The Predictive Analytics in Banking Market has witnessed continuous growth in the past few years and is projected to grow even further during the forecast period (2019-2027). The assessment provides a 360° view and insights, outlining the key outcomes of the industry. These insights help the business decision-makers to formulate better business plans and make informed decisions for improved profitability. In addition, the study helps venture or private players in understanding the companies more precisely to make better informed decisions.
Major Players are:
IBM Corporation (United States) , Microsoft Corporation (United States) , Oracle Corporation (United States) , SAP SE (Germany) , SAS Institute (United States) , Alteryx, Inc. (United States), FICO (United States), Tableau Software (United States), Teradata Corporation (United States), TIBCO Software, Inc. (United States), Amazon Web Services (United States), Aveva (United Kingdom) , Accenture plc (Ireland) , ClearBrain (United States),
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Definition:
Predictive Analytics is basically sub category under advanced analytics, which is used to determine the outcomes for a future event, to assess risks and make decisions. Predictive analytics as a tool uses analytic and statistical techniques such as data mining, statistics, data modelling, machine learning, big data analytics and artificial intelligence. With the large amount of data collected, faster processing, innovation in analytical tools and easier to use softwares have accelerated the use of Predictive Analytics. Banking as a whole is facing certain operational and fraud inefficiencies which can be successfully overcome with the implementation of predictive analytics in the banking system to better predict the various outcomes to prevent any banking institutional or individual loss. Geographically, Europe and North America are leading in the use and application of Predictive Analytics in Banking. But growing adoption of digitised systems and strategic partnerships with western counterparts is promising a successful prospect for predictive analytics in Asia Pacific Region.
In 2020, OpenText Corporation, market leader in Enterprise Information Management Solutions announced signing of a global strategic partnership with Amazon Web Services (AWS). The Collaboration will enable OpenText to provide great offerings in business-critical information management solutions to its clients.
Market Trends:
Adoption of Machine Learning and Big Data Analytics by Banking Institutions
Market Drivers:
Increased Investments in Digitisation
Raised Demand from Clients for More Personalized Solutions
Years considered for this report:
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Current Scenario Analysis for Decision Framework
Key Strategic Developments in Predictive Analytics in Banking Market:
The research includes the key strategic activities such as Research & Development (R&D) initiatives, Merger & Acquisition (M&A) completed, agreements, new launches, collaborations, partnerships & (JV) Joint ventures, and regional growth of the key competitors operating in the market at global and regional scale to overcome current slowdown due to COVID-19.
Key Market Features in Global Predictive Analytics in Banking Market
The report highlights Predictive Analytics in Banking market features, including revenue size, weighted average regional price, capacity utilization rate, production rate, gross margins, consumption, import & export, demand & supply, cost bench-marking in Predictive Analytics in Banking market share and annualized growth rate (Y-o-Y) and Periodic CAGR.
Significant Facets concerning the Report:
– Predictive Analytics in Banking Market Summary
-Fiscal Effect on Economy
-Predictive Analytics in Banking Market Competition
-Predictive Analytics in Banking Market Analysis by Application
-Industrial Chain, Down-stream Buyers and Sourcing Strategy
-Distributors/Traders, Marketing Strategy Analysis
-Facets, Market Effect, Diagnosis
-Market Forecast
-The latest trends, product portfolio, demographics, geographical segmentation, and regulatory framework of the Predictive Analytics in Banking Market have also been included in the study.
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Extract from Table of Content:
Chapter 01 – Executive Summary
1.1 360 Degree Synopsis
1.2 Market value (US$ million).
Chapter 02 – Market Overview
Chapter 03 – Key Success Factors
3.1 Strategies adopted by key market participants and factors that have turned into success.
3.2 Additional viewpoint on global average pricing analysis benchmark, and consumer’s sentiments’ analysis.
Chapter 04 – Covid-19 Crisis Analysis on Predictive Analytics in Banking Market
Chapter 05 – Global Predictive Analytics in Banking Market – Pricing Analysis
Chapter 06 – Predictive Analytics in Banking Market Background
6.1 Macroeconomic factors affecting the Predictive Analytics in Banking market
6.2 Explore supply chain and value chain analysis.
6.3 In-depth information about the market dynamics and their consequences.
Chapter 07 — Predictive Analytics in Banking Market Segmentation
Chapter 08 – Key and Emerging Countries Analysis in Predictive Analytics in Banking Market
Chapter 09 – Predictive Analytics in Banking Market Structure Analysis
Chapter 10 – Predictive Analytics in Banking Market Competitive Analysis
10.1 Market Concentration Rate
10.2 Competition Scenario: BCG Matrix [Relative Market Share v/s Revenue Growth Rate]
10.3 Heat Map Analysis
10.4 Comparative Market Share Analysis by Players (2018-2019) Rank, [% Market Share, Market Revenue]
Chapter 11 – Assumptions and Acronyms
Chapter 12 – Research Methodology
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Key Questions Addressed in the Report
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