Course Introduction
Process mining is transforming finance and internal audit by enabling organizations to reconstruct actual business processes directly from system event data, compare real workflows with approved procedures, and identify deviations, bottlenecks, control failures, inefficiencies, and unusual transaction patterns. This course provides a comprehensive framework for applying process mining to financial processes and risk-based internal auditing.
The course examines how process mining connects enterprise systems, transaction records, workflow logs, and audit objectives to create evidence-based views of how financial processes actually operate. Participants will learn how to move beyond documented procedures and examine real process execution across accounts payable, accounts receivable, procurement, order-to-cash, record-to-report, payroll, treasury, fixed assets, and other finance processes.
Participants will explore the complete process mining lifecycle, including process discovery, data extraction, event-log construction, data preparation, process visualization, conformance checking, performance analysis, root-cause analysis, anomaly detection, and continuous monitoring. Particular attention is given to understanding event data, case identifiers, timestamps, activities, transaction attributes, process variants, rework, loops, bottlenecks, and deviations that may indicate financial control weaknesses or operational risks.
The course places strong emphasis on internal audit applications. Participants will learn how process mining can support audit planning, risk assessment, control testing, transaction testing, fraud risk identification, continuous auditing, audit scoping, root-cause analysis, and management reporting. They will also examine how process mining can expand audit coverage by analyzing complete transaction populations rather than relying solely on traditional sampling approaches.
Data quality and governance are addressed throughout the programme because process mining results depend heavily on reliable event data and appropriate process definitions. Participants will examine data completeness, timestamp quality, duplicate records, missing events, inconsistent identifiers, system interfaces, master data, privacy, access controls, and transformation logic. The course also addresses how analytical findings should be validated before they become audit conclusions.
Through practical exercises and an integrated finance audit case study, participants will reconstruct financial processes, identify process variants, perform conformance analysis, investigate control deviations, quantify inefficiencies, and develop audit findings. The course equips finance and internal audit professionals to use process mining as a practical bridge between transaction data, operational reality, control assurance, and continuous improvement.
Duration
10 days
Who Should Attend
-
Internal auditors seeking advanced process analytics and continuous auditing capabilities.
-
Finance managers responsible for improving financial processes and internal controls.
-
Audit managers and supervisors designing data-driven audit methodologies.
-
Financial controllers responsible for process performance, compliance, and control effectiveness.
-
Risk and compliance professionals analyzing process-level financial risks.
-
Process owners responsible for procure-to-pay, order-to-cash, record-to-report, or related finance processes.
-
Data analysts supporting finance, internal audit, risk, and control functions.
-
Business process improvement professionals working with finance and shared-service operations.
-
IT auditors evaluating ERP systems, workflows, interfaces, and automated financial controls.
-
Forensic accountants investigating unusual transaction flows and process deviations.
-
Continuous auditing and continuous monitoring specialists.
-
Finance transformation professionals implementing ERP and digital process improvements.
-
Governance professionals evaluating process compliance and control performance.
-
Internal control specialists responsible for process design and testing.
-
Professionals seeking practical expertise in process mining for finance and internal audit.
Course Objectives
-
Develop a comprehensive understanding of process mining concepts and their application to finance, internal controls, risk management, and internal auditing.
-
Distinguish process discovery, conformance checking, performance analysis, process enhancement, and continuous monitoring techniques used in financial process mining.
-
Identify suitable financial processes and transaction populations for process mining based on risk, volume, complexity, control objectives, and data availability.
-
Build reliable event logs using financial system data containing appropriate case identifiers, activities, timestamps, users, organizational units, and transaction attributes.
-
Analyze actual financial process execution to identify deviations from approved procedures, unauthorized steps, rework, bottlenecks, delays, and control weaknesses.
-
Apply conformance checking techniques to compare actual transaction flows against policies, workflows, approval requirements, and control frameworks.
-
Use process mining to strengthen internal audit planning, risk assessment, control testing, transaction testing, continuous auditing, and audit evidence.
-
Identify unusual process variants, transaction paths, repeated activities, skipped controls, excessive overrides, and other indicators of operational or financial risk.
-
Evaluate data quality, event-log completeness, system interfaces, master data, timestamps, and transformation logic before relying on process mining results.
-
Apply root-cause and performance analysis to determine why process deviations occur and distinguish isolated exceptions from systemic control weaknesses.
