Hi, 
Risk Modeling and Fraud Detection with AI
Course
Risk Modeling and Fraud Detection with AI
Apply generative AI to strengthen risk monitoring, fraud triage, AML investigations, and regulatory change tracking. Build the skills that modern risk, fraud, and compliance teams need to stay ahead. No coding required.
Flexible Schedule
Intermediate Level
Mentor Support
Estimated Time
30 hours
Risk and fraud teams today must analyze growing volumes of transaction data, surveillance alerts, and regulatory updates while maintaining strict governance and oversight. The Risk Modeling & Fraud Detection with AI course explores how generative AI can support modern risk monitoring, fraud detection, and compliance workflows, helping financial professionals analyze complex information more efficiently while maintaining strong human oversight and control.
In this course, youll learn how AI can support credit, market, and operational risk monitoring by helping teams analyse risk reports, interpret model outputs, and generate plain-language explanations of complex risk metrics and stress-test results. Youll also explore how AI can assist with operational risk monitoring, vendor and counterparty surveillance, and liquidity risk analysis by synthesising insights from structured data, disclosures, and market information.
As you progress, the course introduces AI-assisted workflows for fraud detection and financial crime surveillance, including fraud alert triage, transaction monitoring analysis, AML case support, communications surveillance, sanctions screening, and KYC documentation review. The course also examines how AI can help risk teams track regulatory updates and assess the impact of new rules on internal policies and controls.
Advanced modules focus on governance and oversight in AI-assisted risk functions, including validating AI outputs, maintaining human-in-the-loop review processes, and aligning AI-assisted workflows with regulatory and model risk management expectations.
By the end of the course, youll be able to apply generative AI across risk monitoring, fraud detection, financial crime surveillance, and regulatory analysis workflows while maintaining strong governance controls and documented review practices.
This course comprises 15 purposely designed modules that take you on a carefully defined learning journey.
Our proven learning methodology combines self-paced learning and mentor-supported hands-on practice to help you build the deep technical and practical understanding today's employers are looking for.
You will get the opportunity to earn recognized certifications, which will help your resume and LinkedIn profile stand out.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs, and online exam questions.
As part of our mentoring service, you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.
Once you have successfully completed the course, you will earn your Certificate of Completion.
By the end of this course, you will be able to:
- Use AI tools for credit, market, and operational risk monitoring.
- Apply AI in fraud detection, AML surveillance, and KYC workflows.
- Interpret quantitative risk models using AI-generated narratives.
- Build no-code AI-assisted compliance and surveillance workflows.
- Draft regulatory summaries, SARs, and risk reports using AI.
- Apply AI governance, validation, and model risk management practices.
- Senior Analysts
- Risk Managers
- Quantitative Strategists
- Fraud Operations Professionals
- AML Analysts
- Model Risk Officers
- Compliance Specialists
- Treasury Analyst
- Operational Risk Manager
- Completion of the AI-Powered Financial Analysis course
- Familiarity with risk, fraud, or compliance workflows
- No coding or technical background required
Course Outline
Reading: Course Overview
Reading: How to Make the Most of This Course
Reading: What You’ll Explore: Credit, Market, and Operational Risk
Grading Scheme
Reading: AI-Assisted Credit Memo Comparison Workflow
Video: Summarizing and Comparing Credit Memos with AI
Reading: Analyzing Management Tone for Early Risk Signals
Activity: Spot the Early Warning Sign
Reading: Building Prompts and Escalation Logic for Stress Testing
Practice Lab: Building Prompts and Escalation Logic for Stress Testing
Practice Quiz: AI in Credit and Market Risk Monitoring
Reading: Designing Trigger Criteria for a Credit Watchlist
Practice Lab: Designing Trigger Criteria for a Credit Watchlist
Reading: Mapping AI Support Against Human Escalation Points
Graded Lab: Mapping AI Support Against Human Escalation Points
