Ability to Create and Manage External Users

Service Administrators can now use the Manage Users tab under Access Control to create, edit, and delete external users (users who are not provisioned to login to the environment, but are created only in Account Reconciliation, are called external users).

Additions to the Manage Users tab include the following:

• Filters to search using Role, Last Login, Preparer, Status, and Reviewer
• Customize Columns icon to select the columns displayed on the tab
• Refresh button to display the latest updates changes made to user details

Business Benefit: 

This feature enhances the alert capabilities since external users can now be assigned as Notification Assignees or Viewers, which allows them to receive email notifications related to alerts, greatly streamlining the exception management process.

Thank you!

Assistance in Oracle ARCS for Predicting Matches with AI

From Apr-2026 monthly patches, Oracle have introduced the AI assistance for predicting Matches using AI for both Reconciliation compliance and Transaction Matching module. Below are the details -

Transaction Matching Assistance for Predicting Matches with AI

Transaction Matching Assistance uses Artificial Intelligence (AI) to predict matches in Transaction Matching by using a prediction model that is trained using your historical manual match data. Users have the option to review the predicted matches and confirm or discard them.

A confidence score is provided for each predicted match. Higher confidence scores indicate that the predicted matches are more reliable. The confidence score helps users prioritize and make informed decisions about manual matches.

Business Benefit:

 In addition to an enhanced user experience, this feature provides the following benefits:

Reduces time and effort spent on manual matching

    A majority of the loaded transactions are matched using Auto Match, with only the exceptions needing to be manually matched. Predicting potential matches for unmatched transactions further reduces time and effort spent on manual matching, thereby speeding up the period-end close process.

Improves accuracy and enhances the overall efficiency of manual matching

    Data-driven predictions that are based on proven patterns leads to more accurate and consistent predicted matches

Steps to enable and configure

The Enable Predictive AI configuration setting must be selected to use Transaction Matching Assistance.

Reconciliation Assignment Assistance for Predicting Attribute Values with AI

Reconciliation Assignment Assistance uses Artificial Intelligence (AI) to predict the value of a specified attribute by using Machine Learning algorithms that are trained on your historical data. To use Reconciliation Assignment Assistance, Service Administrators must create a predicted attribute and train it using the existing data. This training creates a model that can then be used, any number of times, to predict the value of the specified attribute. The model can be retrained periodically to reflect changes in data over time, thereby ensuring its effectiveness.

For each predicted value, an attribute is created for confidence percentage. A higher confidence percentage indicates that the predicted value is likely more accurate.

Business Benefit: 

In addition to automating the process of setting values for profile attributes, this feature provides the following benefits:

1. 1.Reduces the manual effort involved in creating profile attributes, thereby enabling you to focus in higher-value tasks
2. 
   
3. 2.Streamlines and speeds up the period-end close
4. 
   
5. 3. Enhances consistency and accuracy by minimizing human errors and leveraging historical data-driven insights

Steps to enable and configure

The Enable Predictive AI configuration setting must be selected to use Reconciliation Assignment Assistance.

Thank you!

Cloud-Native EPM Automation: Why It's Time to Migrate to Oracle EPM Pipelines

For years, Oracle Cloud EPM administrators looking to build robust, hands-free automation workflows had to walk a narrow, complex path. You either wrestled with the code-free but severely restrictive Batch functionality within Data Management, or you stood up standalone servers to orchestrate complex external scripts via EPM Automate. But the architecture of Enterprise Planning and Budgeting Cloud Service (EPBCS) has officially shifted. With Oracle systematically decommissioning legacy Data Management batches, a modern framework has taken center stage: The Pipeline. Far from a simple cosmetic makeover, the Pipeline feature completely replaces cumbersome legacy processes with a visual, centralized, and cloud-native orchestration powerhouse located right inside the Data Integration dashboard.

The Death of Custom Scripting and Legacy Batches

Historically, chain-linking EPM actions required significant operational overhead. If you wanted to load data, map it, run a series of business rules, clear a partition, and send a completion email, you had to write shell or PowerShell scripts using EPM Automate. This required an on-premise or cloud infrastructure host, security certificates, credential management, and constant maintenance. The new Pipeline feature natively swallows these infrastructure requirements. It allows administrators to build end-to-end, multi-stage, multi-module execution paths without writing a single line of external code. Because it runs natively inside Oracle EPM Cloud, there are no third-party servers to maintain and no external batch utilities to configure. Architectural Shift Notice: Oracle's strategic direction is clear. Legacy Data Management batches are being deprecated. Transitioning to Pipelines isn't just about modernizing your stack—it's a critical path item to ensure your EPM ecosystem remains fully supported and operational. 