-
Develop dashboards and continuous monitoring indicators that provide finance and internal audit teams with timely visibility into process compliance and emerging risks.
-
Design an integrated process mining audit framework that connects data analysis, professional judgment, evidence evaluation, findings, remediation, and continuous assurance.
Comprehensive Course Outline
Module 1: Foundations of Process Mining for Finance and Internal Audit
-
Examine process mining principles and their relevance to financial management, internal controls, operational efficiency, and audit assurance.
-
Compare traditional process documentation, transaction testing, sampling, data analytics, process mining, and continuous auditing approaches.
-
Identify financial processes where process mining can provide meaningful visibility into transaction flows, control execution, and process performance.
-
Establish a process mining framework connecting financial risks, process objectives, event data, control requirements, analytical findings, and audit conclusions.
Module 2: Finance Processes, Transaction Flows and Audit Risk
-
Map major finance processes including procure-to-pay, order-to-cash, record-to-report, payroll, treasury, and fixed asset transactions.
-
Identify key financial risks, control points, approvals, handoffs, system interactions, and exception paths within finance processes.
-
Assess process complexity, transaction volume, organizational structure, system dependencies, and risk factors when selecting audit priorities.
-
Develop risk-based process mining objectives aligned with internal audit plans, financial control frameworks, and management assurance needs.
Module 3: Process Mining Data and Event-Log Construction
-
Examine event-log components including case identifiers, activities, timestamps, users, organizational units, transaction values, and process attributes.
-
Extract and transform ERP, accounting, procurement, payment, workflow, and other system data into reliable process mining datasets.
-
Evaluate event ordering, timestamp consistency, duplicate records, missing events, incomplete cases, and inconsistent transaction identifiers.
-
Develop data preparation procedures that preserve transaction traceability and support reliable reconstruction of financial processes.
Module 4: Process Discovery and Financial Workflow Visualization
-
Use process discovery techniques to reconstruct actual finance workflows from historical transaction and system event data.
-
Analyze process maps to identify common transaction paths, alternative variants, loops, rework, unnecessary handoffs, and unexpected activities.
-
Compare documented finance procedures with actual transaction execution to identify differences requiring management or audit attention.
-
Interpret process visualizations in the context of financial controls, segregation of duties, authorization requirements, and operational responsibilities.
Module 5: Conformance Checking and Financial Control Compliance
-
Compare actual transaction flows with approved process models, policies, approval matrices, workflows, and control requirements.
-
Identify skipped approvals, unauthorized activities, segregation-of-duties conflicts, out-of-sequence transactions, and policy deviations.
-
Assess the frequency, financial value, organizational distribution, and recurrence of process conformance exceptions.
-
Develop audit procedures for validating process deviations and determining whether they represent control deficiencies, legitimate exceptions, or data issues.
Module 6: Process Mining for Procure-to-Pay Auditing
-
Analyze purchase requisitions, purchase orders, goods receipts, invoices, approvals, and payments across the procure-to-pay lifecycle.
-
Identify duplicate payments, invoice-before-order patterns, excessive approval delays, bypassed controls, split purchases, and unusual supplier activity.
-
Examine three-way matching, segregation of duties, approval thresholds, supplier changes, and payment timing using complete transaction populations.
-
Develop process mining audit tests linking procurement workflow deviations to financial exposure, control weaknesses, and potential fraud indicators.
Module 7: Process Mining for Order-to-Cash and Revenue Auditing
-
Reconstruct customer order, delivery, billing, receivables, collections, credit, returns, and adjustment processes using transaction event data.
-
Identify unusual billing sequences, delayed invoicing, unauthorized discounts, excessive credits, unusual returns, and revenue process deviations.
-
Analyze customer-level and organizational process variants to identify recurring weaknesses, revenue leakage risks, and control exceptions.
-
Apply conformance and performance analysis to revenue processes to support completeness, occurrence, cutoff, accuracy, and collection-related audit procedures.
Module 8: Record-to-Report, Journal Entries and Financial Close
-
Analyze journal entry creation, approval, posting, adjustment, reversal, reconciliation, and financial close activities through process event data.
-
Identify unusual posting sequences, repeated adjustments, late entries, manual overrides, approval bypasses, and period-end process anomalies.
-
Examine reconciliation workflows, account certification, close activities, and financial reporting controls for process deviations and delays.
