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(Wireless-NewsWire.Com, February 19, 2020 ) According to research report "Predictive Analytics Market by Solutions (Financial Analytics, Risk Analytics, Marketing Analytics, Sales Analytics, Web & Social Media Analytics, Network Analytics), Services, Deployment, organization size and Vertical - Global Forecast to 2022", The predictive analytics market size is expected to grow from USD 4.6 billion in 2017 to USD 12.4 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 22.1% during the forecast period. The key factors driving increasing adoption of predictive analytics for forecasting future market trends and growing adoption of big data and other related technologies.
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82 - Tables
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163 - Pages
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The BFSI vertical is expected to account for the largest market size during the forecast period
Banks and other financial institutions gather large volumes of data every day. The BFSI vertical is undergoing large-scale transformations as banks, credit card companies, investment funds, insurance companies, and government-funded enterprises are facing continuous challenges in offering value added services for customers and launching new products. The BFSI vertical has to handle challenges such as rising costs because of numerous regulatory bodies including the US Office of the Comptroller of the Currency (OCC), Federal Reserve Board (FRB), Consumer Financial Protection Bureau (CFPB), European Central Bank, and Reserve Bank of Australia. They also need to cascade complex control requirements and handle costs effectively, across the supply and services networks. Organizations in the banking, financial services, and insurance vertical, are running the risk of default in payment or repayment, and volatility across the trading market. Risk Analytics, financial analytics, and customer analytics are some of the major predictive analytics solution that are utilized by companies operating in the BFSI vertical.
Additionally, banking and financial services organizations have to face frauds at different levels which vary from purchases made by stolen credit card, money laundering, first-party fraud, and insurance claims. Predictive analytics also complements an organization’s current transaction monitoring systems, by tracking frauds before the occurrence.
Enhanced business productivity and timely delivery of products and services are the important aspects for the success of any organization, as large organizations are obliged to regulations and hence to account for a larger market size
Large enterprises accumulate huge chunks of data which can be attributed to the wide spread client base. In large enterprises, data plays a major role in evaluating the overall performance of the organization and good quality data has always been a key enabler for the organizations to focus on enhancing their core competencies which ultimately lead them to have a competitive edge over their competitors. Predictive analytics caries extreme potential for large organizations as poor performances may cast them with the loss of clients, ultimately affecting their brand name. Moreover, large organizations are obligated toward adhering to stringent compliance regulations such as GDPR and other banking related regulations such as Basel III and Dodd–Frank Wall Street Reform and Consumer Protection Act; these regulations are driving the adoption of predictive analytics among the large enterprises.
Predictive analytics solutions help organizations in improving their decision-making process
Organizations are often surrounded by risks that might affect its numerous factors in addition to the primary operational area; these risks comprise reputational risk, environmental risk, third-party risk, and economic risk. Predictive analytics provides companies with risk model-based vendor performance management and analysis application which is based on external data and ongoing performance of the vendors for efficiently evaluating and monitoring vendor performance to mitigate future risk of vendor failure. Predictive analytics offers users with spend analysis to identify anomalies in their direct and indirect spend through machine data analytics. This application uses analytical models on spend data to find anomalies that indicate potential savings, such as contract noncompliance, rate mismatches, duplicate invoices, and incorrect demand specifications.
Indispensable need to predict future business possibilities are leading to the rising adoption of big data-related technologies in North America
The adoption of predictive analytics solutions is expected to be the highest in North America, as compared to the other regions. This is mainly because of the presence of various developed economies, such as Canada and the US, and due to the focus on innovations obtained from R&D and technology. North America, which is the hub of data generation in large quantities, is the largest market for predictive analytics solutions, with a share of 41.1% in the global market. The high penetration of predictive analytics in multiple industry verticals, such as manufacturing, healthcare, transportation, and logistics, is driving the growth of this market in this region. The North American region has been extremely open toward the adoption of any new and innovative technologies, and is expected to provide market growth opportunities to predictive analytics vendors, as it is expected to witness the exponential growth of IT device-based generated data, and stringent laws and policies for safeguarding the data. The indispensable need to predict future business scenarios and the rising adoption of big data-related technologies are said to have historically driven the overall growth of the predictive analytics market in this region. Factors, such as the emergence of AI technology, machine learning, and the rapid adoption of cloud-based solutions, and the increasing number of business applications are said to be further fueling the growth of the predictive analytics market in North America. Consequently, the predictive analytics components are said to be showing strong positive trends in the region, as several companies and industries are adopting predictive analytics software and services at various levels as a part of their strategy, to strive in the market and increase the efficiency of IoT data for enhancing their overall productivity. Many predictive analytics giants, such as International Business Machines Corporation, Oracle Corporation, SAS Institute, Inc., and RapidMiner, Inc., are offering predictive analytics software that includes sensor data analytics, IoT gateway analytics, and network management.
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North America has been the most promising region across various industry verticals, such as the BFSI, manufacturing, retail and eCommerce, healthcare and life sciences, and telecommunication and IT. The government sector has also joined the race to become a technologically-advanced industry vertical, serving a large customer base. Some of the biggest retail giants are also located in this region. In terms of adoption, North America is contributing significantly to the market and is expected to grow further too. The US is said to have adopted predictive analytics to a great extent.
The predictive analytics ecosystem comprises vendors, such as Alteryx, Inc. (US), AgilOne (US), Angoss Software Corporation (Canada), Domino Data Lab (US), Dataiku (US), Exago, Inc. (US), Fair Isaac Corporation (FICO) (US), GoodData Corporation (US), International Business Machines (IBM) Corporation (US), Information Builders (US), Kognitio Ltd. (UK), KNIME.com AG (Switzerland), MicroStrategy, Inc. (US), Microsoft Corporation (US), NTT DATA Corporation (Japan), Oracle Corporation (US), Predixion Software (US), RapidMiner (US), QlikTech International (US), Sisense, Inc. (US), SAP SE (Germany), SAS Institute, Inc. (US), Tableau Software, Inc. (US), TIBCO Software, Inc. (US), and Teradata Corporation (US).
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Mr. Sanjay Gupta
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