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面向企业绩效管理的 AI 配置云探索 [SHO3129].pdf

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1、Cloud Adventure for Configuring AI in Enterprise Performance Management Colton BretschneiderPrincipal EPM Solution EngineerNorth America ApplicationsOctober 14,2025Agenda2Copyright 2025,Oracle and/or its affiliates|Confidential:Internal/Restricted/Highly Restricted123AI In EPMHands On SessionQ&A3Cop

2、yright 2025,Oracle and/or its affiliates|Confidential:Internal/Restricted/Highly RestrictedIPM Insights To automate analysis,detect issues,and find opportunities.Narrative ReportingTo respond to changing circumstances by generating narrative and recommendations in financial and management reports.Jo

3、urnal Entry,Reconciliation NotesTo automatically add explanations and commentary to a journal entry for the approver to approve or reject based on risk threshold.Financial Data ExplanationsTo provide financial-focused rationale via GenAI with context in a dashboard.Intelligent AutomationAutomate ana

4、lysis and content generation 4Copyright 2025,Oracle and/or its affiliates|Confidential:Internal/Restricted/Highly RestrictedPredictive InsightsAI empowers finance to predict outcomesPredictive PlanningTo increase forecast accuracy by using ML to refine your forecasts and recommend the most likely ou

5、tcomes.Auto-predictive PlanningTo automatically seed a comparison forecast based on past performance to improve forecast accuracy.Predictive Cash ForecastingOptimize your cash flow by using predictive algorithms to accurately forecast daily or weekly cash forecasts.AutoML for Custom ModelsTo leverag

6、e your investment in ML by importing your models into EPM in the context of finance.5Copyright 2025,Oracle and/or its affiliates|Confidential:Internal/Restricted/Highly RestrictedConnected ActionsAligned decisions for optimal outcomePredictive Cash ForecastingOptimize your cash flow by blurring the

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根据《Cloud Adventure for Configuring AI in Enterprise Performance Management》的内容,以下是全文关键点的概括: 1. **AI在EPM中的应用**: - 自动化分析、检测问题和发现机会。 - 生成财务和管理报告中的叙述和推荐。 - 自动添加解释和评论到日记账目。 2. **智能自动化**: - 自动分析和内容生成。 - 预测性洞察,通过机器学习提高预测准确性。 - 自动预测性规划,基于历史性能自动生成比较预测。 3. **连接行动**: - 通过模糊ERP和其他下游系统之间的界限来优化现金流。 - 连接规划,提供企业视角的所有计划,AI引导战略伙伴。 4. **数据分析挑战**: - 数据坐标数量庞大,难以手动审查。 - 数据内部结构复杂,难以视觉识别异常。 5. **洞察类型**: - 预测偏差和偏差洞察。 - 预测洞察。 - 异常洞察。 6. **数据量示例**: - 公司有100个账户,200个产品,100个实体,50个地点,产生约1亿个潜在坐标。 7. **反馈**: - 鼓励通过QR码或移动应用分享对本次会议的看法。
"AI如何加速企业绩效管理?" "智能自动化在财务预测中的应用?" "如何通过AI优化现金流?"
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