-
Use process mining findings to strengthen audit procedures addressing financial statement risks, management override, cutoff, and reporting controls.
Module 9: Payroll, Treasury, Assets and Other Finance Processes
-
Apply process mining to payroll transactions including employee setup, changes, approvals, payroll processing, adjustments, and payments.
-
Analyze treasury workflows involving payment initiation, approval, bank processing, reconciliation, cash movements, and exception handling.
-
Examine fixed asset acquisition, capitalization, transfer, depreciation, impairment, disposal, and reconciliation process flows.
-
Identify process deviations and control weaknesses across other finance processes using transaction sequencing, timing, user, and organizational analysis.
Module 10: Process Performance, Bottlenecks and Root-Cause Analysis
-
Measure processing times, waiting periods, throughput, rework, handoffs, and other performance characteristics within financial processes.
-
Identify bottlenecks and recurring delays that may create financial, compliance, operational, or reporting risks.
-
Analyze process variants by business unit, location, supplier, customer, employee, transaction type, value, or responsible user.
-
Apply root-cause analysis to determine whether process problems arise from system design, staffing, policy, training, control gaps, or operational behavior.
Module 11: Fraud, Anomalies and Suspicious Process Patterns
-
Identify process patterns that may indicate fraudulent behavior, collusion, unauthorized transactions, control circumvention, or deliberate manipulation.
-
Analyze unusual transaction sequences, repeated overrides, suspicious timing, abnormal user activity, and atypical process paths.
-
Combine process mining with transaction analytics, master data, relationship analysis, and other evidence to support fraud risk assessment.
-
Establish investigation procedures that distinguish suspicious process behavior from legitimate exceptions and data-quality problems.
Module 12: Data Quality, Governance and Technology Controls
-
Assess data completeness, accuracy, lineage, transformation rules, interfaces, timestamps, master data, and system dependencies affecting process mining.
-
Evaluate ERP configurations, workflow engines, APIs, system integrations, access controls, logging, and audit trails supporting process analysis.
-
Identify privacy, confidentiality, security, retention, and access risks associated with large-scale financial process data.
-
Develop governance procedures for dataset approval, analytical reproducibility, data validation, documentation, and controlled use of process mining outputs.
Module 13: Process Mining for Continuous Auditing and Monitoring
-
Design continuous monitoring routines that automatically identify financial process deviations, control failures, and emerging transaction risks.
-
Establish risk thresholds, exception categories, alert mechanisms, investigation workflows, and management escalation procedures.
-
Integrate process mining outputs into internal audit planning, control monitoring, issue management, and audit follow-up processes.
-
Develop dashboards that provide timely visibility into process compliance, exception volumes, financial exposure, bottlenecks, and remediation status.
Module 14: Process Mining, Internal Audit Evidence and Reporting
-
Determine how process mining results can support audit evidence while maintaining appropriate validation, corroboration, documentation, and professional skepticism.
-
Translate analytical observations into clear audit findings describing criteria, condition, cause, consequence, risk, and recommended corrective action.
-
Quantify financial exposure, transaction populations, control exceptions, processing delays, and recurring deviations where reliable data supports measurement.
-
Communicate process mining insights effectively to audit committees, senior management, finance leaders, process owners, and control functions.
Module 15: Emerging Process Mining Technologies and Advanced Assurance
-
Examine the use of artificial intelligence, machine learning, predictive analytics, generative AI, and intelligent automation alongside process mining.
-
Evaluate emerging risks involving automated workflows, digital finance platforms, robotic process automation, cloud ERP systems, and complex system integrations.
-
Explore predictive process monitoring approaches that identify transactions or process paths likely to result in future control failures or delays.
-
Develop advanced assurance strategies combining process mining, continuous auditing, AI analytics, control monitoring, and human professional judgment.
Module 16: Integrated Process Mining for Finance and Internal Audit Case Study
-
Conduct an end-to-end process mining engagement using realistic financial transaction data across multiple finance processes and control environments.
-
Build event logs, reconstruct actual process flows, identify variants, perform conformance testing, and analyze performance and control deviations.
-
Investigate significant exceptions and connect process mining findings with transaction evidence, financial exposure, root causes, and control deficiencies.
-
Prepare an integrated internal audit report and management dashboard demonstrating process insights, audit conclusions, remediation priorities, and continuous monitoring opportunities.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
