Identity Analytics Market Size, Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2019-2025
Report ID: GMI3381
Identity Analytics Market size will expect lucrative gains during the forecast period impelled by rising demand from enterprises to automate identity-related risks and issues such as access, provision or restriction. These solutions are significantly used in fraud detection, account management, identity & access management, and others. The increasing occurrences of data leak or identity frauds cause a heavy loss in revenue to many firms, forcing them to adopt identity analytics software and tools. Identity analytics combines the capabilities of advanced analytics and big data for the detection of identity-based risks in organizations. This will enhance the security of the company’s confidential data and help to manage its access.
Conventionally, SOD (Segregation of Duties) used to be done manually, which used to cost more; however, SMEs and large corporations are currently trying to make business processes more cost-effective. This problem is resolved due to the introduction of AI (Artificial Intelligence) and ML (Machine Learning) into identity analytics aiding businesses to do SOD and monitor them digitally. Identity analytics examines the existing roles and designations from the system and identifies inter and intra SOD risks. After this risk identification, the access is disabled and notified to the authorities.
In 2018, more than 1.4 million fraud cases were registered, which cost around USD 1.48 billion. This makes organizations keen to implement identity analytics software. Business can establish HPA (High Privileged Access) to certain users to keep sensitive data safe. The main problem large enterprises are facing is to manage a large amount of identity-related data, which needs to be kept safe and its maintenance to be cost-effective. Identity analytics software and tools are attracting SMEs as well as large corporations due to its cost-effective nature and the facility to access from anywhere.
Digitalization in various sectors has opened ways for cybercriminals to attempt more frauds. In the BFSI landscape, such incidences can cause heavy loss. To prevent such activities, banks are using intelligent systems and software to combat such crimes. This software uses machine learning, big data, and predictive analytics to catch identity-related frauds. Identity analytics is used for the examination of every transaction and identification of unusual transactions. Predictive analytics is used to analyze such unusual transactions. Machine learning and data mining techniques can also detect frauds.
In IT and Telecom, identity management solutions are required at a large scale due to huge volumes of data generated every day and managing such huge amounts of data is a hectic task. With a rise in the competition, operators are required to keep more data about customers such as device, usage, and location. Identity analytics helps to identify potential customers and offers them better services based on their needs, behavior, demographics, and devices. Customer retention is a big challenge in the telecom sector and identity analytics helps to identify the value loss of customers at an early stage, allowing operators to identify the factors that determine customers’ decisions and help to retain customers for a long period of time.
In North America, credit card frauds on new accounts went up to 24%, misusing someone’s information to open a new credit card account was reported more often than any other identity-related crime in 2018. Due to the widespread adoption of technology, the reports on frauds are registered more by youngsters than old people. These reasons together anticipate that North America will hold the largest market share in the identity analytics market. This region has accepted identity analytics tools in many sectors and the presence of many large players in the market makes it more favorable for the growth of this sector.
Asia Pacific’s identity analytics market is enormously growing due to the continuously increasing adoption of technology in the emerging IT sector. The countries including India are becoming the first preference for IT solutions outsourcing in the world as the required workforce is cost-effective in this region. Keeping track of such a big workforce is made easy by identity analytics, creating a suitable situation for the growth of the market in Asia Pacific.
The key players in the identity analytics market are Symantec, Oracle, Quantum Secure, Confluxsys, Threatmetrix, Nexis Gmbh, Okta, Hitachi Id Systems, Logrhythm, Idax Software, Centrify, Anomalix, Novetta, Gurucul, Verint Systems, Venafi, One Identity, Brainwave Grc, NetIQ, Sailpoint Technologies, Netowl, and Evidian. The companies are forming tie-ups with other companies to increase data processing capabilities. For instance, in May 2019, HDFC Ergo, a general insurance company, and IBM, a technology solution provider, jointly set up a data lab in India to run identity data-driven analytics on customer data and develop customized solutions and improve business’s profitability.
Identity Analytics Market, By Component Type, 2014-2025 (USD Million)
Identity Analytics Market, By Service Type, 2014-2025 (USD Million)
- Professional service
- Managed service
Identity Analytics Market, By Application Type, 2014-2025 (USD Million)
- Account Management
- Customer Management
- Fraud Detection
- GRC Management
- Identity and Access Management
Identity Analytics Market, By Deployment Type, 2014-2025 (USD Million)
Identity Analytics Market, By Organization Type, 2014-2025 (USD Million)
- Large enterprise
Identity Analytics Market, By Industry Verticals Type, 2014-2025 (USD Million)
- Government and defense
- IT and telecom
- Energy and utilities
The above information has been provided for the following regions and countries:
- North America
- Australia & New Zealand (ANZ)
- South Korea
- Latin America
- South Africa
- Saudi Arabia
- Verint Systems
- Quantum Secure
- Happiest minds
- Sailpoint technologies
- ID Analytics
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