MASSIVUE
    AI-Powered Banking Operations
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    AI & Digital TransformationAdvancedMicrocredential

    AI-Powered Banking Operations

    Agent Supports, Analyst Decides. This course teaches you to design that boundary so it survives a supervisory review.

    About 80 minutes·Self-paced online·Lifetime access·Verified digital credential
    Enrol nowTalk to an advisor
    Course intro
    Microcredential Credential 1 of 2Part of Certified AI Banking SpecialistSee the pathway ↓
    Why it matters

    What most courses get wrong, and what this one does differently

    From

    A vendor demo with compliance bolted on at the end, showing what the tool can do and leaving you to work out what you are allowed to do

    To

    Designing the agent's job description before the agent: scope, inputs, outputs, escalation triggers, and named human owner

    From

    A chatbot and a prompt, with no architecture and nothing a regulator can inspect

    To

    A four-layer architecture (data, reasoning, guardrails, channel) with an audit trail, and an AI grounded in your own typology libraries rather than the internet

    From

    Treating the SAR narrative as the AI's output and the analyst as the reviewer

    To

    The Author Rule: the analyst is the author, accountable for the investigative judgement, the narrative, and the filing decision

    Outcomes

    What you'll be able to do

    • Diagnose where AI creates real leverage in KYC onboarding and AML operations, and where it does not
    • Distinguish rule-based automation, generative AI copilots, and agentic workflows, and select the right operating model for each task
    • Apply the regulatory foundations governing AI-assisted regulated decisions, including MAS Notice 626 and FATF expectations
    • Design human accountability into AI workflows using the Agent Supports, Analyst Decides principle
    • Recognise how poor input data produces confident, polished, wrong output, and control for it
    • Identify high-value KYC use cases: document extraction, beneficial ownership mapping, adverse media synthesis, source of wealth, and CDD memo drafting
    • Architect an agentic KYC workflow across data, reasoning, guardrails, and channel layers, with an audit trail a regulator can inspect
    • Define an agent's scope, inputs, outputs, escalation triggers, and named human owner
    • Apply context engineering to ground AI in the bank's own policies, risk appetite, and PEP and sanctions logic
    • Use AI to triage transaction monitoring alerts and assemble investigation packages
    • Ground an AML assistant in firm-specific typology libraries using retrieval-augmented generation
    • Draft SAR narratives with correct source attribution and citation integrity, under the Author Rule
    • Apply FEAT principles and MAS Technology Risk Management expectations to operational AI
    • Choose human-in-the-loop patterns: copilot, recommendation-plus-review, and routing
    • Run adversarial testing for hallucination, prompt injection, fairness, and data leakage before deployment
    Skills

    Skills you'll gain

    Agentic AI workflow designKYC automation (document extraction, beneficial ownership, adverse media, source of wealth)AML alert triage and investigation supportContext engineering and grounded promptingRetrieval-augmented generation over typology librariesSAR narrative drafting and attributionAudit trail designMAS Notice 626 and FATF alignmentFEAT principlesMAS Technology Risk ManagementHuman-in-the-loop design patternsAdversarial and red-team testingAI deployment readiness
    Curriculum

    4 modules · 20 lessons · About 80 minutes

    About 80 minutes, module by module

    Diagnose where AI creates real leverage in KYC and AML, distinguish automation from agentic workflows, apply the regulatory foundations, and design human accountability using the Agent Supports, Analyst Decides principle

    Identify high-value KYC use cases, architect an agentic KYC workflow across all four layers, define the agent's scope and escalation design, and apply context engineering to ground AI in the bank's own knowledge

    Use AI for alert triage and investigation package assembly, ground an AML assistant in firm-specific typology libraries using RAG, and draft SAR narratives under the Author Rule with correct source attribution

    Apply FEAT principles and MAS Technology Risk Management to operational AI, choose human-in-the-loop design patterns, and run adversarial testing for hallucination, prompt injection, fairness, and data leakage before deployment

    The credential

    The credential you earn

    A verified digital credential you can share publicly, and that stacks toward a full certification.

    • Publicly verifiable via a unique credential link
    • One-click add to your LinkedIn profile
    • Verified digital credential, CPD recognition in progress
    How it's earned · Final Assessment (10 minutes): Scenario-based questions on KYC and AML workflow design, the Agent Supports, Analyst Decides principle, FEAT principles, MAS Technology Risk Management, and adversarial testing requirements, plus a capstone: design a governance-ready AI workflow for one KYC or AML use case, specifying escalation triggers, the human accountability owner, and the adversarial test categories required before deployment.
    The MASSIVUE pathway

    Complete both micro-credentials to earn Certified AI Banking Specialist.

    Self-paced microcredentials, about 3 hours of learning in total. Each one stands alone; together they earn the full certification.

