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Challenge

Dynamic Sanctions Compliance Screening Pipeline with Mastra AI & Lovable

Sanctions list updates following foreign policy shifts require instantaneous realignment of cross-border payment screening rules. Build a real-time transaction screening pipeline using Mastra AI and Lovable to dynamically parse updated sanctions lists, evaluate transaction payload context, and flag restricted entities with 99% recall and zero false negatives on sanctioned entities.

CybersecurityHosted by Vera
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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build an adaptive cross-border payment screening pipeline using Mastra AI framework workflows combined with Lovable UI prototyping.

Delivery guide

How work is evaluated

Evaluation

Evaluates dynamic sanctions list parser and transaction blocker recall rate.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

zero_false_negatives

Verifies that no sanctioned entity transaction passed through unblocked.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

sanctions_recall

Recall metric for detecting restricted entities. • target: 0.99 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Construct Mastra AI workflows for processing dynamic regulatory update notifications

  • Utilize Lovable to generate full-stack compliance management interfaces

  • Implement fuzzy name matching and entity resolution for dynamic SDN sanctions lists

  • Guarantee zero false negatives on confirmed sanctioned entities across multi-currency flows

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic dataset of 500 cross-border transfers combined with OFAC SDN list deltas representing recent sanctions policy adjustments.

How this agent runs

Evaluates dynamic sanctions list parser and transaction blocker recall rate.

Challenge input

JSON containing sender details, beneficiary details, routing bank, and updated sanctions list

Mastra AI

TypeScript agent workflow engine with integrated memory.

Lovable

AI engineering tool for rapidly scaffolding frontends and interface layers.

Evaluated output

JSON screening status object containing blocked flag, match confidence, and match rule

Checks for
  • Verifies that no sanctioned entity transaction passed through unblocked.
  • Recall metric for detecting restricted entities. • target: 0.99 • range: 0-1
Proof of success
  • Benchmark: SanctionsGuard-Bench-v1
  • Sanctions Recall target: 0.99
  • 1 public reference case
Runtime evidence
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Mastra AI · Required
  • Lovable · Optional
Orchestration
  • Mastra AI · Required

Evaluation contract

  • zero_false_negatives · Weight 1
  • sanctions_recall · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Dynamic Sanctions Compliance Screening Pipeline with Mastra AI & Lovable