Predictive Analytics in Banking Market Expected to Grow $5.43 Billion By 2026 at 20.80% CAGR | Business Outlook

Predictive Analytics in Banking Market

Predictive Analytics in Banking Market

Significant increase in fraudulent activities such as accounting fraud, money laundering and payment card fraud drives the global market growth”

— Vivek Karmalkar

PORTLAND, OREGON, UNITED STATES, September 17, 2020 /EINPresswire.com/ — Allied Market Research published a new report, titled, "Predictive Analytics in Banking Market 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): Global Opportunity Analysis and Industry Forecast, 2020-2027".

The report has offered an all-inclusive analysis of the global predictive analytics in banking market taking into consideration all the crucial aspects like growth factors, constraints, market developments, top investment pockets, future prospects, and trends. At the start, the report lays emphasis on the key trends and opportunities that may emerge in the near future and positively impact the overall industry growth.

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Key drivers that are propelling the growth of the market included in the report. Additionally, challenges and restraining factors that are likely to curb the growth of the market are put forth by the analysts to prepare the manufacturers for future challenges in advance.

The report presents in-depth insights into each of the leading predictive analytics in banking end user verticals along with annual forecasts to 2027. The report provides revenue forecast with sales, and sales growth rate of the global predictive analytics in banking market. The forecasts are also provided with respect to the product, application, and regional segments of the market. The forecasts are issued to understand the future outlook and prospects of the industry.

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The market is evaluated based on its regional penetration, explaining the performance of the market in each regional market covering provinces such as North America (United States, Canada and Mexico), Europe (Germany, France, UK, Russia and Italy), Asia-Pacific (China, Japan, Korea, India and Southeast Asia), South America (Brazil, Argentina, Colombia), Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa).

Top 10 leading companies in the global predictive analytics in banking market are analyzed in the report along with their business overview, operations, financial analysis, SWOT profile and predictive analytics in banking products and services. The key players operating in the global predictive analytics in banking industry include 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.

Latest news and industry developments in terms of market expansions, acquisitions, growth strategies, joint ventures and collaborations, product launches, market expansions etc. are included in the report.

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Key Benefits:
1. The report provides a qualitative and quantitative analysis of the current predictive analytics in banking market trends, forecasts, and market size from 2020 to 2027 to determine the prevailing opportunities.
2. Porter’s Five Forces analysis highlights the potency of buyers and suppliers to enable stakeholders to make strategic business decisions and determine the level of competition in the industry.
3. Top impacting factors & major investment pockets are highlighted in the research.
4. The major countries in each region are analyzed and their revenue contribution is mentioned.
5. The market report also provides an understanding of the current position of the market players active in the predictive analytics in banking industry.

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Highlights of the Report:
1. Competitive landscape of the predictive analytics in banking market.
2. Revenue generated by each segment of the predictive analytics in banking market by 2027.
3. Factors expected to drive and create new opportunities in the predictive analytics in banking industry.
4. Strategies to gain sustainable growth of the market.
5. Region that would create lucrative business opportunities during the forecast period.
6. Top impacting factors of the predictive analytics in banking market.

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Predictive Analytics in Banking Market Key Segments:
By Component:
1. Solution
2. Service

By Deployment Model:
1. On-Premise
2. Cloud

By Organization Size:
1. Large Enterprises
2. SME’s

By Application:
1. Fraud Detection & Prevention
2. Customer Management
3. Sales & Marketing
4. Workforce Management
5. Others

By Region:
1. North America
2. Europe
3. Asia-Pacific
4. LAMEA

CHAPTERS DISCUSSED IN THE REPORT: [Total 223 Pages]
Chapter 1: Introduction
Chapter 2: Executive Summary
Chapter 3: Market Landscape
Chapter 4: Predictive Analytics in Banking Market By Component
Chapter 5: Predictive Analytics in Banking Market By Deployment Model
Chapter 6: Predictive Analytics in Banking Market By Organization Size
Chapter 7: Predictive Analytics in Banking Market By Application
Chapter 8: Predictive Analytics in Banking Market By Region
Chapter 9: Company Profiles

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About Us:
Allied Market Research (AMR) is a full-service market research and business consulting wing of Allied Analytics LLP based in Portland, Oregon. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of “Market Research Reports” and “Business Intelligence Solutions.” AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.

We are in professional corporate relations with various companies and this helps us in digging out market data that helps us generate accurate research data tables and confirms utmost accuracy in our market forecasting. Each and every data presented in the reports published by us is extracted through primary interviews with top officials from leading companies of domain concerned. Our secondary data procurement methodology includes deep online and offline research and discussion with knowledgeable professionals and analysts in the industry.

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Source: EIN Presswire