AI5 ACADEMY · APPLIED AI FINANCE LABS · UPDATED SEPTEMBER 2026
AI for AML, KYC & Financial Crime Investigation Course
Who should join: AML and KYC analysts · Fraud and financial-crime investigators · Banking, fintech, risk and compliance teams
8 weeks · Online + Offline · 7 practical projects
Tools: ChatGPT · NotebookLM · Microsoft Excel · Power BI · Neo4j · Google Colab / Python
Build: AI-Assisted KYC & Customer Risk Assessment · Transaction Anomaly Detection Exercise
Want syllabus, fees and batch timing?
Talk to AI5 Academy counsellor and get course details based on your background.
APPLIED AI FOR MODERN AML, KYC & FINANCIAL-CRIME INVESTIGATION
Learn how Generative AI, Machine Learning, anomaly detection, network analysis, RAG and AI-assisted investigation workflows are applied to KYC, transaction monitoring and financial-crime operations.
Online + Offline3 sessions per week60–90 minutes per sessionAI + domain practice
What You Will Actually Do
Learn by Doing → Build → Check → Improve → Apply
Approximately 20% concepts and 80% practical application across the program. This is a teaching direction, not a fixed split for each class.
- AI-Assisted KYC & Customer Risk Assessment
- Transaction Anomaly Detection Exercise
- AI-Assisted Financial Crime Investigation
- Entity & Suspicious Network Investigation
- AML Regulatory RAG/Knowledge Assistant
- Alert-to-STR/SAR Investigation Workflow
- End-to-End Financial Crime Investigation Capstone
8 weeks · 24 live sessions · approximately 24–36 instructor-led hours. Three sessions per week, generally 60–90 minutes each. Assignments, practice and portfolio work outside class are additional.
India and international Live Online learners can request a suitable cohort. Confirm local times and time-zone differences before enrolment.
Every finance lab includes a review.
Concept → Demonstration → Guided Lab → Independent Task → Verification → Professional Output.
Start with a realistic problem and source material. Watch the trainer perform the workflow, build it yourself, check the result, improve it and submit a usable workbook, report or investigation record.
Source & retrieveAnalyse & calculateCite & reconcileVerifyHuman review & approve
Verification exercises include invented numbers, incorrect calculations, broken formulas, unsupported assumptions, stale market information, wrong citations, incomplete or conflicting documents, missing data, outliers and misleading summaries. Keep a record of the error, correction and reviewer decision.
NEXT START OPTIONS
Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Applied AI training for modern AML, KYC and financial-crime investigation. Learn how Generative AI, Machine Learning, anomaly detection, entity and network analysis, RAG and supervised agentic workflows support practical compliance work without turning the programme into a coding-heavy data science course.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
AML Analytics SpecialistKYC Risk AnalystFinancial Crime InvestigatorRegTech Operations Associate
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You work in or want to enter AML, KYC, compliance or financial-crime operations
You want applied AI methods for investigation rather than a generic AML certification
You want practical AI workflows without an advanced-coding requirement
YOUR LEARNING ARC
From guided foundation to finished work.
Foundations
Map AML/KYC work and safe AI-assistance boundaries.
Investigation
Apply AI, ML and LLM methods to customer and transaction risk.
Grounding
Use entity networks and approved regulatory sources.
Capstone
Complete a governed alert-to-STR/SAR case.
INDUSTRY TASKS
Practise the work, not only the tool.
- Assess a synthetic customer and document risk
- Prioritise suspicious transaction signals
- Investigate entities, networks and adverse media
- Prepare a reviewed investigation summary and draft STR/SAR
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
TRAIN A PROFESSIONAL TEAM
Run this programme around your tools and operating controls.
Private weekday, weekend and fast-track formats are available for organisations.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Assess KYC and customer risk with AI assistance
A source-checked customer-risk assessment with documented human review.
02
Analyse suspicious activity and connected entities
A transaction anomaly exercise and Neo4j network investigation using synthetic data.
