Nepali citizens face relentless digital scams – phishing links draining eSewa wallets, fake loan offers trapping small businesses – with community reports arriving too slowly to prevent mass victimization. Today, Tech Aware Nepal's manual review process takes 72 hours (source: Q2 ops logs) to connect identical scams, allowing a single fake Daraz coupon link to spread across 17 districts and drain $8,500 before alerting the community (source: Kathmandu Post investigation, Jan 2024). Each hour of delay costs real livelihoods: a micro-merchant loses 3 days' income recovering from a $30 scam (source: UNDP Nepal financial resilience survey).
Business case: 12,000 monthly reports (source: platform analytics, Apr 2024) × 65% preventable repeats (source: Nepal Police Cyber Bureau case analysis) × $38 avg. loss per scam (source: Nepal Rastra Bank 2023 digital fraud report) = $3.55M/year recoverable losses. If adoption reaches only 40% of estimated reports: $1.42M/year. This feature is an AI-powered scam pattern detector that clusters reports and auto-publishes alerts in <15 minutes. It is not a fraud transaction blocker, real-time intercept system, or law enforcement evidence platform.
Execution risk: False negatives could leave campaigns undetected – a 5% miss rate on high-volume scams risks $177K in preventable losses. Inaction risk: Without this by Q3, Nepal Police's planned public scam portal (source: MoCIT roadmap) will capture community trust. Given the asymmetric upside and operational urgency, this warrants immediate build with robust validation gates.
Primary outcomes (D90):
| Metric | Baseline | Target | Kill Threshold |
|---|---|---|---|
| Avg. alert latency | 72 hours | ≤45 min | >6 hours |
| Repeat scam victims | 38% (Q1 survey) | ≤15% | >30% |
| Community trust score | 3.2/5 (n=420) | ≥4.3 | <3.5 |
Guardrails:
| Metric | Threshold | Action |
|---|---|---|
| False campaign alerts | >0.5% weekly | Freeze auto-publish |
| P95 clustering time | >30 sec | Scale inference nodes |
| Unreviewed alerts | >50 backlog | Add moderator capacity |
What we DON'T measure:
TECHNICAL: URL obfuscation evasion
ADOPTION: Low report volume in rural areas
COMPLIANCE: Nepal Electronic Transactions Act §35 data retention
EXECUTION: Moderation capacity bottleneck
Kill criteria:
2% false alert rate sustained for 72 hours
Core AI job: Cluster unstructured scam reports (SMS/email screenshots, descriptions) into campaigns using three signals:
Performance requirements:
Failure boundaries:
Sources:
Pipeline:
POST /report {phone: "98XXXXXX95", text: "क्लिक गर्नुहोस्...", urls: [...]}Critical gaps:
Test suites:
| Test Type | Criteria | Target |
|---|---|---|
| Campaign detection | Time from 5th identical report → alert | ≤15 min |
| Clustering accuracy | F1 score vs human-labeled campaigns | ≥0.97 |
| False alert rate | Campaigns flagged without ≥3 reports | 0% |
Validation protocol:
Evaluation owner: Community Moderator Team (validate against 200-sample threat corpus weekly)
Critical oversight points:
UI for oversight:
┌───────────────────────────────[ PENDING CAMPAIGNS ]──────────────────────────────┐
│ ⚠ Daraz 50% coupon scam [12 reports] VERIFY ▼ │
├──────────────────────────────────────────────────────────────────────────────────┤
│ 📱 Sender: 98*****95, 98*****01 ⏱ First seen: 2h ago │
│ 🔗 URL: daraz-offer-np[.]xyz (12x) 📍 Kathmandu (9), Pokhara (3) │
│ 📝 Text pattern: "अन्तिम २ घण्टा! डाराजबाट ५०% छुट को उपहार" │
└──────────────────────────────────────────────────────────────────────────────────┘
Trust metrics:
| Metric | Target | Measurement |
|---|---|---|
| Alert accuracy | ≥99.5% | User "false alert" reports |
| Alert usefulness | ≥4.5/5 | Post-alert survey (n≥100/month) |
| Detector uptime | ≥99.9% | Synthetic report probes |
Failure containment: