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Duration 7 hours
Course Outline
Module 1: Manus for Financial Professionals
- Defining the AI agent lifecycle: planning, acting, and delivering results versus simple answering
- Comparing Chat mode and Agent mode: criteria for selecting the appropriate approach
- Understanding the credit system: typical task costs and managing the team’s shared pool
- Interface overview: tasks, Projects, files, connectors, Skills, and Automations
- Identifying suitable applications in finance, forensic, and corporate workflows, as well as recognizing limitations
- Practical: Execute a small task in both modes and compare outcomes against credit costs
Module 2: Briefing, Steering, and Review
- Crafting actionable briefs: defining goals, inputs, output formats, and constraints
- Monitoring agent activity: intervening during tasks and managing browser or login steps
- Evaluating outputs: key verification points, requesting sources, and criteria for re-running tasks
- Practical: Conduct background and regulatory research on a specific target company
- Practical: Use Wide Research to benchmark multiple companies against identical criteria
Module 3: Managing Financial Data
- Data ingestion: uploading spreadsheets, PDF statements, and finance system exports
- Data hygiene: standardizing ledgers, constructing formulas, and creating summaries in Excel-style formats
- Data extraction: converting figures from PDF financial statements into structured tables
- Analysis techniques: reconciliations and anomaly detection (duplicate checks, round-number tests, Benford’s law screening)
- Practical (Forensic): Identify anomalies in a synthetic transaction ledger and document the methodology
- Practical (Corporate Finance): Construct a comparables table from provided financial statements
Module 4: Deliverables and Repetition
- Creating final outputs: generating memos, slide decks, and interactive dashboards from a single analysis
- Project management: consolidating files, instructions, and context for specific engagements
- Skill creation: converting successful workflows (e.g., due-diligence checklists) into reusable steps
- Automation: setting up scheduled or event-triggered tasks, such as weekly market updates
- Practical: Package Module 3 analysis into a memo and slides, then save the process as a Skill
Module 5: Risk, Governance, and Credit Management
- Data governance: defining permissible data inputs, client confidentiality, and regulatory compliance
- Provider landscape: analyzing Manus ownership changes (2025–26) and the August 2026 data deletion policy, and their impact on data strategy
- Output verification: identifying hallucinations, outdated sources, and calculation errors; enforcing citation and spot-checking practices
- Audit trails: preserving task histories, exporting results, and documenting agent actions
- Cost efficiency: task sizing, using Chat mode for simple queries, and preventing excessive credit usage
- Discussion: drafting a one-page team usage policy
Module 6: Capstone and Next Steps
- Development of a personalized workflow based on each participant’s role
- Group presentation with feedback from the trainer and peers
- 30-day action plan: identifying two tasks to migrate to Manus and one Skill to develop
- Resources: prompt patterns, review checklists, and credit management guides
Requirements
- Basic proficiency with web applications is required; prior experience with AI is not necessary
- Each participant must access their own Manus license via a work laptop using Chrome or Edge. As Manus is a cloud-based service, no virtual machine installation is needed.
- Verify the Manus subscription plan and credit balance prior to the course. It is advisable to schedule the session early in the billing cycle, as a full day of practical work may consume a significant portion of the team’s monthly credits.
- Coordinate with IT departments to confirm approved connectors (such as Gmail, Google Drive, or Notion) to ensure alignment between demonstrations and post-course usage.
- The trainer will utilize a separate paid Manus account for preparation and live demonstrations.
- All exercise data is synthetic and provided by the trainer; participants should not bring client data.
- Complete the pre-course survey (approx. 10 minutes) by submitting one or two repetitive tasks from current workflows, at least one week before the session.
Target Audience
- Finance Associates
- Forensic Accountants
- Corporate Finance Professionals
Testimonials (4)
The difference between strategy and plan
Berat Rahmani - Wallee Group AG
Course - Leadership and Team Management for Managers
How to manage business financials
surprise mtileni - Hatima Holdings (Pty) ltd
Course - Learning Xero
Good communication, open for discussion, kept it interesting and engaging
Ahmet Keyman - Keytrade AG
Course - Management Accounting and Finance for Non-Finance Professionals
Experience of the trainer and his way of conveying the content
