1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Predictive Analytics in Banking Market Size Growth Rate by Type: 2017 VS 2021 VS 2028
1.2.2 Customer Analytics
1.2.3 White-Collar Automation
1.2.4 Credit Scoring
1.2.5 Trading Insight
1.2.6 Other
1.3 Market by Application
1.3.1 Global Predictive Analytics in Banking Market Share by Application: 2017 VS 2021 VS 2028
1.3.2 Small & Medium Enterprises (SMES)
1.3.3 Large Enterprises
1.4 Study Objectives
1.5 Years Considered
2 Global Growth Trends
2.1 Global Predictive Analytics in Banking Market Perspective (2017-2028)
2.2 Predictive Analytics in Banking Growth Trends by Region
2.2.1 Predictive Analytics in Banking Market Size by Region: 2017 VS 2021 VS 2028
2.2.2 Predictive Analytics in Banking Historic Market Size by Region (2017-2022)
2.2.3 Predictive Analytics in Banking Forecasted Market Size by Region (2023-2028)
2.3 Predictive Analytics in Banking Market Dynamics
2.3.1 Predictive Analytics in Banking Industry Trends
2.3.2 Predictive Analytics in Banking Market Drivers
2.3.3 Predictive Analytics in Banking Market Challenges
2.3.4 Predictive Analytics in Banking Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Predictive Analytics in Banking Players by Revenue
3.1.1 Global Top Predictive Analytics in Banking Players by Revenue (2017-2022)
3.1.2 Global Predictive Analytics in Banking Revenue Market Share by Players (2017-2022)
3.2 Global Predictive Analytics in Banking Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Predictive Analytics in Banking Revenue
3.4 Global Predictive Analytics in Banking Market Concentration Ratio
3.4.1 Global Predictive Analytics in Banking Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Predictive Analytics in Banking Revenue in 2021
3.5 Predictive Analytics in Banking Key Players Head office and Area Served
3.6 Key Players Predictive Analytics in Banking Product Solution and Service
3.7 Date of Enter into Predictive Analytics in Banking Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Predictive Analytics in Banking Breakdown Data by Type
4.1 Global Predictive Analytics in Banking Historic Market Size by Type (2017-2022)
4.2 Global Predictive Analytics in Banking Forecasted Market Size by Type (2023-2028)
5 Predictive Analytics in Banking Breakdown Data by Application
5.1 Global Predictive Analytics in Banking Historic Market Size by Application (2017-2022)
5.2 Global Predictive Analytics in Banking Forecasted Market Size by Application (2023-2028)
6 North America
6.1 North America Predictive Analytics in Banking Market Size (2017-2028)
6.2 North America Predictive Analytics in Banking Market Size by Country (2017-2022)
6.3 North America Predictive Analytics in Banking Market Size by Country (2023-2028)
6.4 United States
6.5 Canada
7 Europe
7.1 Europe Predictive Analytics in Banking Market Size (2017-2028)
7.2 Europe Predictive Analytics in Banking Market Size by Country (2017-2022)
7.3 Europe Predictive Analytics in Banking Market Size by Country (2023-2028)
7.4 Germany
7.5 France
7.6 U.K.
7.7 Italy
7.8 Russia
7.9 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Predictive Analytics in Banking Market Size (2017-2028)
8.2 Asia-Pacific Predictive Analytics in Banking Market Size by Country (2017-2022)
8.3 Asia-Pacific Predictive Analytics in Banking Market Size by Country (2023-2028)
8.4 China
8.5 Japan
8.6 South Korea
8.7 Southeast Asia
8.8 India
8.9 Australia
9 Latin America
9.1 Latin America Predictive Analytics in Banking Market Size (2017-2028)
9.2 Latin America Predictive Analytics in Banking Market Size by Country (2017-2022)
9.3 Latin America Predictive Analytics in Banking Market Size by Country (2023-2028)
9.4 Mexico
9.5 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Predictive Analytics in Banking Market Size (2017-2028)
10.2 Middle East & Africa Predictive Analytics in Banking Market Size by Country (2017-2022)
10.3 Middle East & Africa Predictive Analytics in Banking Market Size by Country (2023-2028)
10.4 Turkey
10.5 Saudi Arabia
10.6 UAE
11 Key Players Profiles
11.1 Accretive Technologies Inc.
11.1.1 Accretive Technologies Inc. Company Detail
11.1.2 Accretive Technologies Inc. Business Overview
11.1.3 Accretive Technologies Inc. Predictive Analytics in Banking Introduction
11.1.4 Accretive Technologies Inc. Revenue in Predictive Analytics in Banking Business (2017-2022)
11.1.5 Accretive Technologies Inc. Recent Development
11.2 Angoss Software Corporation
11.2.1 Angoss Software Corporation Company Detail
11.2.2 Angoss Software Corporation Business Overview
11.2.3 Angoss Software Corporation Predictive Analytics in Banking Introduction
11.2.4 Angoss Software Corporation Revenue in Predictive Analytics in Banking Business (2017-2022)
11.2.5 Angoss Software Corporation Recent Development
11.3 FICO
11.3.1 FICO Company Detail
11.3.2 FICO Business Overview
11.3.3 FICO Predictive Analytics in Banking Introduction
11.3.4 FICO Revenue in Predictive Analytics in Banking Business (2017-2022)
11.3.5 FICO Recent Development
11.4 HP
11.4.1 HP Company Detail
11.4.2 HP Business Overview
11.4.3 HP Predictive Analytics in Banking Introduction
11.4.4 HP Revenue in Predictive Analytics in Banking Business (2017-2022)
11.4.5 HP Recent Development
11.5 IBM
11.5.1 IBM Company Detail
11.5.2 IBM Business Overview
11.5.3 IBM Predictive Analytics in Banking Introduction
11.5.4 IBM Revenue in Predictive Analytics in Banking Business (2017-2022)
11.5.5 IBM Recent Development
11.6 Information Builders
11.6.1 Information Builders Company Detail
11.6.2 Information Builders Business Overview
11.6.3 Information Builders Predictive Analytics in Banking Introduction
11.6.4 Information Builders Revenue in Predictive Analytics in Banking Business (2017-2022)
11.6.5 Information Builders Recent Development
11.7 KXEN Inc.
11.7.1 KXEN Inc. Company Detail
11.7.2 KXEN Inc. Business Overview
11.7.3 KXEN Inc. Predictive Analytics in Banking Introduction
11.7.4 KXEN Inc. Revenue in Predictive Analytics in Banking Business (2017-2022)
11.7.5 KXEN Inc. Recent Development
11.8 Microsoft
11.8.1 Microsoft Company Detail
11.8.2 Microsoft Business Overview
11.8.3 Microsoft Predictive Analytics in Banking Introduction
11.8.4 Microsoft Revenue in Predictive Analytics in Banking Business (2017-2022)
11.8.5 Microsoft Recent Development
11.9 Oracle
11.9.1 Oracle Company Detail
11.9.2 Oracle Business Overview
11.9.3 Oracle Predictive Analytics in Banking Introduction
11.9.4 Oracle Revenue in Predictive Analytics in Banking Business (2017-2022)
11.9.5 Oracle Recent Development
11.10 Salford Systems
11.10.1 Salford Systems Company Detail
11.10.2 Salford Systems Business Overview
11.10.3 Salford Systems Predictive Analytics in Banking Introduction
11.10.4 Salford Systems Revenue in Predictive Analytics in Banking Business (2017-2022)
11.10.5 Salford Systems Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details

 

Research Methodology

 

SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.

PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.

MARKET ENGINEERING
The market engineering phase involves analysing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.

EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.

REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.