‘Predictive Analytics in Banking market’ research report provides the up-to-the-minute industry qualitative research data and industry upcoming trends, allowing you to identify the products and end users driving Revenue growth and productivity. The Predictive Analytics in Banking industry report lists the leading competitors and provides the insights strategic industry Analysis of the key factors influencing the market. The report includes the forecasts, breakdown, and discussion of important industry trends, market size, market share estimates and profiles of the leading industry Companies.
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Predictive analytics comprises predictive model, and data mining using multivariate analyzing techniques such as time series, regression analysis, and decision tree. The technology uses several statistical and analytical techniques for developing predictive models to deliver enhanced solutions by identifying outcome of future events and customer behavior of organizations through historical data & current data. This technique allows banks and financial industry for analyzing customer behavior, customer segmentation, risk assessment and future trend. The banks build a customer experience strategy to make improvements in their email & print communications, financial services and online & mobile banking services. These enhanced improvements in customer experience have been helping organizations to boost profit and increase customer retentions. Moreover, the predictive analytics offers a clear view into customer satisfaction trend, better risk and complaint management, cross sell & up sell opportunities, thus help in increasing operational efficiency of banks.
Predictive analytics have been helping the bank and financial institutions to predict their incoming and outgoing property payment and customer flow, which is driving the growth of the market. In addition, significant increase in fraudulent activities such as accounting fraud, money laundering and payment card fraud, is the major factor driving the global predictive analytics in banking market growth. However, issues associated with implementation and integration among banks and financial institutions hamper the growth of the market. Conversely, integration of artificial intelligence in mobile banking apps and a rise in demand from developing economies are expected to provide major opportunities for the growth of the predictive analytics in banking market during the forecast period.
The global predictive analytics in banking market is segmented on the basis of component, deployment model, organization size, application, and region. In terms of component, it is bifurcated into solution and services. Based on deployment model, the market is segmented into on-premise and cloud. In terms of organization, the market is segmented into large enterprises and SMEs. As per application, it is divided into fraud detection & prevention, customer management, sales & marketing, workforce management and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The qualitative research report on ‘Predictive Analytics in Banking market’covering fundamental strategic developments of the market, key market features, including revenue, capacity, price, capacity utilization rate, production rate, gross, production, consumption, import/export, supply/demand, cost, market share, CAGR, and gross margin. In addition to that, the study provides a comprehensive analysis of the key market factors and their latest trends, along with relevant market segments and sub-segments.
The in-depth information by segments of the Predictive Analytics in Banking market:
|Key players: Alteryx, Inc., Fair Isaac Corporation, IBM Corporation, Microsoft corporation, Oracle Corporation, SAP SE, SAS Institute, Inc., Tableau Software, Inc., Teradata Corporation and TIBCO Software, Inc.|
|By Component (Solution and Service), Deployment Model (On-Premise and Cloud), Organization Size (Large Enterprise and SME), Application (Fraud Detection and Prevention, Customer Management, Sales and Marketing, Workforce Management and Others)|
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Market analysis on the basis of types, services, and regions; customizations can be done as per company specific needs.
- Detailed country analysis
- In-depth country wise opportunity plot analysis
- Economic analysis for major KPIs of the market
- Application segmentation of other verticals
- PESTEL, Porter and SWOT analysis of the global market.
- Demand and supply side analysis.
- Product matrix analysis.
- Country level macro factor analysis.
- Go-to-market (market entry) analysis
- Market share analysis (company/solution/region)
- Company wise portfolio analysis.
- Market ecosystem analysis.
- Market intelligence analysis (new product development tracking, M&A analysis, technological development tracking, and benchmarking analysis)
- Company analysis (Strategic, operational, and functional analysis)
Furthermore, the years considered for the study are as follows:
Historical year – 2013-2017 | Base year – 2018 | Forecast period** – 2019 to 2025 [** unless otherwise stated]
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Chapters to display the Global Predictive Analytics in Banking Market:
Chapter 1, to describe Definition, Specifications and Classification of Global Predictive Analytics in Banking, Applications of , Market Segment by Regions;
Chapter 2, to analyze the Manufacturing Cost Structure, Raw Material and Suppliers, Manufacturing Process, Industry Chain Structure;
Chapter 3, to display the Technical Data and Manufacturing Plants Analysis of , Capacity and Commercial Production Date, Manufacturing Plants Distribution, Export & Import, R&D Status and Technology Source, Raw Materials Sources Analysis;
Chapter 4, to show the Overall Market Analysis, Capacity Analysis (Company Segment), Sales Analysis (Company Segment), Sales Price Analysis (Company Segment);
Chapter 5 and 6, to show the Regional Market Analysis that includes United States, EU, Japan, China, India & Southeast Asia, Segment Market Analysis (by Type);
Chapter 7 and 8, to explore the Market Analysis by Application Major Manufacturers Analysis;
Chapter 9, Market Trend Analysis, Regional Market Trend, Market Trend by Product Type, Market Trend by Application;
Chapter 10, Regional Marketing Type Analysis, International Trade Type Analysis, Supply Chain Analysis;
Chapter 11, to analyze the Consumers Analysis of Global Predictive Analytics in Banking by region, type and application;
Chapter 12, to describe Predictive Analytics in Banking Research Findings and Conclusion, Appendix, methodology and data source;
Chapter 13, 14 and 15, to describe Predictive Analytics in Banking sales channel, distributors, traders, dealers, Research Findings and Conclusion, appendix and data source.
……..and view more in complete table of Contents
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