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There is a necessity for organisations to progress towards a comprehensive IGA solution. In many organisations with an established IGA, the necessity for modernisation represents a significant challenge. The implementation of IGA solutions encounters three main areas of challenge, which tend to delay progress and result in project stalling. The first area of difficulty is application onboarding, where organisations encounter challenges in connecting all the target systems they wish to integrate within the IGA environment. The majority of IGA projects are significantly longer than anticipated in addressing this challenge. Another aspect is the complexity of access reviews/recertification. Entitlements that are reviewed can be difficult to understand, with a tendency towards authorizing rather than thorough and detailed reviews. The potential of AI/ML to improve this is an area of interest.
Many IGA implementations are customized to a state where they are complex to manage. An underlying problem is that majority of the IGA solutions are deployed without a comprehensive set of out-of-the-box processes. This is mainly because the customer has added a lot of complex customizations instead of staying in the standard processes. Finally the other challenge is customers are hesitant to move to IDaaS. The trend is slowly shifting as more and more customers are shifting from on-premises to hybrid of fully IDaaS deployments.
The various challenges that organizations have to contend with when managing identities, users, and their entitlements are:
Regulatory frameworks are updating on a regular basis. Organizations have to comply with these frameworks or face penalties and hefty fines. With the help of a comprehensive IGA solution, organizations can leverage the Identity and Access Governance (IAG) aspect for better visibility of identity administration and access entitlements across its IT infrastructure. IAG can provide simple reporting and dashboarding to more advanced capabilities that can include AI and/or machine learning techniques enabling pattern recognition to deliver valuable intelligence for process optimization, role design, automated reviews, and anomaly detection.