Anatomy of an EPM Pipeline

Pipelines bring a highly structured hierarchy to business process automation. They are built on two core concepts: Stages and Jobs. Stages (Serial vs. Parallel): A pipeline is broken into sequential stages. However, inside each stage, you can configure jobs to execute either sequentially (Serial) or concurrently (Parallel). Running jobs in parallel allows you to process up to 25 data integrations or processes simultaneously, drastically slashing nightly batch windows. Supported Job Types: Pipelines are fully integrated across the platform. A single pipeline can call Data Integrations, execute Open Batches, trigger complex Business Rules or Rulesets, run Data Maps, clear data slices, import/export metadata, and even dynamically update Substitution Variables. 

What’s New? Recent High-Impact Pipeline Releases 

Oracle has aggressively added enterprise-grade features to the Pipeline framework over recent updates. If you haven't reviewed Pipelines lately, here are the major game-changing enhancements you need to know: 

1. Seamless Cross-Instance Orchestration Modern enterprise architecture rarely relies on just one EPM environment. You might handle planning in EPBCS, but handle financial consolidation in FCCS and account reconciliation in ARCS. Pipelines can now cross instance boundaries. You can log into your primary planning instance and build a pipeline that triggers data exports locally, pushes them to FCCS, runs consolidation rules there, and triggers balance updates in ARCS—all managed from a single pane of glass. 

2. Direct SFTP Integration Eliminating the need for intermediate data-staging servers, Oracle introduced native SFTP job types. Pipelines can now securely pull source files directly from an external SFTP server or push exports out to external environments. This effectively replaces traditional file-transfer agents for basic automated integrations. 

3. Proxy User Execution for Non-Admins Historically, complex system automations required full Service Administrator privileges to execute. The new Proxy User credential capability changes the game. Administrators can assign a proxy credential to a pipeline, enabling business power users or regional finance teams to trigger the workflow themselves. The pipeline executes with administrative authority behind the scenes, without elevating the actual user's system privileges. 

4. Enterprise-Grade User Interface Refinements As pipelines have grown to encompass hundreds of sequential and parallel steps, managing them could become unwieldy. Oracle resolved this by introducing a compact Table View, allowing administrators to filter, audit, and modify massive workflows quickly. Additionally, the canvas has moved to a Manual Save model, ensuring that complex layout changes are only committed when you choose, preventing accidental runtime disruptions. 

Advanced Error Handling and Scheduling What happens when things go wrong? Legacy automation often failed silently or required custom error-parsing scripts. The Pipeline feature handles errors natively: 

• Conditional Logic: Configure steps to explicitly "Abort on Failure" or gracefully "Continue on Failure" depending on the criticality of the job. 
• Native Notifications: Automatically emails stakeholders upon pipeline success, warning, or failure, complete with direct links to the exact runtime logs. 
• Job Scheduler Integration: Pipelines live directly inside the core EPM Job Scheduler, letting you plan executions right alongside your standard system maintenance blocks. 

The Bottom Line 

The Oracle Cloud EPM Pipeline is no longer a peripheral feature—it is the definitive future of platform automation. By stripping away external scripting servers, providing native parallel processing, and breaking down boundaries between disparate EPM instances, Oracle has given administrators a cleaner, safer, and faster way to manage the financial close and planning cycles. If your organization is still leaning heavily on legacy Data Management batches or fragile external EPM Automate scripts, it’s time to plan your migration. The Pipeline is ready for prime time.

Demystifying the Black Box: AI Hits Enterprise Profitability & Cost Management (EPCM)

For corporate finance teams, Profitability and Cost Management (PCM) has historically been the most mathematically dense, computationally heavy corner of the EPM ecosystem. Running complex, multi-stage allocations to slice shared services, calculate true product margin, or map IT financial management feels entirely necessary—but tracing how a dollar of cost moved through fifty steps is a notorious headache.