Graded Quiz: AI in Credit and Market Risk Monitoring
Reading: Converting Model Outputs into Executive-Ready Summaries
Video: Converting Model Outputs into Executive-Ready Summaries
Reading: Communicating VaR and Scenario Outputs to Stakeholders
Practice Lab: Translating VaR and Scenario Results into Visual Narratives
Video: Documenting Model Assumptions and Limitations with AI
Activity: Build a Mini Model Card
Practice Quiz: Quantitative Risk Model Interpretation with AI
Reading: Spotting Conflicting Claims in Validation Reports
Graded Lab: Spotting Conflicting Claims in Validation Reports
Reading: Applying SR 11-7 to AI-Assisted Modeling
Graded Quiz: Quantitative Risk Model Interpretation with AI
Reading: Monitoring Real-Time Event Feeds for Operational Risk
Reading: Organizing Incident Timelines into Post-Mortem Narratives
Activity: Draft a Post-Mortem Snapshot
Reading: Surfacing Root-Cause Patterns Across Incident Libraries
Graded Lab: Surfacing Root-Cause Patterns Across Incident Libraries
Practice Quiz: Operational Risk and Incident Management
Reading: Structuring Operational Loss Data into Risk Narratives
Video: From Loss Data to Risk Committee Narratives
Reading: Building No-Code Dashboards for Operational Risk Reporting
Graded Quiz: Operational Risk and Incident Management
Reading: Extracting Key Risk Indicators from Vendor Documents
Practice Lab: Extracting Key Risk Indicators from Vendor Documents
Reading: Tracking Counterparty Risk Across News and Filings
Activity: Spot the Emerging Risk Signal
Video: Generating Executive-Ready Concentration Risk Narratives
Practice Lab: Generating Executive-Ready Concentration Risk Narratives
Practice Quiz: Third-Party and Concentration Risk Surveillance
Reading: Improving Consistency in Regulatory Risk Reporting
Reading: Designing a Reusable Prompt Library for Surveillance
Graded Lab: Designing a Reusable Prompt Library for Surveillance
Graded Quiz: Third-Party and Concentration Risk Surveillance
Reading: Translating Treasury and ALM Data into Executive Liquidity Narratives
Practice Lab: Generating Liquidity Narratives from Treasury and ALM Data
Reading: Structuring ILAAP and ICAAP Sections with AI
Practice Lab: Transforming Structured Inputs into ILAAP and ICAAP Sections
Reading: Breaking Down LCR and NSFR for Non-Technical Audiences
Video: Decoding LCR and NSFR for Boards and Executives
Activity: Translate the Liquidity Metric
Practice Quiz: Liquidity and Balance Sheet Risk with AI
Reading: Translating Rate and Funding Scenarios into ALCO Commentary
Reading: Validating and Refining AI-Generated Liquidity Narratives
Graded Lab: Validating and Refining AI-Generated Liquidity Narratives
Graded Quiz: Liquidity and Balance Sheet Risk with AI
Reading: What You've Achieved
Reading: What You’ll Explore: Fraud Detection and Financial Crime
Video: Accelerating Large-Scale Exception Review with AI
Reading: Clustering Fraud Alert Patterns into Escalation Summaries
Practice Lab: Clustering Fraud Alert Patterns into Escalation Summaries
Reading: Turning Fraud Indicators into Escalation-Ready Explanations
Video: Translating Fraud Indicators for Escalation Teams
Practice Quiz: Fraud Pattern Recognition and Alert Triage
Reading: Prioritizing and Escalating High-Volume Fraud Alerts
Reading: Mapping Fraud Workflows to AI and Investigator Roles
Graded Lab: Mapping Fraud Workflows to AI and Investigator Roles
Graded Quiz: Fraud Pattern Recognition and Alert Triage
Reading: Prioritizing and Summarizing Flagged Monitoring Alerts
Practice Lab: Prioritizing and Summarizing Flagged Monitoring Alerts
Video: AI Narratives on Placement, Layering, and Integration Patterns
Reading: Turning AML Case Data into SAR Narratives
Graded Lab: Transforming AML Case Data into SAR Narratives
Practice Quiz: AML and Transaction Monitoring Surveillance
Reading: Minimizing Sensitive Data Exposure in AML Prompts
Activity: Redact Before You Prompt
Reading: Documenting Traceability for AI-Assisted AML Decisions
Graded Quiz: AML and Transaction Monitoring Surveillance (10 questions /
Reading: Spotting Conduct Risk Language in Flagged Communications
Reading: Detecting Manipulation Signals in Trading and Communications Data
Practice Lab: Detecting Manipulation Signals in Trading and Communications Data
Reading: Categorizing and Prioritizing the Surveillance Queue
Graded Lab: Categorizing and Prioritizing the Surveillance Queue
Practice Quiz: Communications Surveillance and Conduct Risk
Reading: Protecting Sensitive Data in Surveillance Review
Activity: Privacy Check Before Submission
