OneSpan Risk Analytics
Fraud detection software
Web security software
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- Banking and insurance
- Healthcare and life sciences
- Public sector and nonprofit organizations
What is OneSpan Risk Analytics
OneSpan Risk Analytics is a risk-based authentication and fraud analytics product used by financial institutions to assess the risk of digital banking sessions and transactions. It combines device and session intelligence with behavioral signals to support step-up authentication, transaction verification, and fraud investigation workflows. The product is typically deployed alongside digital banking channels and authentication methods to reduce account takeover and unauthorized payments. It is positioned for organizations that need fraud scoring and policy-driven responses integrated into existing identity and authentication stacks.
Risk-based authentication workflows
The product supports risk scoring that can trigger step-up actions such as additional authentication or transaction verification. This fits common banking use cases like login risk assessment, payee changes, and high-risk payments. It is designed to work as part of an end-to-end authentication flow rather than only post-transaction monitoring. That can reduce friction for low-risk sessions while focusing controls on anomalous activity.
Device and session intelligence
OneSpan Risk Analytics uses device and session attributes to help identify suspicious access patterns and potential account takeover attempts. These signals can complement credential-based controls by adding context about the environment and interaction. The approach is useful when fraudsters reuse credentials across devices or automate access. It also supports investigation by providing session-level telemetry for flagged events.
Fits regulated banking environments
OneSpan’s portfolio is oriented toward financial services security and authentication, which aligns with regulated operational requirements. Risk analytics can be integrated with transaction signing or verification methods used in banking. This can help institutions implement layered controls across login and transaction stages. The product focus is generally better aligned to banking risk scenarios than tools built primarily for e-commerce checkout fraud.
Less suited to e-commerce
The product’s core design targets digital banking and payment authorization rather than merchant checkout and chargeback workflows. Organizations looking for order-level fraud decisions, fulfillment guarantees, or dispute management may find gaps. Adapting it to retail/e-commerce processes can require additional tooling and integration work. Fit is strongest where authentication and transaction verification are central.
Integration and tuning effort
Deployments typically require integration into web/mobile channels and alignment with existing IAM, authentication, and fraud operations processes. Risk policies and thresholds often need tuning to balance false positives and user friction. This can extend implementation timelines compared with more self-contained, plug-in style tools. Ongoing monitoring is usually needed as fraud patterns change.
Limited public model transparency
As with many fraud analytics products, detailed information about scoring models and feature weighting is not always fully exposed to customers. This can make it harder to independently validate why a session or transaction is scored as high risk. Some teams may need additional reporting or SIEM integration to meet internal audit expectations. The level of explainability can vary by deployment and configuration.
Seller details
OneSpan Inc.
Boston, MA, USA
1991
Public
https://www.onespan.com/
https://x.com/OneSpan
https://www.linkedin.com/company/onespan/
