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Top 9 Risk-Based Authentication Software SaaS Companies in May 2026

As of May 2026, there are 9 SaaS companies in Risk-Based Authentication Software. They have combined revenues of $63.9M and employ 642 people. They have raised $2.3M and serve 290K customers combined.

Risk-Based Authentication Software is a security approach designed to evaluate the risk associated with user login attempts or transactions in real-time. By analyzing various factors such as the user's location, the device being used, and historical behavior, the software dynamically adjusts the authentication requirements. This adaptive mechanism helps organizations enhance security while minimizing friction for legitimate users. Primary use cases for Risk-Based Authentication include protecting sensitive data in financial services, securing remote workforce access, and controlling entry into SaaS applications. The software typically features real-time risk assessment algorithms, multi-factor authentication options, and detailed analytics dashboards. Typical buyers include IT security professionals, compliance officers, and risk management teams seeking to bolster their identity and access management strategies.

Companies
9
Revenue
$63.9M
Funding
$2.3M
Employees
642

Filters

Sorting: Highest -> Lowest

Filters

Top Risk-Based Authentication Software Companies

Showing 10 of 2 companies ranked by annual revenue.

1
Keyri

San Francisco, California, United States

Secure fraud prevention and authentication platform for developers

Revenue
$1M
Customers
-
Year founded
2021
Funding
-
Team size
4
Growth
-
2
GPSFlex Corporation

Americana, Sao Paulo, Brazil

Our Mission is to integrate Facial and Speech Recognition Solutions along with technologies, such as, OCR and QRCODE to assist Virtual Banks, CryptoCurrency Brokers and Virtual Stores in the fight against Fraud, using an effective Validation and Identification Solution.

Revenue
$184.6K
Customers
-
Year founded
2008
Funding
-
Team size
2
Growth
26.5%

Inclusion Criteria

- The software must analyze multiple contextual signals to assess login risk levels. - It should adapt authentication requirements based on the assessed risk. - Must support integration with various identity management systems. - It should offer reporting and analytics features for monitoring login attempts. - Not just a static authentication tool; must provide real-time assessments and adjustments.