03
Build grounded compliance research
A cited AML/KYC knowledge assistant based on approved documents.
04
Complete a governed financial-crime investigation
An end-to-end case file, draft STR/SAR and AI-governance checklist.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
8 learning modules
Progress from AML/KYC foundations to customer risk, transaction monitoring, AI-assisted investigation, grounded regulatory research and a governed alert-to-STR/SAR capstone.
Week 1 — AML, KYC & AI Foundations
Map the investigation lifecycle and decide where AI may assist under human control.
CORE TOPICS
- AML, KYC, CDD and EDD workflows
- Transaction monitoring, alert investigation and STR/SAR lifecycle
- Rules-based systems, Machine Learning and anomaly detection
- Generative AI, LLMs, agents and automated workflows
- Human-in-the-loop decisions, privacy and safe AI use
GUIDED PRACTICE
Map an existing AML investigation workflow and identify suitable AI-assisted tasks. Record approved sources, permissions and human escalation boundaries.
MODULE DELIVERABLE
AI opportunity and control map
Week 2 — AI for KYC, CDD, EDD & Customer Risk
Use AI to structure customer research while verifying every material claim.
CORE TOPICS
- Customer profiling and KYC document review
- Information extraction from customer documents
- Beneficial ownership and UBO research
- PEP, sanctions and adverse-media concepts
- Risk classification, EDD summaries and hallucination control
GUIDED PRACTICE
Create an AI-assisted KYC and customer-risk assessment for a synthetic customer. Check missing documents, conflicting identities and unsupported adverse-media claims.
MODULE DELIVERABLE
AI-assisted KYC & customer risk assessment
Week 3 — AI & Machine Learning for Transaction Monitoring
Understand practical ML methods used to detect and prioritise suspicious activity.
CORE TOPICS
- Classification, clustering and outlier detection
- Anomaly detection, risk scoring and behaviour patterns
- Thresholds, precision and recall in AML
- False positives and alert prioritisation
- Rules versus AI monitoring; optional Colab/Python demonstration
GUIDED PRACTICE
Analyse a synthetic transaction dataset and identify suspicious or anomalous activity. Measure false positives and false negatives on labelled cases; record missed alerts and escalation decisions.
MODULE DELIVERABLE
Transaction anomaly detection exercise
Week 4 — Generative AI & LLMs for Financial Crime Investigation
Use leading LLMs to plan and document a source-led case investigation.
CORE TOPICS
- ChatGPT for AML investigations
- Claude and Gemini for document and case analysis
- AML/KYC prompt design and investigation questions
- Fact extraction, comparison, case summaries and adverse-media research
- Evidence-based responses, hallucination checks and sensitive-data controls
GUIDED PRACTICE
Conduct an AI-assisted investigation of a simulated financial-crime case. Check citations, dates, evidence completeness and hallucinated case facts.
MODULE DELIVERABLE
AI-assisted financial-crime investigation
Week 5 — Entity Resolution, Network Analysis & Hidden Relationships
Connect people, companies, accounts and counterparties to reveal suspicious patterns.
CORE TOPICS
- Entity resolution and customer/company matching
- Beneficial ownership and account connections
- Network and graph concepts
- Mule accounts, circular transactions and hidden relationships
- Neo4j and visual investigation of connected entities
GUIDED PRACTICE
Create and investigate a financial-crime relationship network using synthetic data. Test false entity matches and missed links before accepting a network conclusion.
MODULE DELIVERABLE
Entity & suspicious network investigation
Week 6 — RAG & AI Knowledge Systems for AML Compliance
Build a grounded compliance assistant based on approved public sources.
CORE TOPICS
- What RAG is and why grounding matters
- AML/KYC policy and regulatory-document research
- Approved sources and internal policy assistants
- Citations, verification and source control
- NotebookLM and general-versus-grounded LLM answers
GUIDED PRACTICE
Create an AML/KYC regulatory knowledge assistant using public documents and NotebookLM or a similar grounded workflow. Test stale policies, unsupported questions and incorrect citations; retain retrieval evidence.