Video: Setting Investigator Oversight Standards for Surveillance
Graded Quiz: Communications Surveillance and Conduct Risk
Reading: Extracting Customer Risk Information from KYC Files
Reading: Turning Customer Risk Data into EDD Narratives
Practice Lab: Transforming Customer Risk Data into EDD Narratives
Reading: Drafting Consistent Sanctions Escalation Notes
Video: Sanctions Match Rationale Walkthrough
Activity: Explain the Match
Practice Quiz: Sanctions Screening and KYC Support with AI
Reading: Designing a Reusable Prompt Library for KYC Review
Graded Lab: Designing and Testing a KYC and Sanctions Prompt Set
Reading: Setting Reviewer Accountability Standards for AI-Assisted KYC
Graded Quiz: Sanctions Screening and KYC Support with AI
Reading: Summarizing Regulatory Publications into Compliance Briefings
Practice Lab: Summarizing Regulatory Publications into Compliance
Reading: Spotting Language and Obligation Changes Across Rule Versions
Video: Side-by-Side Regulatory Rule Comparison Demo
Activity: Spot What Changed
Reading: Generating Impact Assessment Summaries from New Regulations
Practice Lab: Generating Impact Assessment Summaries from New
Practice Quiz: Regulatory Change Management for Risk Teams
Reading: Tracking DORA, Basel IV, and AML Developments with AI
Reading: Configuring a No-Code Regulatory Monitoring Pipeline
Graded Lab: Configuring a No-Code Regulatory Monitoring Pipeline (25
Graded Quiz: Regulatory Change Management for Risk Teams
Reading: What You've Achieved
Reading: What You’ll Explore: AI Governance and Risk Capstone
Reading: Classifying AI Output as Advisory or Decision-Driving
Video: Advisory vs. Decision-Driving AI in Practice
Activity: Advisory or Decision-Driving
Reading: Building Traceable Evidence Files for AI-Assisted Activities
Practice Lab: Creating Audit-Ready Evidence Files for AI-Assisted Activities
Reading: Sorting AI Tools into Low-, Medium-, and High-Risk Tiers
Practice Quiz: AI Governance in Risk and Fraud Functions
Reading: Assigning AI Oversight Across the Three Lines of Defense
Reading: Drawing the Line Between AI Support and Human Judgment
Graded Lab: Building the Human-AI Responsibility Matrix
Graded Quiz: AI Governance in Risk and Fraud Functions
Reading: Placing Review Checkpoints in AI-Assisted Risk Workflows
Video: Human-in-the-Loop Checkpoints Walkthrough
Activity: Human-in-the-Loop Spot Check
Reading: Comparing AI Narratives Against Source Data and Models
Practice Lab: Validating AI Narratives Against Source Datasets
Reading: Detecting Hallucinations in Credit, Market, and Fraud Analysis
Practice Lab: Identifying Hallucinations in AI-Generated Risk Analyses
Practice Quiz: Validating AI Outputs in Risk Workflows
Video: Setting Validation Standards for AI-Generated Content
Graded Lab: Designing and Testing a Quality Review Rubric
Reading: Setting Materiality Thresholds for Senior Officer Escalation
Graded Lab: Evaluating AI Outputs for Escalation
Graded Quiz: Validating AI Outputs in Risk Workflows
Reading: Classifying AI-Assisted Workflows Under SR 26-2
Activity: Classifying Systems Under SR 26-2
Video: Distinguishing Governed Models from Operational Tools
Practice Lab: Evaluating Use Cases for Model vs. Tool Classification
Reading: Setting Inventory and Challenge Process Standards for AI
Practice Lab: Creating an AI Tool Inventory with Risk Classifications
Practice Quiz: Model Risk Management in AI-Enabled Risk Functions: SR 11-7 to SR 26-2
Video: Avoiding New Model Risk When Drafting with AI
Practice Lab: Drafting and Correcting AI-Assisted Model Risk
Reading: Building an Audit-Ready AI Model Risk Record
Graded Lab: Building a Defensible Model Risk Record for a Global Bank
Graded Quiz: Model Risk Management in AI-Enabled Risk Functions: SR 11-7 to SR 26-2
Reading: Automating Regulatory Updates with a No-Code Automation Platform
Video: No-Code Regulatory Workflow Demo
Activity: Highlight the Evidence
Reading: Building a Secure No-Code Policy Q&A Assistant
Practice Lab: Configuring a No-Code Policy Q&A Assistant
Reading: Improving Consistency in Compliance Exception Queues
Practice Lab: Configuring an AI-Assisted Compliance Exception Workflow
Practice Quiz: Building No-Code Risk Monitoring Workflows
Reading: Securing No-Code Integrations to Internal Data Sources
Graded Lab: Connecting Internal Data Sources via Point-and-Click Integrations
Reading: Establishing Traceable Records for AI Risk Processes
Graded Quiz: Building No-Code Risk Monitoring Workflows
Reading: About the Project
Reading: Preparing for the Project
Choosing Your Workflow Track
