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2024 Identity and Security Trends
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Over-hyped solutions have some identity professionals wary about truly ‘intelligent’ identity management. At Saviynt, we let our tech do the talking.
Using analytics, artificial intelligence (AI), and machine learning (ML) to improve enterprise identity security is critical to outpace cybersecurity threats. The hangup for many are the buzzwords – leaders want to see real-world use cases where human and machine intelligence meaningfully converge.
As discussed in our Identity and Security Trends and Predictions report, we expect more in-depth use of analytics and AI/ML technologies to improve risk awareness and decision making for identity-related business processes. While loftier benefits – like totally human-less access decisions – are some years away, others are accessible now.
Moving Beyond The Hype: How Saviynt Uses AI/ML and Analytics to Transform Enterprise Identity
Innovations are irrelevant if they don’t produce the outcomes enterprises expect. Identity platforms often promise – but don’t deliver – lower risk profiles, improved decision making, reduced compliance violations, and hardened security postures built around Zero Trust.
Our team is shifting the narrative and transforming IGA and PAM with robust AI/ML and analytics built into our Enterprise Identity Cloud. Here are some breakthroughs we’re delivering now.
As organizations shift to the cloud, agile delivery models or ineffective Identity Governance may lead to excessive access. Sharing the ‘keys to the kingdom’ can be disastrous; few applications are designed with least-privilege principles and advanced analytics are required to reduce emerging risks.
Saviynt uses data-rich analytics to simplify identity intelligence. Armed with insights, identity analysts and administrators can identify and mitigate risks accurately and rapidly.
For example, organizations can streamline IAM Policy creation and create a consistent definition of identity and access based on user attributes. Analytics-driven attribute-based access controls (ABAC) and role-based access controls (RBAC) help enterprises better manage least privilege access. With focused analytics, enterprises can narrow definitions of ‘access’, and control what end-users can do – while reducing Segregation of Duties violations.
Deloitte recognizes the use of behavioral analytics to create baseline markers of normal user behaviors. Additionally, built-in natural language processing (NLP) can help easily monitor for abnormal occurrences – and learn (and infer) from behavior patterns. This supports faster, frictionless identity-related decision making.
During our recent CONVERGE 20 Roadshow, Michael Allred, Director of Identity and Access Management at Intermountain Healthcare shared how his team benefits from analytics (and making smarter, more secure decisions) at scale: “Reviewing user-behavior and auditing access for 50,000 users is simply not sustainable.”
With Saviynt’s actionable analytics, enterprises can visualize data and risks, and promptly respond. These include real-time insights into user risk changes due to excessive access or the presence of activities outside a role/user’s typical behavior. Insights lead to smarter controls, too, including creating and managing access policies & roles.
Intelligence without actionability isn’t useful, which is why Saviynt integrates with (and ingests data from) SIEM and UEBA solutions. Most companies use multiple tools to evaluate their security postures, which requires managing large quantities of logs, alerts, and notifications. Our platform intelligently curates these – adding visibility and risk scoring to support anomalous activity detection and incident responses.
Central to ‘intelligent identity’ is smarter work underpinned by AI & ML. One of the most useful applications of these technologies is risk modeling and decision making.
For example, we recently announced Assisted AI, which bridges human and machine intelligence interactions to create better governance strategies. Identity-centric security starts with knowing who accesses what resources, why they need access, and how they ultimately use that access.
As access approvals and denials occur, Saviynt gathers data from each request made. Our platform curates and learns from the data; eventually, the AI precisely understands appropriate responses to common request scenarios. This alleviates the burden of repetitive requests and enables approvers to focus on unusual or high-risk requests.
Our automation also reduces costs associated with birthright provisioning, continuous monitoring, and governance. We’re excited about how automated dynamic provisioning leads companies toward zero standing privilege and just-in-time access principles. Along the way, we’re creating linkages between all identifiers, cataloging and discovering assets, and making time-series observations of these relationships to build recommendations and personalization.
Organizations utilizing Saviynt have seen up to 36% of SoD violations prevented during the access request process. This reduction translates to managers saving time when reviewing excess access. Historical data, platform analytics, and peer benchmarks are feeding our AI to help drive actionable authorization decisions, as well.
Our AI & ML recommendation engine supports other insights, including business rule and policy suggestions, and recommendations to improve role quality, ownership, and user membership. Saviynt’s work to build a fully automated, self-learning platform is part of our mission to transform IGA and create a truly “prescriptive” identity experience.
Cynicism around AI/ML and advanced analytics in the identity market is often warranted. At Saviynt, we don’t just market a smarter platform — we deliver one.
Risk reduction, security improvements, centralized access control, increased productivity, cost reduction, and regulatory compliance assurance are direct results of infusing intelligent functionality into our Enterprise Identity Cloud platform.
We’re proud of our performance to-date. But the use cases above – and recent breakthroughs like Identity BOT (built-in RPA engine to automate provisioning) and Identity Exploration (helping users explore trends and determine patterns in identity data) – are just the beginning.
Interested in maximizing cloud-based identity governance with performant AI/ML and analytics tools? We’re here to help.
10 / 30 / 2024
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