Oracle’s blockbuster Spring 2026 EPM Cloud updates have completely changed the game. Oracle is focusing its massive Generative AI and Agentic AI rollout directly on Enterprise PCM (EPCM), introducing tools designed to open the allocation "black box."
If you’re looking to add speed and transparency to your costing models, here is how AI and a fresh user experience are reshaping EPCM this quarter.

1. Meet Your New Assistant: The PCM Interrogation Agent
The biggest headline of the release is the official debut of the PCM Interrogation Assistant inside Oracle’s Fusion AI Agent Studio.
Instead of manually digging through massive allocation trace spreadsheets or auditing individual rule sets to figure out why an operational cost pool spiked, you can now use natural language to interrogate your model.

How it works:

The embedded AI agent scans your modeling artifacts, application context, rule paths, and structural metadata. You can literally ask the assistant: "Show me the source logic for our corporate IT allocations this month," or "What rule sets impacted our logistical cost objects in Q1?"
This drastically lowers the barrier to entry for business users and executives who need to trust the validity of profitability reporting but don't know how to navigate backend calculation scripts.

2. The Great UI Redesign Becomes the Default
To support this new AI-driven model analysis, Oracle has completely overhauled the visual workspace. After introducing a revamped interface via optional Substitution Variables in the previous patch, Designer 2.0 is now the default experience.

The following primary screens have been completely rebuilt with a sleek, modern look:

• Models and Rule Designer
• Calculation Control and Calculation Analysis

The new interface drastically improves visibility when mapping driver weights and managing multi-step allocation execution. If your team isn't quite ready to switch over during a live close cycle, you can temporarily revert to the 1.0 legacy screens using Substitution Variables—but keep in mind that Oracle will completely remove the old UI starting with the 26.07 update this summer.

3. Fueling External AI Agents with New REST APIs

If your organization is building proprietary internal AI tools or cross-platform executive dashboards, Oracle is making it much easier to programmatically feed EPCM insights into those pipelines.

Oracle rolled out three new Agentic AI REST APIs this quarter. Most notably, the Get Application SummaryAPI extracts a highly dense, AI-optimized text brief of your EPCM model structure. Combined with new high-velocity JSON data grid exports, your data science or corporate automation teams can seamlessly pull allocation slices and data queries into external frameworks without clunky CSV scripts.

4. Under-the-Hood: Optimizing Calculation Speed

AI requires a rock-solid data engine, and Oracle paired these intelligence features with core calculation optimizations designed to speed up long-running allocation batches on sparse cubes:

• Non-Empty Tuple (NET) Settings: A new preference allows allocation rules to perform exponentially faster by skipping empty data intersections.
• Skip Scripts When Data is Missing: Currently in beta, this setting tells the calculation engine to automatically bypass rules if the source data pools are empty, saving precious processing minutes during month-end stress periods.

The Bottom Line
The Spring 2026 updates prove that Oracle views Enterprise PCM as a primary beneficiary of the generative AI boom. By embedding the PCM Interrogation Assistant directly into the modeler's workflow, Oracle is shifting cost allocation from a complex backend IT process into an accessible, conversational strategic asset.

What’s Hot in Oracle Cloud EPM (EPBCS): Spring 2026 Release Highlights

If you manage an Enterprise Planning and Budgeting Cloud Service (EPBCS) environment, your spring just got a whole lot busier—and a lot more exciting.

After a brief pause in monthly updates to thoroughly iron out Essbase 21c backend fixes, Oracle officially roared back with its Spring 2026 EPM Cloud updates. This quarter’s drops are heavy on productivity, offering a massive leap forward in Generative AI, smoother integration pipelines, and critical infrastructure updates that you need to account for immediately.

Let's break down the most impactful new features hitting your EPBCS environment this quarter and what they mean for your finance team.

1. Agentic AI & Generative AI Go Global

Oracle isn't just treating AI like a buzzword; they are embedding it directly into the fabric of FP&A.

• Global Gen AI Availability: Generative AI capabilities have officially rolled out across all regions in the primary OC1 realm, as well as OC4, OC19, OC29, and OC42.

• Agentic AI REST APIs: Oracle introduced three new REST APIs specifically designed to fuel Agentic AIinteractions. This includes a new Get Application Summary API that generates an AI-focused brief of an EPM application, alongside advanced JSON data grid exports. If you are building internal AI agents or automated bots to pull or analyze planning data, these APIs are your new best friend.

