What Is Autonomous Identity?
ForgeRock’s Autonomous Identity is an AI-driven identity analytics solution that provides real-time and continuous enterprise-wide user access visibility, control, and remediation. By leveraging machine learning techniques, Autonomous Identity collects and analyzes identity data, such as accounts, roles, user activity, and entitlements, to identify security access and risk blind spots. The solution provides organizations with wider and deeper insight into the risks associated with user access by providing enterprise-wide contextual insights, high-risk user access awareness, and remediation recommendations. ForgeRock Autonomous Identity increases the business value of existing identity governance solutions, and infrastructure investments by layering on top of and integrating with them.
What is ForgeRock Autonomous Identity?
ForgeRock Autonomous Identity Benefits
Enterprise-Wide Risk Visibility
- Quickly understand organizational user access risk posture
- Contextual awareness of who has access to what and why
- Continuously identify high-risk access
Boost Operational Efficiency
- Automated AI-driven risk visibility, analysis, and reporting of user access
- Focus organizational effort on the areas that present the most risk
- Allows productivity shift so teams can focus on and address higher priority tasks
- Empower decision makers to allow or remove user access based on risk
- Take immediate action based on confidence scores, not static roles and entitlements
- Automate high-confidence access to eliminate unnecessary requests, reviews, certifications, and approvals
ForgeRock Autonomous Identity Customer Successes
- Multinational financial services organization
Automated entitlement assignments clean up to a major ERP application
- Major US healthcare service provider
Automated entitlement assignments clean up across the organization
- Global Consumer Goods Provider
Reduction of required roles across the organization
How ForgeRock Autonomous Identity Works
By leveraging AI and machine learning techniques, ForgeRock Autonomous Identity collects and analyzes identity data, such as accounts, roles, user activity, and entitlements, to identify security access and risk blind spots.
Autonomous Identity | Analytics Explainer
ForgeRock Autonomous Identity Features
AI-driven identity analytics that provides enterprise-wide visibility, control, and remediation for today’s modern enterprise.
Contextual, Enterprise-Wide Visibility
By leveraging AI-driven identity analytics, organizations can collect and analyze identity data (accounts, roles, user activity, entitlements, and more) from diverse identity, governance, and infrastructure solutions in order to provide enterprise-wide visibility of all identities and what they have access to across the entire organization. This modern approach provides security and risk professionals with contextual insights into low-, medium-, and high-risk user access at scale.
Access Rights Identification
Organizations can contextually examine all identity-related data and identify and recommend the right level of user access rights. This modern intelligence-based approach provides the ability to identify and apply appropriate birthright or leaver user access rights to accounts, applications, systems, roles, entitlements, and more. This process reduces the overall request volume by predicting appropriate user access at the right time to the right resources.
Transparent Artificial Intelligence
Unlike other “black box” identity analytics solutions, ForgeRock Autonomous Identity allows you to fully comprehend how and why risk confidence scores are determined. By visually presenting low-, medium-, and high-risk confidence scores together, security and risk professionals can contextually understand what key risk indicators were met. This AI-driven approach recommends risk-based identity and governance remediation updates based on enterprise-wide confidence scores.
Continuous Machine Learning
As new identity data is collected and old data is purged, the AI/machine learning model evolves and learns the dynamic changes within the organization. By leveraging predefined machine learning techniques and algorithms, organizations can quickly predict, recommend, and identify outliers. This intelligence-based approach allows security and risk professionals to automatically analyze and model high volumes of identity data in order to identify high-risk user access and unauthorized or unknown user access across the entire enterprise.
Remediation and Automation
With AI-driven identity analytics, organizational actors — application owners, supervisors, administrators, and others — can take corrective action based on recommended remediation, such as revoking stale user access rights and automatically removing them. By automatically approving and certifying high-confidence and low-risk access requests, enterprises can reduce operational burdens and accelerate certification campaigns across the entire organization.
Data Stream Processing
With intelligent data stream processing , organizations can leverage existing and diverse identity, governance, and infrastructure data sources to continuously collect and process high-velocity, high-volume data (identity, application, entitlement, assignment entities, and more) from across the enterprise. Combined with a highly scalable and distributed microservices architecture, enterprises can process and analyze tens of millions of data points quickly to predict and recommend user access rights and highlight potential risks. This intelligence-based approach enables security and risk professionals to accelerate their decision-making process.
ForgeRock Autonomous Identity: High-level Overview
AI-driven identity analytics for the modern enterprise
Maximize the Value of Your Identity Solution with AI-Driven Identity Analytics
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ForgeRock Autonomous Identity: AI-Driven Identity for the Modern Enterprise
Learn how Autonomous Identity answers the question "who has access to what and why"