Fraud analytics toolbox
Practical tools for banking fraud, AI risk, payment scams, and financial-crime analytics.
Use this page as a working library for checklists, signal maps, KPI ideas, dashboards, investigation workflows, and architecture references. Every resource points readers toward a practical next step rather than a chronological article feed.
Resource cards
Choose the tool that matches the fraud problem you are working on.
APP Fraud Risk Signal Checklist
A field-style checklist for sender behavior, recipient and mule account risk, scam story cues, payment journey controls, and case intake questions.
Who it is for: Fraud analysts, payment-risk teams, branch/call-center escalation teams, and scam operations leaders.
Fraud Analytics KPI Checklist
A KPI planning guide for loss, alerts, detection quality, false positives, case workflow, recovery, customer friction, and model governance.
Who it is for: Fraud analytics teams, risk reporting owners, dashboard builders, and managers setting operating metrics.
Money Mule Detection Guide
A practical guide to mule-account indicators across onboarding, dormancy, transaction velocity, recipient networks, rapid funds-out movement, and graph analytics.
Who it is for: Payment fraud teams, AML partners, transaction monitoring analysts, scam operations leaders, and account-risk investigators.
FedNow Fraud Controls Matrix
A control-mapping reference for instant payment risk, including sender friction, receiver intelligence, account thresholds, escalation, and review timing.
Who it is for: Instant-payment teams, fraud strategy groups, bank risk leaders, and operational control owners.
AI-Generated Identity Fraud Guide
A practical identity-risk guide for deepfake IDs, synthetic documents, liveness checks, digital onboarding controls, KYC lifecycle monitoring, and mule-account links.
Who it is for: Digital onboarding teams, KYC owners, fraud strategy groups, identity risk analysts, and financial crime leaders.
AI Fraud Governance Checklist
A governance checklist for explainability, model monitoring, human review, documentation, bias checks, alert quality, and safe AI-assisted investigation.
Who it is for: AI risk teams, fraud model owners, analytics leaders, compliance partners, and investigation workflow designers.
Scam Intake Questions Template
A practical question framework for identifying coercion, urgency, relationship claims, investment narratives, remote-access pressure, and payment journey clues.
Who it is for: Call-center teams, fraud intake specialists, branch teams, investigators, and customer-protection programs.
Account Takeover Signal Checklist
A signal checklist for suspicious login behavior, device shifts, profile changes, credential abuse, payment initiation, and graph-based relationship patterns.
Who it is for: Digital banking fraud teams, cybersecurity partners, graph analytics teams, and account security investigators.
Fraud Analyst SQL Starter Pack
A starter path for common analyst queries: alert volume, case aging, transaction velocity, customer/device pivots, losses, recoveries, and false positives.
Who it is for: Fraud analysts, BI developers, junior analytics hires, and teams standardizing investigation datasets.
Fraud Dashboard KPI Template
A dashboard planning reference for executive, operations, model monitoring, and investigator views of fraud performance.
Who it is for: Fraud reporting owners, analytics managers, BI teams, and risk leaders who need a cleaner metric hierarchy.
Real-Time Fraud Detection Architecture Diagram
A reference architecture path for streaming events, feature pipelines, decisioning, case queues, feedback loops, and human review.
Who it is for: Data engineers, fraud platform owners, architects, analytics leaders, and real-time decisioning teams.
Identity Fraud Guide Set
A reader path for synthetic identity, account takeover, first-party fraud, and graph-based account risk.
Who it is for: Digital banking fraud teams, identity risk analysts, account security teams, and financial-crime analytics groups.
AI Voice Cloning Scam Guide
A guide path for synthetic voice scams, customer pressure tactics, AI-enabled deception, and fraud review escalation.
Who it is for: Scam operations teams, customer-protection groups, AI risk teams, and fraud analysts reviewing social engineering cases.
Reader paths
Fraud KRI Toolkit
Key risk indicator guides for banking fraud teams.
Start with the hub, then use the four focused guides to build fraud KRI dashboards, thresholds, escalation paths, model monitoring routines, and executive reporting.
Fraud KRIs in Banking Hub
Operations, exposure, model controls, and governance in one framework.
Operational Fraud KRIs
Backlogs, SLAs, queues, staffing, QA, handoffs, and control pressure.
Fraud Risk KRIs
Scams, mule risk, ATO, synthetic identity, ACH, instant payments, and exposure signals.
Fraud Model KRIs
Drift, false positives, alert quality, rules, labels, warnings, and AI-assisted controls.
Fraud KRI Governance
Risk appetite, ownership, thresholds, escalation, remediation, and executive reporting.
Need a starting point?
Start with the live checklist if you are working on APP fraud, use the topic hubs if you are researching a broader problem, or subscribe for new templates as the resource library grows.
