Global Predictive Analytics in Banking Market Report By Component (Solution and Service), By Deployment Model (On-Premise and Cloud), By Organization Size (Large Enterprise and SME), By Application (Fraud Detection and Prevention, Customer Management, Sales and Marketing, Workforce Management and Others), And By Regions - Industry Trends, Size, Share, Growth, Estimation and Forecast, 2023-2032
The global demand for Predictive Analytics in Banking Market is presumed to reach the valuation of nearly USD XX MN by 2028 from USD XX MN in 2021 with a CAGR of XX% during the period of 2022-2028.
Predictive analysis is a process of anticipating future events based on computer models. The prediction relies on data mining, and machine learning to analyze enormous amounts of information. In the banking sector, predictive analytics can help manage to cross-sell and upsell, segmentation, customer retention, fraud detection, collection, expense, liquidity planning, and account transaction management.
The banking sector is struggling with two challenges: fraud fight and adoption of the latest technology to stay competitive. The predictive analytics helps to cope with this struggle. Along with this, predictive analysis automates work, improves visibility, adapts automatically, deploy in multi-channel applications. There is a growing pressure of clients on financial service providers to offer more personalized solutions, easy-to-access products, and the overall better customer experience in line with strict security and privacy standards. Predictive analytics can help at numerous touchpoints and streamline more than a few operations to accomplish this disparity between client demands and banking goals.
The report covers Porter's Five Forces Model, Market Attractiveness Analysis and Value Chain analysis. These tools help to get a clear picture of the industry's structure and evaluate the competition attractiveness at a global level.
Additionally, these tools also give inclusive assessment of each application/product segment in the global market of Predictive Analytics in Banking.
The entire Predictive Analytics in banking market has been sub-categorized into type, application, and end-user. The report provides an analysis of these subsets with respect to the geographical segmentation. This research study will keep marketer informed and helps to identify the target demographics for a product or service.
By Deployment Model
By Organization Size
Fraud Detection & Prevention
Sales & Marketing
This section covers regional segmentation which accentuates on current and future demand for Predictive Analytics in Banking market across North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa. Further, the report focuses on demand for individual application segment across all the prominent regions.
Global Predictive Analytics in Banking Market Share by Region (Representative Graph)
The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide. The major players in the Predictive Analytics in Banking market include Alteryx Inc., Fair Isaac Corporation, IBM Corporation, Microsoft corporation, Oracle Corporation. This section includes a holistic view of the competitive landscape that includes various strategic developments such as key mergers & acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.
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1 . PREFACE
1.1. Report Description
1.1.2. Target Audience
1.1.3. Unique Selling Proposition (USP) & offerings
1.2. Research Scope
1.3. Research Methodology
1.3.1. Market Research Process
1.3.2. Market Research Methodology
2 . EXECUTIVE SUMMARY
2.1. Highlights of Predictive Analytics In Banking Market
2.2. Global Predictive Analytics In Banking Market Snapshot
3 . PREDICTIVE ANALYTICS IN BANKING – INDUSTRY ANALYSIS
3.2. Market Drivers of Predictive Analytics In Banking Market
3.3. Market Restraints of Predictive Analytics In Banking Market
3.4. Opportunities of Predictive Analytics In Banking Market
3.5. Trends of Predictive Analytics In Banking Market
3.6. Porter's Five Force Analysis of Predictive Analytics In Banking Market
3.7. Predictive Analytics In Banking Market Attractiveness Analysis
3.7.1 Market Attractive Analysis by Component
3.7.2 Market Attractive Analysis by Deployment Model
3.7.3 Market Attractive Analysis by â€‹Organization Size
3.7.4 Market Attractive Analysis by Application
3.7.5 Market Attractive Analysis by Region
4 . VALUE CHAIN ANALYSIS
4.1. Predictive Analytics In Banking Value Chain Analysis
4.2. Predictive Analytics In Banking Raw Material Analysis
4.2.1. List of Raw Materials
4.2.2. Predictive Analytics In Banking Raw Material Manufactures List
4.2.3. Price Trend of Predictive Analytics In Banking Key Raw Materials
4.3. List of Potential Buyers
4.4. Marketing Channel
4.4.1. Direct Marketing
4.4.2. Indirect Marketing
4.4.3. Marketing Channel Development Trend