AI fraud radar for Zambian micro-insurance claims with built-in KYC.
Insurtech firms suffer rampant fraud in micro-insurance claims due to lacking robust, Zambian-regulation-compliant KYC systems.
KYCShieldZM combines KYC verification with AI scoring of claim patterns against fraud signals like duplicate phones or rapid claims. It integrates with your backend via webhooks for real-time blocks. Fully BoZ-compliant reports ensure audit readiness, targeting 90% fraud catch rate.
Insurtech firms providing micro-insurance in Zambia
AI model trained on anonymized Zambian micro-insurance data for hyper-local fraud patterns.
professional
Score claims 0-100 based on KYC + behavior.
Real-time alerts to block suspicious claims.
Link verifications to claims for history tracking.
Visualize risk trends and blocked claims.
Generate compliant fraud reports.
Set company-specific fraud thresholds.
Notify on high-risk detections.
Auto-improve with your data.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| company_name | text | No |
| webhook_url | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| claimant_phone | text | No |
| kyc_id | uuid | Yes |
| fraud_score | int | No |
| status | text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| claim_id | uuid | No |
| pattern_type | text | No |
| confidence | int | No |
| timestamp | timestamp | No |
Relationships:
/api/claimsSubmit claim for scoring
/api/claims/:idGet claim details
/api/dashboard/fraud-statsFraud metrics
/api/webhooks/claim-updateSend to customer webhook
/api/rulesUpdate custom rules
/api/exportsGenerate BoZ report
No webhooks
Email support
None
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 15 | 7% | $42 | $504 |
| Month 6 | 120 | 18% | $866 | $10,392 |
Catch 90% of fraudulent claims with KYC + AI, BoZ compliant.
DM 20 Zambian insurtechs on LinkedIn sharing fraud stats from BoZ reports. Offer free Pro access for 50 claims. Post case study in Africa Fintech Slack.
Advanced ML
No Africa data, expensive
Zambia-tuned AI at micro-SaaS price
Anonymized fraud dataset from Zambian users, improving AI accuracy over time.
Post-2023 BoZ fraud crackdown and AI accessibility via edge models.
AI false positives
Configurable thresholds + human override
Data privacy compliance
GDPR/BoZ aligned, anon data only
Success: Avg 20% fraud confirms need
Success: 85% accuracy
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