Applying the Design Brief — A Worked Example
Handout: Credit & Market Risk Monitoring — Marrowgate Capital
Handout: Operational, Third-Party & Liquidity Risk — Cindervale Regional Bank
Handout: Fraud & AML Investigation — Coldharbor Payments Group
Handout: Conduct, Sanctions & KYC Compliance — Wrenfield & Thistlewood Wealth Advisors
Final Project: Design Your AI-Augmented Risk Monitoring Workflow
Final Exam: Risk Modeling and Fraud Detection
Reading: What You've Achieved
How to access your course completion certificate and Credly Badge
Obtaining your ACE Transcripts
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
This course is ideal for finance professionals, risk analysts, auditors, compliance teams, and learners who want to understand how AI is transforming fraud detection, risk assessment, and decision-making across modern financial institutions with practical skills for long-term career growth.
In this course, you will learn how fraud detection with AI works alongside risk assessment techniques. You will also learn to identify suspicious activities, strengthen controls, and make more informed decisions using practical AI-powered tools and real-world financial scenarios across diverse financial services environments.
No. The course starts with the fundamentals before introducing advanced concepts, making it suitable for beginners as well as experienced finance professionals. This course is a perfect starting point to expand their AI knowledge through easy-to-follow lessons and practical learning exercises.
In this course, you will explore financial risk modeling methods to evaluate potential threats, assess exposure, and improve decision-making. You will learn using AI-driven insights for more accurate and proactive risk management across lending, investments, and financial operations.
Absolutely! The course introduces practical AI applications designed for compliance professionals. It helps you strengthen regulatory monitoring, improve reporting accuracy, and identify potential compliance risks more efficiently while supporting the evolving regulatory requirements.
Yes. You will gain practical knowledge of credit risk analysis using AI models to evaluate borrower profiles, detect warning signs, and support smarter lending decisions with greater confidence using data-driven insights and predictive risk evaluation.
Yes. This course will help you understand how to prevent financial fraud. You'll learn modern strategies for financial fraud prevention. You'll also explore how AI identifies unusual transaction patterns and reduces false positives. Along the way, you'll see how it supports faster investigation of potential fraud cases, before they turn into costly losses that damage market reputation.
Yes. You work through practical case studies and industry scenarios to understand how AI is applied across banking, insurance, lending, and financial services. It also gives detailed insights to solve real business challenges with greater confidence and practical understanding.
Yes. The course introduces AI-powered techniques for market risk monitoring, enabling learners to track market trends, identify emerging risks, and respond quickly to changing financial conditions using intelligent analytics and predictive financial insights.
This fraud analytics course carefully combines AI concepts with practical business applications. It also serves as valuable fraud detection training, helping learners build skills that align with today's evolving financial risks and increasing demand for AI-powered finance professionals.
Type of certificate
Certificate of Completion
About this course
15 Modules
06 Skills
Includes
Discussion Space
36 Hands-on Labs
75 Instructional Readings
10 Videos
14 Interactive Activities
14 Practice Quizzes
14 Graded Quizzes
01 Final Project
01 Final exam
Create
AI-assisted fraud triage workflows
SARs and regulatory summaries
Governance and validation frameworks
No-code compliance monitoring workflows
AI-augmented risk monitoring playbooks (Capstone)
Exercises to explore
Credit and market risk analysis using AI
Quantitative risk model interpretation and stakeholder communication
Operational risk and incident review
Third-party and concentration risk surveillance
Fraud alert and AML transaction analysis
Communications surveillance and conduct risk analysis
KYC and sanctions screening review
Regulatory change monitoring and compliance analysis
This course has been created by
Newsletters & Updates
Subscribe to get the latest tech career trends, guidance, and tips in your inbox.