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, 2019-2026
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 key players profiled in the predictive analytics in bankingmarket analysis are 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. These players have adopted various strategies to increase their market penetration and strengthen their position in the industry.
Key Benefits for Stakeholders
The study provides an in-depth analysis of the global predictive analytics in banking market forecast along with the current & future trends to elucidate the imminent investment pockets.
Information about key drivers, restraints, and opportunities and their impact analysis on the global predictive analytics in banking market size is provided in the report.
Porter’s five forces analysis illustrates the potency of the buyers and suppliers operating in the industry.
The quantitative analysis of the market for the period 2019–2026 is provided to determine the market potential.
Key Market Segments
By Deployment Model
By Organization Size
Fraud Detection & Prevention
Sales & Marketing
Rest of Europe
Rest of Asia-Pacific
KEY MARKET PLAYERS
Fair Isaac Corporation
SAS Institute, Inc.
Tableau Software, Inc.
TIBCO Software, Inc.
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