2. Infrastructure & Scripting: The Mandatory Groovy Update

This is the "stop what you're doing and check your code" headline of the quarter.

Oracle has deployed a mandatory Groovy engine upgrade. This update introduces much stricter validation rules for your custom calculations and rules. If you have complex, tailored Groovy scripts running your driver-based planning or data movements, you need to test them in your sandbox environment immediately to prevent scripts from breaking in production.

On the bright side, Groovy rules have also been enhanced to natively support the copying of relational data, comments, attachments, and supporting details, giving you far more automation flexibility.

3. Data Integration: Essbase Load Rules & Smarter Pipelines

Data integration admins are getting some highly requested quality-of-life improvements this quarter.

• Native Essbase Load Rules Support: In a massive win for hybrid or migrating environments, you can now migrate classic Essbase data load rules directly into Cloud EPM applications without completely rebuilding them as Data Integrations from scratch.

• Restart Pipelines from Failed Stages: We’ve all been there: a massive data pipeline fails at step 7 out of 10, and you have to rerun the entire thing from midnight. No more. You can now restart automated pipelines directly from the specific stage that failed.

• Pipeline Wait Times: You can now inject precise wait times and pauses within pipeline jobs, allowing dependent backend processes or file transfers time to breathe before the next job triggers.

4. Next-Level Security & Maintenance: Physical Backups

Historically, EPBCS administrators relied solely on Artifact Snapshots for daily maintenance. This quarter, Oracle introduced a brand-new Environment Backup system.

This creates a full backup at the physical tier during daily maintenance. Alongside this, the new restoreEnvironment EPM Automate command allows you to roll back and restore environments with a much deeper layer of data integrity.

Additionally, the essbaseBlockAnalysisReport utility has been upgraded to show the percentage of Essbase blocks containing near-zero values. This is an incredible tuning tool, as near-zero values heavily bloat application size and tank calculation performance.

Head's Up: Watch Your EPM Automate Scripts!

A minor change that could cause a major headache: the default installation path for EPM Automate on Windows has moved to the standard Program Files\Oracle\EPM Automate directory. If you have batch files or Windows Task Scheduler scripts hardcoded to legacy pathing, you'll want to update those file paths before your next scheduled run.

The Bottom Line

The Spring 2026 updates prove that Oracle is laser-focused on turning EPBCS into a highly automated, AI-driven machine. From Agentic AI capabilities to granular pipeline controls, these changes remove friction for finance teams—provided your admins proactively test the new Groovy validation limits.

The Evolution of Master Data: From the Genesis of Oracle EDM to the AI-Driven Mesh

In the landscape of modern enterprise architecture, a single, sobering truth has emerged: your enterprise AI is only as smart as your master data. If your organizational hierarchies, charts of accounts, and entity mappings are perfectly synchronized, the advanced machine learning models deployed across your tech stack can operate at peak performance.

Achieving flawless master data has transformed from a rigid, manual process into an agile, automated experience. To fully understand the power of today's intelligent enterprise data layer, we must look back at the journey of Oracle Enterprise Data Management (EDM) Cloud—tracing its trajectory from a core structural utility tool into an AI-powered control plane.

2018: The Genesis of Application-Centric Governance

When Oracle launched Enterprise Data Management Cloud (originally EDMCS) in early 2018, it marked a massive philosophical shift in data governance.

For nearly two decades, the standard for managing corporate hierarchies was Oracle Data Relationship Management (DRM)—a highly robust, on-premises engine. However, DRM was built for the classic, waterfall style of IT deployment: gather requirements for months, build a massive canonical model, deploy it, and manage it through heavily centralized IT workflows.

Oracle EDM disrupted this paradigm by introducing an application-centric approach. Instead of forcing an organization to agree on a single, unchanging data model across ERP, EPM, HCM, and SCM systems, EDM allowed different departments to maintain their unique perspectives, known as Viewpoints. It recognized that finance, operations, and human resources see the company through different lenses, providing the structural workflows to safely bridge them in real time.

The Automation Bridge: Data Ingestion & Cross-Viewpoint Subscriptions

As EDM matured, its capability to orchestrate change across diverse application environments transformed the platform into a critical operational hub. It transitioned from a static repository of record into an active change agent through two core components:

• Packaged and Universal Adapters: Oracle built deep, native awareness directly into EDM for platforms like Oracle ERP Cloud, EPM Cloud, NetSuite, and Salesforce, while providing universal adapters for external environments. Registering a new application became an automated, wizard-driven process.

