
- Sales and Marketing
- Workforce Management
A detailed breakup and analysis of the predictive analytics in banking market based on the application has also been provided in the report. This includes fraud detection and prevention, customer management, sales and marketing, workforce management, and others. According to the report, customer management accounted for the largest market share.
- North America
- United Kingdom
- Asia Pacific
- South Korea
- Latin America
- Middle East and Africa
The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Europe (Germany, France, the United Kingdom, Italy, Spain, and others); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America was the largest market for predictive analytics in banking. Some of the factors driving the North America predictive analytics in banking market included the surging need for risk management solutions, the increasing focus on customer experience, and the rising volume of data.
The report has also provided a comprehensive analysis of the competitive landscape in global predictive analytics in banking market. Competitive analysis such as market structure, market share by key players, player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided. Some of the companies covered include Alteryx Inc., FICO, International Business Machines Corporation, Oracle Corporation, SAS Institute Inc., Tableau Software Inc. (Salesforce Inc), TIBCO Software Inc., etc. Kindly note that this only represents a partial list of companies, and the complete list has been provided in the report.
Predictive Analytics in Banking Market Report Scope:
|Base Year of the Analysis
| Historical Period
|Scope of the Report
||Exploration of Historical Trends and Market Outlook, Industry Catalysts and Challenges, Segment-Wise Historical and Predictive Market Assessment: ·
- Deployment Model
- Organization Size
- Solutions: Procure- to- Pay Solutions, Supply and Risk Management, Travel and Expense Management, Contract and E-Tender Management, Spend Management/Spend Analytics, Others
- Services: Managed Services, Professional Service
|Deployment Models Covered
|Organization Sizes Covered
||Large Enterprises, Small and Medium-sized Enterprises
||Fraud Detection and Prevention Customer Management, Sales and Marketing, Workforce Management, Others
||North America, Europe, Asia Pacific, Latin America, Middle East and Africa
||United States, Canada, Germany, France, United Kingdom, Italy, Spain, China, Japan, India, South Korea, Australia, Indonesia, Brazil, Mexico
||Alteryx Inc., FICO, International Business Machines Corporation, Oracle Corporation, SAS Institute Inc., Tableau Software Inc. (Salesforce Inc), TIBCO Software Inc., etc.
||10% Free Customization
|Report Price and Purchase Option
||Single User License: US$ 2499
Five User License: US$ 3499
Corporate License: US$ 4499
|Post-Sale Analyst Support
||PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)
Key Questions Answered in This Report:
- How has the global predictive analytics in banking market performed so far, and how will it perform in the coming years?
- What are the drivers, restraints, and opportunities in the global predictive analytics in banking market?
- What is the impact of each driver, restraint, and opportunity on the global predictive analytics in banking market?
- What are the key regional markets?
- Which countries represent the most attractive predictive analytics in banking market?
- What is the breakup of the market based on component?
- Which is the most attractive component in predictive analytics in banking market?
- What is the breakup of the market based on deployment model?
- Which is the most attractive deployment model in predictive analytics in banking market?
- What is the breakup of the market based on organization size?
- Which is the most attractive organization size in predictive analytics in banking market?
- What is the breakup of the market based on application?
- Which is the most attractive application in predictive analytics in banking market?
- What is the competitive structure of the global predictive analytics in banking market?
- Who are the key players/companies in the global predictive analytics in banking market?
Key Benefits for Stakeholders:
- IMARC’s report offers a comprehensive quantitative analysis of various market segments, historical and current market trends, market forecasts, and dynamics of the predictive analytics in banking market from 2017-2028.
- The research study provides the latest information on the market drivers, challenges, and opportunities in the global predictive analytics in banking market.
- The study maps the leading, as well as the fastest-growing, regional markets. It further enables stakeholders to identify the key country-level markets within each region.
- Porter's five forces analysis assist stakeholders in assessing the impact of new entrants, competitive rivalry, supplier power, buyer power, and the threat of substitution. It helps stakeholders to analyze the level of competition within the predictive analytics in banking industry and its attractiveness.
- Competitive landscape allows stakeholders to understand their competitive environment and provides an insight into the current positions of key players in the market.