MODULE DELIVERABLE
AML regulatory RAG/knowledge assistant
Week 7 — AI-Assisted Investigation, STR/SAR & AI Governance
Take an alert through evidence review and controlled regulatory reporting.
CORE TOPICS
- Alert workflow, evidence collection and chronology
- Case disposition and investigation summaries
- STR/SAR drafting assistance, QA and human approval
- Explainable AI, bias and output validation
- Governance, audit trails and human-in-the-loop controls
GUIDED PRACTICE
Take a simulated alert from investigation through case summary and draft STR/SAR. Review STR/SAR drafts against case evidence and local process requirements; only an authorised human can approve or submit.
MODULE DELIVERABLE
Alert-to-STR/SAR investigation workflow
Week 8 — Agentic AML Workflows & Capstone
Coordinate an end-to-end supervised investigation without making automation the course focus.
CORE TOPICS
- KYC data, customer risk and screening
- Adverse media, transaction analysis and anomaly review
- Evidence compilation and investigation summary
- Simple n8n or similar workflow demonstration
- Human approval and AI-governance checklist
GUIDED PRACTICE
Complete a simulated case covering customer risk, transactions, network links, research, chronology, evidence, case decision and draft STR/SAR. Keep action logs, evidence references, explainable risk scores and reviewer decisions. Test agent failure and escalation.
MODULE DELIVERABLE
End-to-end financial-crime investigation capstone
Want syllabus, fees and batch timing?
Talk to AI5 Academy counsellor and get course details based on your background.
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
AI-Assisted KYC & Customer Risk Assessment
Plan, produce, test and present a finished piece with trainer feedback.
Transaction Anomaly Detection Exercise
Plan, produce, test and present a finished piece with trainer feedback.
AI-Assisted Financial Crime Investigation
Plan, produce, test and present a finished piece with trainer feedback.
Entity & Suspicious Network Investigation
Plan, produce, test and present a finished piece with trainer feedback.
AML Regulatory RAG/Knowledge Assistant
Plan, produce, test and present a finished piece with trainer feedback.
Alert-to-STR/SAR Investigation Workflow
Plan, produce, test and present a finished piece with trainer feedback.
End-to-End Financial Crime Investigation Capstone
Plan, produce, test and present a finished piece with trainer feedback.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
Core hands-on tools
ChatGPTNotebookLMMicrosoft ExcelPower BINeo4jGoogle Colab / Python
Python is optional technical exposure, not a prerequisite. It is used only where it helps explain practical AI and Machine Learning methods.Additional AI & industry exposure
ClaudeGeminiPerplexityNICE ActimizeSAS AMLn8n
NICE Actimize and SAS AML are presented as industry AML platform exposure. Licensed hands-on access is included only when specifically confirmed for a batch.COMMON QUESTIONS
Before you apply
Is this an AI for AML course or a general AML certification?
It is applied AI training for AML, KYC and financial-crime work. It covers AI-assisted customer risk, transaction monitoring, investigation, regulatory research and governed reporting; it does not replace a statutory or employer-required AML certification.
＋Do I need AML/KYC or Machine Learning experience?
No prior AI or Machine Learning experience is required. AML/KYC knowledge is helpful but not mandatory, and the course begins with the operating foundations.
＋Is Python required?
No advanced coding is required. Google Colab and Python appear only as optional technical demonstrations where they help explain practical AI and Machine Learning methods.
＋Will I receive licensed NICE Actimize or SAS AML access?
NICE Actimize and SAS AML are included as industry AML platform exposure. Licensed hands-on access is not promised unless it is specifically confirmed for a batch.
＋What practical work will I complete?
You will complete six guided builds covering KYC risk, transaction anomalies, investigation, entity networks, regulatory RAG and alert-to-STR/SAR work, followed by a separate end-to-end capstone.
＋Can a bank, fintech or compliance team request a private batch?