• Automated Subscriptions: This became the foundational engine for cross-system harmony. When a data steward created or altered an operational node—such as establishing a new cost center within a core ERP framework—downstream systems could subscribe to those changes. EDM automatically generated the corresponding structural adjustments in financial consolidation or workforce planning modules, instantly translating attributes to match target requirements.

The Modern Paradigm: Commercialization via EPM Enterprise

Architecturally, data integrity is no longer treated as an isolated infrastructure cost. Oracle formalized this concept by embedding EDM directly into its Cloud EPM Enterprise Subscription.

Under Oracle's simplified licensing structure, organizations choosing the Enterprise tier gained full access to the complete EPM ecosystem—spanning Planning, Financial Consolidation, and Narrative Reporting—with EDM serving as the shared data layer. By removing the friction of standalone data-governance pricing, Oracle enabled organizations to implement strict corporate governance across all applications from day one, setting up a clear path for the next major technological boundary: Enterprise AI.

The AI Reality: Powering the Intelligent Digital Mesh

The current era has introduced a major operational upgrade. Oracle's embedded AI ecosystem operates on two distinct, powerful levels: Internal System Optimization and serving as the Enabling Foundation for Broad Enterprise AI.

1. Internal AI Assistants

Integrated directly into the EDM request and governance framework, native intelligent assistants drastically reduce administrative friction and accelerate delivery:

• The Registration Assistant: Setting up a brand-new application structure used to take days of schema design. The platform now utilizes automated configuration assistants to scan financial ledger files, analyze the shape of the data, and automatically generate the necessary metadata and application artifacts in seconds.

• The Conversational Request Assistant: Business users no longer need to navigate deep hierarchy trees to make updates. They can query master data using conversational, natural language (e.g., "Show me all vacant cost centers in the APAC region and move them under our new Singapore entity"). The assistant interprets the request, models the impact across viewpoints, and places the changes directly into a secure, auditable request cart for human approval.

2. The Anchor for Enterprise GenAI (Maximizing AI ROI)

Beyond internal productivity, EDM serves as the ultimate catalyst for maximizing the return on investment for corporate Generative AI initiatives.

When an executive asks a conversational AI agent a strategic question—such as comparing regional tech expenditures across business lines—the AI model must read data coming from various sources (ERP, EPM, and Supply Chain engines). Oracle EDM ensures this process is seamless.

The Structural Truth: Oracle EDM serves as the definitive source of reference for your data mesh. By providing clearly governed node descriptions, accurate parent-child rollups, and exact mappings across disparate ledgers, EDM acts as the verified map that corporate AI models rely on. It ensures that when your AI agents query your financial systems, they interpret data cleanly, accurately, and with maximum contextual intelligence.

Looking Ahead: Continuous Data Harmony

The journey of Oracle EDM from its launch to the present day reflects the broader evolution of enterprise technology. What began as a tool to clean up messy financial hierarchies has become a vital strategic asset.

By automating real-time updates via robust data subscriptions, offering an accessible consumption model within the EPM Enterprise layer, and deploying conversational AI tools, Oracle EDM ensures that your data layer remains agile, organized, and prepared to power the future of autonomous corporate intelligence.

Thank you!

Frictionless Finance: Oracle Cloud FCCS Spring 2026 Release Highlights

 The corporate close cycle is a race against the clock, where victory is measured in hours saved and variances eliminated. For accounting and finance teams running Oracle Financial Consolidation and Close Cloud Service (FCCS), the newly deployed Spring 2026 platform updates are here to give you an analytical edge.

Following a period focused heavily on backend infrastructure stability—specifically optimizing the Essbase 21c migration framework—Oracle’s recent 26.04 and 26.05 updates shift the focus back to user empowerment. This quarter’s release delivers game-changing ownership controls, smarter consolidation logic, and critical performance enhancements designed to squeeze every second out of your close window.

Here is what FCCS administrators and controllers need to know about the new release.

