Idskor

Idskor is a term used in digital identity and risk management to denote a computed score that represents the likelihood that a claimed identity is valid and not associated with fraud or abuse. There is no universal standard definition, and practices vary by sector and provider. In many implementations, idskor aggregates signals from user-supplied data, device and network attributes, and verification results to produce a numeric or categorical risk rating.

Common inputs include demographic information, contact details, device fingerprint, IP reputation, geolocation, and recent account activity, as well as results from identity document checks and external risk feeds. Some systems also incorporate behavioral analytics, historical fraud records, and relationship signals such as linkage to other accounts. Scoring methods range from rule-based rules to machine-learning models, often producing a score on a 0–100 scale or a set of risk bands like low, medium, and high.

Idskor is used to support processes such as onboarding and KYC, passwordless or multifactor authentication, and transaction monitoring. It can drive risk-based authentication decisions, limit or require additional verification for higher-risk actions, and inform continuous identity assurance during a customer relationship.

Limitations include data quality and bias, privacy and consent considerations, and the need to comply with data protection laws. Transparency about the meaning of the score and how it is used is important, as is regular auditing of models and data sources.