Yes. Private training can be aligned to approved policies, role levels and tools while keeping confidential data outside open classroom exercises.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are trainer-led in the classroom or live online.Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Ask admissions to confirm the completion document and assessment requirements for your cohort. No external professional certification is implied.
＋Can working professionals join?
Yes. Three live sessions per week, generally 60–90 minutes each. Confirm a suitable cohort and time zone before joining.
＋Tools follow the work.
| Workflow | Tools and materials | Access |
|---|---|---|
| AI and spreadsheets | ChatGPT, Claude, Gemini, Microsoft Copilot; Excel and Google Sheets. ChatGPT for Excel or Google Sheets where enabled. | Use the cohort’s approved assistant and spreadsheet environment. Paid accounts and usage limits are confirmed before enrolment. |
| Repeatable workflows | ChatGPT Work or equivalent approved agentic workflows, apps/connectors, n8n, Make and APIs. | No-code/low-code builds with approval gates. Paid connectors, API credits and enterprise systems depend on confirmed access; equivalent dataset-based exercises support the learning goal. |
Use public, synthetic or approved sanitised data. Never upload confidential client information without permission. Product references do not imply partnerships.
Assessment through professional work
Assessment centres on lab completion, workflow assignments, model or case review, research outputs, verification exercises and the final capstone. Short quizzes support practice. Submit source references, an assumptions review, calculation and formula checks, citation and freshness checks, and a human approval record with every major output.
Combine the weekly outputs into a source-backed financial-crime case file, investigation workflow and reviewed STR/SAR draft. Explain the process and demonstrate how it behaves when inputs are incomplete or AI is wrong.
These outputs provide portfolio evidence of practical learning. The course does not replace CA, CFA, MBA or regulated qualifications and does not provide investment advice or guarantee employment, accuracy, compliance or investment returns.
Learn with domain specialists who use AI in their work.
AI5’s trainer standard combines relevant professional practice, strong current AI usage and the ability to teach live practical workflows. Finance, accounting, audit, FP&A, research, modelling or AML experience must match the subject taught.
Trainer selection requires a live workflow demonstration, error checking and clear answers to domain questions. Sessions call for active builds, learner coaching and project review. Ask admissions for the assigned trainer’s background before joining.
Training for corporate teams
Finance departments, accounting, FP&A, internal audit, banks, NBFCs, fintech, investment, asset-management and compliance teams can request a program built around their responsibilities. Organisation-specific workflows use approved datasets subject to privacy and security rules. Duration, scope and pricing are agreed separately.
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NEXT BATCH
Choose your course.
Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.
COURSE PLANNING
AI for AML, KYC & Financial Crime Investigation Course: syllabus, projects and admission details
Learn how Generative AI, Machine Learning, anomaly detection, network analysis, RAG and AI-assisted investigation workflows are applied to KYC, transaction monitoring and financial-crime operations.
AI for AML, KYC & Financial Crime Investigation Course syllabus
AML, KYC & AI Foundations, AI for KYC, CDD, EDD & Customer Risk, AI & Machine Learning for Transaction Monitoring. Read the full curriculum above for the complete learning sequence.
AI for AML, KYC & Financial Crime Investigation Course projects
AI-Assisted KYC & Customer Risk Assessment; Transaction Anomaly Detection Exercise; AI-Assisted Financial Crime Investigation. Check the project section for the work expected in this program.
AI for AML, KYC & Financial Crime Investigation Course eligibility
Entry level: Beginner to Intermediate. Ask a counsellor to confirm whether your background meets the program prerequisites.
AI for AML, KYC & Financial Crime Investigation Course duration
Program duration: 8 weeks. Confirm the next batch timetable before joining.
AI for AML, KYC & Financial Crime Investigation Course tools
ChatGPT, NotebookLM, Microsoft Excel, Power BI, Neo4j, Google Colab / Python. Tool access and any paid accounts should be confirmed for your cohort.
AI for AML, KYC & Financial Crime Investigation Course fees and batches
Training mode: Online + Offline. Request current fees, available batches and a suitable schedule.
Get course details →