1. Advanced Enterprise Journal Workflows

Enterprise Journals are vital for maintaining compliance and keeping an audit trail during manual adjustments but managing them across multi-entity global structures can get messy. This quarter introduces highly requested flexibility to validation and posting processes:

• Bypassing Non-Applicable Validations: Administrators can now configure specific Enterprise Journals to bypass redundant validation rules that only apply to standard data forms. This prevents system-generated warnings from clogging up your workflow when posting specialized top-side adjustments.

• Enhanced Audit Tracking on Bulk Approvals: When controllers approve or post journals in bulk at quarter-end, the system now stamps precise user-context metadata across all affected entities simultaneously, giving internal auditors an unshakeable electronic paper trail.

2. Dynamic Ownership Management & Equity Pickup

Tracking complex, multi-tiered corporate structures with changing ownership percentages is one of the most mechanically demanding parts of a consolidation. Oracle has pushed two major mathematical optimizations to address this:

• Weighted Ownership Account Processing: FCCS has overhauled how the system calculates and inherits rules based on the Weighted Ownership Account property. When ownership stakes shift mid-month, the consolidation engine now processes statutory calculations using more precise time-weighted variables, reducing manual true-up entries.

• Optimized Equity Pickup (EPU) Performance: For organizations using the native Equity Pickup feature to record a parent's share of a subsidiary’s net income, the backend calculations have been streamlined. By eliminating redundant multi-currency evaluation passes, EPU rules now execute significantly faster during the consolidation phase.

3. High-Velocity Consolidations: Near-Zero Block Purging

As an FCCS application matures, years of historical data movements can leave behind millions of "near-zero" or empty data blocks within the underlying Essbase cube. This data bloat subtly degrades consolidation speeds over time.

Oracle has introduced an incredibly powerful maintenance upgrade this quarter:

• The essbaseBlockAnalysisReport Upgrade: Administrators can now run a deep-dive diagnostic that isolates the exact percentage of data blocks containing near-zero values.

• Targeted Performance Tuning: Armed with this report, admins can selectively purge these dead blocks during the daily maintenance window without impacting historical data integrity, resulting in immediate performance gains during heavy, concurrent user-driven consolidations.

4. Enhanced Data Integration & Pipeline Resiliency

When your ERP system feeds data into FCCS, a single failed mapping rule shouldn't ground your entire reporting cycle to a halt.

• Stage-Specific Pipeline Restarts: If a multi-step data integration pipeline encounters an error at a later stage (such as during final data validation or the FCCS load phase), you no longer have to rerun the entire extraction process from your source ERP. You can now restart automated pipelines directly from the exact stage that failed.

• Native Integration for Legacy Load Rules: If your organization is migrating legacy on-premise Hyperion Financial Management (HFM) elements or classic Essbase components into the cloud, you can now import data load rules directly into Cloud EPM Data Integration without rewriting the logic from scratch.

The Bottom Line

The Spring 2026 FCCS release proves that Oracle is listening to corporate controllers who demand both speed and rigorous compliance. By cutting out processing bloat, offering smarter journal workarounds, and making data pipelines resilient to real-world failures, this update helps your accounting team spend less time managing the system and more time analyzing the numbers.

Thank you!

Navigating the Shift: Oracle Tax Reporting Cloud (TRCS) Spring 2026 Update Highlights

Corporate tax departments are currently facing an unprecedented wave of global regulatory pressure. Between the ongoing enforcement of OECD Pillar Two rules and the logistical nightmare of cross-border financial reconciliation, tax automation has shifted from a luxury to an absolute baseline necessity.

Recognizing this, Oracle’s Spring 2026 EPM Cloud updates delivered highly targeted features specifically engineered for Tax Reporting Cloud Service (TRCS).

If you are a corporate tax director or a TRCS administrator, here are the most significant upgrades hitting your environment this quarter and how they will streamline your tax provisioning and compliance workflows.

1. Perfecting OECD Pillar Two (GloBE) Automation

As Pillar Two moves from transitional safe harbors into strict data-driven calculations, Oracle is continuing to build out its native Global Minimum Tax automation framework.

• Configurable Source Period for Average Logic: In the Pillar Two GloBE Automation engine, you can now configure specific source periods when applying average logic. This gives tax teams precise control over how multi-period financial data is aggregated and smoothed when calculating effective tax rates and top-up taxes across jurisdictions.