    1
    AI-Powered Banking OperationsAbout 90 minYou are hereAgent Supports, Analyst Decides. This course teaches you to design that boundary so it survives a supervisory review.
    2
    AI-Powered Service Professionals (Financial Services)About 90 minRetrieve, Verify, Explain. Three steps that sit between the AI's confident output and the customer who will hold you to it.
    See the full certification →Enrol in the full certification
    How MASSIVUE credentials work:1Take a microcredential→2Stack all 2→★Earn the certification
    Who it's for

    Built for the people who own the regulated decision

    KYC and CDD analysts and onboarding teams
    AML analysts and transaction monitoring teams
    Financial crime compliance officers and MLROs
    Operations team leads and heads of banking operations
    Compliance reviewers and second-line risk functions
    Technology and change teams deploying AI into financial crime operations
    Internal audit reviewing AI-assisted regulated processes
    Not for: People looking for a general introduction to AI, or a general introduction to AML. This course assumes you work in banking operations, understand what a CDD memo and a SAR are, and are now trying to work out how to use AI in that context without losing your licence. Prerequisites: Working knowledge of KYC or AML operations in a regulated institution.

    Prerequisites: Basic understanding of banking operations, financial crime compliance, or risk management processes. Basic digital literacy and familiarity with operational workflows

    What's included

    Everything in the credential

    4 modules of focused video lessons
    About 80 minutes covering the full agentic KYC and AML workflow from operating model selection through deployment readiness
    One continuous operational case: Atlas Private Bank
    The customer Mr. Lim Wei Jian and named roles including KYC Analyst, AML Analyst, Operations Team Lead, Compliance Reviewer, and MLRO. The case runs from onboarding through AI-assisted due diligence, into a transaction monitoring alert, an AML investigation, and a red-team review before deployment
    Sixteen embedded operational scenarios
    Including two onboarding files processed with AI where one has missing ownership information, demonstrating how input quality silently corrupts output; a comparison of vague prompts against policy-grounded prompts; and an AI-generated triage package for analyst review
    The agentic workflow architecture
    Data layer, reasoning layer, guardrails layer, and channel layer, with audit trail design built for regulatory inspection
    Grounding techniques
    Context engineering, structured prompting, and retrieval-augmented generation over firm-specific AML typology libraries, escalation precedents, and materiality frameworks
    Governance content
    FEAT, MAS Notice 626, FATF, MAS Technology Risk Management Guidelines, third-party and model risk, and data residency
    Human-in-the-loop design patterns
    Copilot, recommendation-plus-review, and routing: choosing the right pattern for each regulated task
    Adversarial testing
    Hallucination testing, prompt injection testing, fairness testing, and data leakage testing, plus a FEAT deployment checklist for the go or no-go decision
    Module-end quizzes and a 20-question final assessment
    Covering agentic AI fundamentals, KYC workflows, AML investigation, FEAT principles, MAS TRM expectations, and human-in-the-loop design
    Lifetime access
    Learn at your own pace and revisit as MAS AI Risk Management Guidelines and Singapore's agentic AI supervisory expectations are finalised
    Verified digital badge and certificate
    A publicly verifiable credential you can share on LinkedIn
    For organisations

    Bring this to your team

    For teams

    • Volume pricing and central billing
    • Team progress reporting
    • Optional tailored examples for your sector
    See team plans and pricing

    Deliver under your brand

    • Co-branded or fully white-label delivery
    • Your LMS or ours
    • Revenue-share partnership options
    Become a partner
    FAQ

    Questions, answered honestly

    The regulated decision is not the AI's to make, and that is the point. AI can assemble evidence, extract documents, synthesise adverse media, and draft narratives. The onboarding decision, the escalation decision, and the filing decision stay with a named human owner. This course teaches that boundary as a design principle, not a disclaimer.

    It makes them more convincingly. That is the real risk, and it is why Garbage In, Polished Out is one of the first things this course teaches. Generative AI produces fluent, well-formatted output regardless of whether the input was complete. Every control in the course exists to interrupt that.

    It will not eliminate them. What AI can do is compress the triage work: assembling the alert context, pulling counterparty information, surfacing relevant typologies, and drafting a summary, so the analyst spends their time on judgement rather than assembly. The rigour stays. The clerical load drops.

    It is Singapore-anchored, using MAS Notice 626, MAS Technology Risk Management Guidelines, and the FEAT principles, alongside FATF recommendations which apply globally. If you operate under MAS, it is directly applicable. If you do not, the architecture, the accountability design, and the testing regime transfer, but you should map them to your own regulator's expectations.

    It is a verified digital credential you can share and verify online. It is not an accredited or government-recognised qualification, and it is not regulatory or legal advice. CPD recognition is in progress.

    Yes, and that is the right way to use it. The whole course is about the boundary between what the agent does and what the analyst owns, and that boundary has to be agreed by operations, compliance, and technology together. Team access with volume pricing and central billing is available on request.

    Keep stacking

    Related microcredentials

    Microcredential
    AI-Powered Service Professionals (Financial Services)
    About 90 min
    View microcredential →

    The Author Rule: AI may draft the SAR narrative. The analyst is the author, accountable for the investigative judgement, the narrative, and the filing decision.

    Verified digital credential

    Enrol nowSee the full certification