Role-Based Programme
RB0385

Ollama for Risk & Internal Audit

Private AI Workflows for Risk Analysis, Audit Evidence & Control Review

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

Programme Objectives

  • Develop practical proficiency in using Ollama to run local AI models for risk-management and internal-audit workflows.
  • Apply locally hosted LLMs to risk identification, control review, audit planning, evidence analysis, findings, and reporting.
  • Create structured prompts and reusable local AI workflows for policies, risk registers, audit documents, and control information.
  • Explore privacy-focused document analysis and retrieval approaches for sensitive risk and audit information.
  • Apply responsible AI practices covering confidentiality, evidence integrity, model limitations, traceability, access controls, and professional judgement.

Tools covered

OllamaLocal LLM RuntimeOllama CLIModel LibraryModelfileOllama APIEmbedding ModelsLocal Document AnalysisPrompt Templates

Who should attend

  • Risk Managers
  • Internal Audit Managers
  • Internal Auditors
  • Enterprise Risk Management Professionals
  • Operational Risk Professionals
  • Technology Risk Professionals
  • Risk Analysts
  • Audit Analysts
  • Internal Control Professionals
  • Governance, Risk & Compliance Professionals
  • Assurance Professionals
  • Compliance Audit Professionals
  • Risk Advisory Professionals
  • Audit & Risk Team Leads

Prerequisites & Participant Readiness

  • Working understanding of risk-management or internal-audit processes
  • Familiarity with risk registers, controls, audit evidence, findings, and remediation
  • Basic understanding of generative AI and large language models
  • Basic familiarity with command-line tools is helpful
  • Basic awareness of APIs and structured data is beneficial
  • No advanced programming expertise required
  • No previous Ollama experience required

TOC Modules

Concepts
  • Understanding local LLMs and how Ollama runs AI models on organizational infrastructure
  • Comparing local AI processing with externally hosted AI services
  • Identifying suitable applications across risk assessment, audit planning, evidence review, and reporting
  • Understanding model limitations and professional accountability
Practical activities
  • Installing or accessing an approved Ollama environment
  • Exploring the Ollama CLI and available models
  • Running a basic risk or audit prompt locally
  • Mapping Audit Task → Local Model → Output → Auditor Review workflow

Scenarios

Confidential Internal Audit Using Local AI

Audit Scope → Local Policy & Control Documents → Ollama Analysis → Risk & Control Matrix → Evidence Review → Potential Exceptions → Auditor Validation → Audit Finding

Participants use a locally hosted model to analyze sensitive audit material, map risks and controls, and identify evidence requiring investigation while retaining full auditor ownership of conclusions.

Enterprise Risk Register to Audit Committee Brief

Risk Register → Ollama Local Analysis → Risk Themes → Control Mapping → Emerging Concerns → Management Actions → Executive Risk Brief

Participants analyze an approved enterprise risk register in a private local environment, identify recurring themes and potential control concerns, and prepare a management-ready briefing grounded in validated source information.

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