• Enhanced Currency Translation for Pillar Two: Currency volatility can heavily distort Pillar Two math if it isn't tightly controlled. Oracle has enhanced currency translation rules specifically for Pillar Two schedules, ensuring that local statutory data translates seamlessly into the consolidated reporting currency while matching rigid OECD technical specifications.

2. Simplifying Complex International FX Calculations

Managing cross-border tax provisioning requires navigating incredibly dense Foreign Exchange (FX) calculations. This quarter, Oracle pushed two major updates to how TRCS handles parent-subsidiary translations:

• Dynamic Child-to-Parent Blended FX Rates: You can now configure TRCS to translate parent entities utilizing a blended FX rate derived dynamically from its child entities. This is a massive win for complex legal entity structures where a static parent rate doesn't accurately reflect the real-world tax exposures of the underlying entities.

• Target-to-Source Movement Linking: TRCS now supports translating target data movements by directly inheriting the FX rates applied to specific source movements. This ensures mathematical locking and zero variance during the reconciliation process between your financial accounting book lines and your final tax provision lines.

3. Smarter Return to Accrual (RTA) Automation

• RTA Automation Validation Upgrades: Oracle has enhanced its validation protocols specifically for Return to Accrual automation. When calculating True-Up adjustments—comparing the previous year's filed tax return against what was actually booked in the accruals—new validation features help tax administrators catch anomalies, map data errors, and troubleshoot alignment issues before the data locks.

4. Under-the-Hood Cleanup: Metadata & Security

Because TRCS runs on Oracle's core EPM platform, tax administrators need to be aware of a few foundational cleanups designed to make your system faster and more secure:

• Optimized Metadata Validation: Validation logic tied to critical TRCS metadata properties—such as Consolidated ETR, Tax Data Type, Domicile, and Weighted Ownership Account—has been optimized. The system will no longer trigger redundant hierarchy-based validations on mapping-bound viewpoints, noticeably accelerating your metadata synchronization times.

• Deprecation of Legacy Network Security Commands: Oracle has officially removed the legacy setIPAllowList and getIPAllowList EPM Automate commands. If your internal IT or tax security team used these specific commands to restrict access to tax data via automated scripts, they must transition to managing access via the Oracle Cloud Infrastructure (OCI) identity tier or Access Control lists.

The Bottom Line

The Spring 2026 updates show that Oracle is heavily invested in turning TRCS into a robust compliance engine capable of handling the volatile global tax landscape. From Pillar Two refinements to cleaner FX translations, these upgrades take a significant amount of manual labor off your tax team's plate.

Thank you!

Beyond the Spreadsheet: Automating OECD Pillar Two and Public CbCR with Oracle TRCS and Generative AI

The days of treating Country-by-Country Reporting (CbCR) as a low-stakes, retrospective transfer pricing compliance exercise are officially over.

We are now firmly entrenched in a new era of global tax enforcement. Multinational tech enterprises face an unprecedented compliance challenge: the strict implementation of OECD Pillar Two Global Minimum Tax rules and expanding public disclosure mandates across the European Union and Australia.

For large tech companies managing complex multi-jurisdictional structures, hundreds of legal entities, and shifting intellectual property (IP) frameworks, the traditional tool of choice—the manual corporate spreadsheet—has become a massive liability. To keep pace with rapid legislative changes, corporate tax departments are transitioning to a more robust approach: anchoring their data inside Oracle Tax Reporting Cloud Service (TRCS) and augmenting it with Generative AI.

The Strategic Shift: Linking TRCS and Intelligent Automation

Oracle TRCS acts as a bridge between corporate financial accounting and tax reporting. By combining the system's foundational calculation engines with predictive data pipelines and generative narratives, tax departments are transforming how they handle global compliance.

1. Eliminating Data Fragmentation with Automated Ingestion

A primary bottleneck in tech CbCR is pulling inconsistent data from disparate regional ledgers. Using Oracle TRCS, tax teams map data directly from Oracle ERP Cloud and external third-party systems into a unified platform.

• The Integration: TRCS applies Enterprise Data Management (EDM) principles to map legal entities dynamically.

• The AI Edge: Embedded machine learning algorithms automatically flag anomalies or mismatching tax codes during data ingestion. If an IP holding entity in Ireland or a data center hub in Singapore reflects an unexpected jump in revenue or a shift in employee headcount, the system surfaces the discrepancy before the CbCR consolidation phase occurs.

