Oracle
Among them are new features in
New features include "insight narratives" that can help identify anomalies, variances and biases based on pattern recognition. "Management reporting narratives" help finance professionals explain variances and trends impacting the business. "Predictive forecast explanations" generate contextual commentary to explain forecasts produced by predictive models and key factors driving the prediction. Program managers can generate executive summaries using details drawn from projects and sub-programs. Another new feature helps project managers create tailored project plans based on opportunity details, similar past projects and best practices.
Oracle has also made generative AI-related enhancements to
These new capacities directly integrate with a revamped
"Collecting, analyzing and contextualizing data can be a time-consuming, error-prone process," said T.K. Anand, executive vice president of analytics with Oracle. "With Oracle Fusion Data Intelligence, our customers can optimize this process by taking advantage of a comprehensive analytics offering that brings together data, ready-to-use analytics and prebuilt AI models in the right business context. The new AI capabilities we are adding can help customers further improve decisionmaking and rapidly turn insights into action."
Oracle nodded to security and private concerns by emphasizing no customer data is shared with large language model (LLM) providers or seen by other customers. In addition, an individual customer is the only entity allowed to use custom models trained on its data. To further protect sensitive information, role-based security is embedded directly into Oracle Fusion Applications workflows that only recommends content that end users are entitled to view.
In other news, Oracle also
Users can use direct connections and file-based uploads to consolidate disparate data sources to help meet International Financial Reporting Standards and Global Reporting Initiative standards. For example, organizations can align energy use, fleet mileage, procurement data and other applicable data sources to meet the requirements of the relevant frameworks and standards. In addition, built-in process management tools help capture all data.
Embedded scenario modeling capabilities let organizations run a number of scenarios simultaneously to determine the best path forward. Built-in pattern recognition capabilities provide automated alerts about anomalies and variances, while self-service capabilities for filtering, sorting and visualization enable users to drill into the data via dashboards and automated analysis. Predictive planning features help users create and validate forecasts and predict future performance. Narrative reporting capabilities align data with relevant reporting standards and produce reports with contextual details that can be shared with stakeholders.
"Many organizations are beginning to treat sustainability reporting requirements with the same rigor, governance and technical expertise as financial reporting," said Hari Sankar, group vice president of product management at Oracle. "With Oracle Cloud EPM for Sustainability, our customers can leverage a trusted solution that embeds AI and other advanced technologies to help improve efficiency, deliver insights, promote compliance and effectively manage their progress on sustainability initiatives."
