All ideas/fintech/Plataforma SaaS de analítica de fraude que integre visualización de distribución de riesgo, efectividad de reglas AML, eventos en tiempo real y mapas de calor de fraude.

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Plataforma SaaS de analítica de fraude que integre visualización de distribución de riesgo, efectividad de reglas AML, eventos en tiempo real y mapas de calor de fraude.

Scouted 8 hours ago

6.5/ 10

Overall score

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Score breakdown

Urgency8.0

Market size7.0

Feasibility6.0

Competition5.0

Pain point

Los equipos de cumplimiento no pueden visualizar patrones de fraude, efectividad de reglas ni el backlog de escalación de forma estructurada.

Who'd pay for this

Equipos de cumplimiento y riesgo en instituciones financieras, fintechs y empresas con alta exposición a fraude transaccional.

Source signal

"Compliance teams cannot see fraud patterns, rule effectiveness, or the escalation backlog in a structured way."

Original post

[Wave 200pts] Build Fraud Analytics Dashboard — Risk Distribution, Rule Effectiveness, and High-Risk WebSocket Events

Published: 8 hours ago

Repository: Nexacore-Org/NexaFx-js Author: portableDD ## Summary The risk engine scores transactions and flags them but this data is never surfaced in analytics. Compliance teams cannot see fraud patterns, rule effectiveness, or the escalation backlog in a structured way. ## Acceptance Criteria - [ ] GET /admin/analytics/fraud returns risk score distribution in buckets (0-20, 21-40, 41-60, 61-80, 81-100) - [ ] Flagged, auto-resolved, and escalated counts for configurable period - [ ] Most triggered AML/risk rules ranked by frequency with trigger rate % - [ ] GET /admin/analytics/fraud/heatmap returns 24x7 grid (hour of day × day of week) of fraud flag counts - [ ] New HIGH risk transaction (score > 70) emits fraud.highRisk WebSocket event to admin channel - [ ] Rule effectiveness shows TP/FP rate based on manual review decisions ## Key Files - `src/modules/analytics/services/fraud-analytics.service.ts` - `src/modules/analytics/controllers/admin-analytics.controller.ts` — add fraud endpoints - `src/modules/transactions/services/risk-scoring.service.ts` — expose review outcome data - `src/web-sockets/notifications.gateway.ts` — emit fraud.highRisk - `test/fraud-analytics.e2e-spec.ts` ## Constraints - Heatmap computed from DB data — not in-memory - WebSocket fraud events only go to admin channel — never user channels - Complexity: **High — 200 points**

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