2. Accelerating Pillar Two Safe Harbor Determinations

The connection between CbCR and the OECD Pillar Two Global Minimum Tax is critical. Under Pillar Two, multinational enterprises must pass specific Transitional CbCR Safe Harbor tests to avoid the resource-heavy burden of calculating full top-up taxes.

• The Integration: Oracle TRCS features a dedicated, out-of-the-box Pillar Two Automation Module. It calculates the three foundational safe harbor tests: the De Minimis test, the Simplified Effective Tax Rate (ETR) test, and the Routine Profits test.

• The AI Edge: Rather than treating this as a static, year-end calculation, predictive analytics within the Oracle EPM ecosystem run continuous forecasts. If shifting revenues or changing tax credits threaten to drop a tech entity out of Safe Harbor status mid-year, the system triggers an intelligent warning, allowing tax planners to model the financial impact of top-up taxes well in advance.

3. Writing Public Defenses with Generative Narratives

The ultimate challenge of modern CbCR is that public disclosures require explanations. Under EU public CbCR mandates, corporations must explain why corporate profits align with local economic presence. Tech companies often show heavy profits in low-tax jurisdictions due to R&D and digital sales, which can trigger aggressive audits if left unexplained.

• The Integration: Oracle TRCS compiles the quantitative data required for Table 1 and Table 2 of the statutory CbCR XML schema.

• The AI Edge: Leveraging Oracle's Contextual Generative AI Insights, TRCS interprets these exact quantitative tables. By reading the book-to-tax differences, deferred tax assets, and localized headcount, the system automatically drafts a compliant, natural-language narrative. For example, it can instantly articulate how a timing difference or a localized stock-based compensation deduction caused a temporary gap between cash taxes paid and accrued tax. This provides human tax directors with a highly technical, auditable first draft for public defense.

Achieving Continuous Compliance

Relying on manual spreadsheets to cross-reference transfer pricing data against public financial statements is no longer viable. Global tax authorities are deploying their own automated risk-assessment tools to analyze corporate tax data in real time.

By anchoring global operations within the standardized environment of Oracle TRCS—and augmenting it with automated data validation, safe harbor simulations, and AI-generated narrative reporting—multinational tech organizations ensure their public numbers are defensible, consistent, and audit-ready before they ever leave the department.

Thank you!

IPM Insights: Support for Scaling and Precision

From June'26 monthly patch onwards, we can specify precision and scaling settings for IPM Insights.

To apply scaling and precision for IPM Insights:

1. From the Home page, click IPM and then click Settings. This option is available for all users.
2. To turn on scaling, select Apply Scaling (K- Thousands, M- Millions, B - Billion, T- Trillion) to values displayed in IPM Insights. 
3. Scaling is applied to currency values and non-currency values.
4. Specify the precision to apply after scaling for currency values and non-currency values and percentage values.
5. The default values are the precision settings that are set in User Preferences. The Example Preview panel shows how values will appear with the specified settings.
6. Click Save.

The settings are applied throughout the Insights list, and in the Insights Analyzer View, for example, in the insight description, the graph, the grid, the Explainability tab, and the Insights AI tab.

IPM Insights Scaling and Precision Settings

Alternatively, administrators can apply scaling using a UDA. If you use a UDA, it takes precedence over preferences and settings for scaling. You must first select Apply Scaling (K, M, B, T) to values displayed in IPM Insights in IPM Settings.

To apply a UDA:

1. Open the Dimension Editor.
2. Select the Account dimension and member to edit.
3. Click the UDA tab.
4. Apply one of the following UDAs and then click Save.
1. HSP_DISPLAY_SCALE_K
2. HSP_DISPLAY_SCALE_M
3. HSP_DISPLAY_SCALE_B
4. HSP_DISPLAY_SCALE_T

Business Benefit: 

Scaling and precision settings ensure consistent formatting for all data values displayed for an Insight.

Tips and considerations

1. By default, the Apply Scaling (K, M, B, T) to values displayed in IPM Insights option is enabled, and insights are displayed for each user using the precision set in their User Preferences.
2. You can apply a UDA only to the Account dimension.
3. Scaling and precision settings are not applied in ad hoc grids.
4. To apply the precision settings to narrative summaries for existing insights, you must re-run the insight.

Applies To: 

FCCS, TRCS, FreeForm, Planning and Enterprise Profitability and Cost Management