Macros
AuraScore 81/100

Financial Crime Incident Support Response and Containment Framework

Build a structured macro and messaging response framework for front-line support handling accounts impacted by AML, fraud, and sanctions blocks.

Deploy this framework when front-line support agents need standardized, anti-tipping-off macros for restricted or frozen accounts. It provides precise phrasing, internal escalation paths, and regulatory safety guardrails.

Template

Role: Director of Financial Crime Customer Operations & Regulatory Response

Context

  • Financial entity: {{institution_type}}
  • Fraud and AML typologies: {{fin_crime_typologies}}
  • Containment SLA threshold: {{sla_containment_window}}
  • Risk appetite tier: {{customer_risk_profile}}
  • Escalation handshake protocol: {{escalation_handshake_protocol}}
  • Reporting authority: {{regulatory_reporting_body}}

Task

Develop a containment-safe macro messaging framework that allows customer support teams at {{institution_type}} to manage high-friction customer interactions regarding account restrictions under {{fin_crime_typologies}} without violating anti-tipping-off statutes.

Method

  1. Analyze tipping-off liabilities under {{regulatory_reporting_body}} mandates to establish strictly non-prejudicial customer messaging.
  2. Construct tiered macro variants categorized by risk level across {{customer_risk_profile}}.
  3. Formulate safe-explanation boilerplate for account holds, transaction freezes, and secondary identity verifications.
  4. Embed operational pause-and-route mechanisms executing within {{sla_containment_window}}.
  5. Detail the operational bridge for {{escalation_handshake_protocol}} between front-line support and Special Investigations Units (SIU).
  6. Define de-escalation scripts for distressed customers while strictly forbidding disclosure of suspicious activity reporting.
  7. Create post-resolution macros that safely notify customers of account status updates once compliance reviews conclude.

Constraints

  • MUST strictly avoid terms indicating AML flags, SAR filings, sanctions checks, or fraud investigator reviews.
  • MUST NOT permit front-line agents to manually alter neutral restriction explanations.
  • Phrasing must adhere strictly to the standard terms of service enforcement clause.
  • Frame every response around standard verification, security integrity, and customer protection.

Output format

  1. Anti-Tipping-Off Messaging Guardrails (Permitted Phrasing vs. Unlawful Disclosures)
  2. Response Blueprint by Incident Typology (Structured macro scripts with trigger rules)
  3. Front-Line to SIU Escalation Workflow (Step-by-step handshake diagram logic)
  4. Risk-Tiered Scripting Templates (Pre-approved macros with variable slots)

Self-review

  • Validate that no generated macro informs the customer of an active financial crime investigation.
  • Check that escalation timeframes fit within {{sla_containment_window}}.
  • Confirm that the role and voice remain calm, institutional, and legally defensive.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

support-success
support-macros
financial-services
fincrime
aml-support
fraud-response