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9th October 2018
Oracle unveils first AI-driven security and risk management solution
To help protect customers from ever-increasing fraud and security threats, Oracle has unveiled the first artificial intelligence (AI)-driven security and risk management solution.
Designed specifically for Oracle Enterprise Resource Planning (ERP) Cloud, Oracle Risk Management Cloud’s new Advanced Access Controls enable organisations to continuously monitor for segregation of duties (SOD), financial compliance (SOX), privacy risks, proprietary information and payment risks.
The new controls embed self-learning, AI techniques to constantly examine all users, roles and privileges against a library of active security rules. The offering includes more than 100 best practices (configurable rules) across general ledger, payables, receivables and fixed assets.
“As the pace of business accelerates, organisations can no longer rely on time-consuming manual processes, which leave them vulnerable to fraud and human error,” said Laeeq Ahmed, managing director at KPMG. “With adaptive capabilities and AI, products such as Oracle Risk Management Cloud can help organisations manage access controls and monitor activity at scale to protect valuable data and reduce exposure to risk.”
Key benefits of AI-driven Security and Risk Management include:
• Continuous protection: Constant monitoring of user and application activity
• Instant best practices: More than 100 proven ERP security rules
• Self-learning: Embedded AI and self-learning for precise results
• Augmented incident response: Ensures that issues are directed to analysts for tracking, investigation and closure
The pre-packaged audit-approved security rules automate access analysis during the role design phase to significantly accelerate ERP implementations. In addition, the intuitive workbench, visualisation and simulation features within Advanced Access Controls make it easy to add new rules and further optimise user access. Once live, the solution continuously monitors and automatically routes incidents to security analysts.
To help customers analyse complex, recursive and dynamic security data across all users, roles and privileges, Advanced Access Controls uses graph-based analysis and self-learning algorithms. This enables organisations to accurately and reliably review and visualize the entire path by which any user is able to access and execute sensitive functions.
