Role-Based Programme
RB1390

AI for Financial Reporting & Controllership

Financial Close, Reporting Intelligence & Control Excellence

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for financial close, controllership, reconciliations, financial reporting, and accounting analysis.
  • Apply AI to analyse general-ledger information, account movements, reconciliations, reporting schedules, exceptions, and financial-statement trends.
  • Use AI to strengthen close coordination, variance explanations, reporting commentary, accounting research, control documentation, and audit readiness.
  • Improve controllership effectiveness through structured exception analysis, reconciliation intelligence, control monitoring, and management reporting.
  • Apply responsible AI practices related to confidential financial information, accounting judgement, data accuracy, traceability, governance, and human oversight.

Tools covered

Generative AI AssistantsFinancial Data AnalysisFinancial Statement AnalysisReconciliation AnalysisClose Management SupportVariance & Flux AnalysisAccounting Research SupportInternal Control AnalysisAudit SupportException AnalysisManagement ReportingExecutive Summarisation

Who should attend

  • Financial Controllers
  • Corporate Controllers
  • Finance Controllers
  • Financial Reporting Managers
  • Financial Reporting Analysts
  • Controllership Professionals
  • General Accounting Managers
  • Record-to-Report Professionals
  • Management Accountants
  • Financial Accountants
  • Finance Managers
  • Closing & Consolidation Professionals
  • Internal Control Professionals
  • Finance Shared Services Professionals
  • Finance & Accounting Leaders

Prerequisites & Participant Readiness

  • Experience in financial reporting, accounting, controllership, record-to-report, or finance operations
  • Familiarity with general ledger, reconciliations, financial statements, period-end close, and accounting controls
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret accounting and financial information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring applications across close, reconciliation, reporting, controls, accounting research, and audit support
  • Understanding how AI complements ERP, consolidation, close-management, BI, and reporting platforms
  • Recognising hallucinations, calculation errors, unsupported accounting conclusions, and reporting risks
Practical activities
  • Mapping the financial reporting and controllership lifecycle to practical AI applications
  • Identifying high-value versus high-risk finance use cases
  • Comparing traditional and AI-assisted controllership workflows

Scenarios

Month-End Close Delay to Financial Close Recovery

Close Status → Outstanding Activities → Reconciliation Exceptions → Account Movements → Dependency Analysis → Priority Actions → Review → Close Recovery Plan

Participants use AI to analyse a simulated delayed month-end close, identify critical bottlenecks and reconciliation issues, prioritise outstanding activities, and create a structured recovery plan.

Material Financial Movement to Controller Review

Financial Statements → Material Variance → Ledger Analysis → Supporting Evidence → Accounting Assessment → Control Review → Management Commentary → Controller Brief

Participants use AI to investigate a simulated material financial movement, analyse supporting accounting information, identify control and reporting considerations, and prepare a management-ready controllership brief.

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