Real-time fraud detection for Nigerian transactions – rules + anomalies.
Nigerian entrepreneurs face a severe shortage of skilled RegTech professionals, preventing them from developing and maintaining advanced AML and fraud detection systems.
FraudShieldNG monitors transaction streams with Nigeria-tuned rules for unusual patterns like BVN mismatches or geo-fencing. It flags suspicious activities instantly via API/webhook, helping fintechs block fraud without data scientists. Dashboards show fraud rates and prevention stats for compliance reporting.
Nigerian entrepreneurs in fintech, banking, or compliance-heavy startups needing AML and fraud systems
Pre-built rules for NG payment schemes (NIP, POS fraud) + lightweight anomaly detection, solo-dev friendly.
supportive
API to log transactions with amount, BVN, IP, device.
Configurable rules e.g., velocity checks, blacklists.
Simple ML (isolation forest) for outlier txns.
Webhook/email for fraud scores > threshold.
Charts of blocked/approved txns, loss prevented.
Manual review for flagged txns.
CSV of all decisions.
Track repeat fraud devices.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| api_key | text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| org_id | uuid | No |
| amount | int | No |
| bvn | text | Yes |
| ip | text | Yes |
| fraud_score | int | Yes |
| decision | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| org_id | uuid | No |
| name | text | No |
| conditions | jsonb | No |
Relationships:
/api/txnsLog transaction for scoring
/api/txnsFetch org txns
/api/rulesCreate custom rule
Basic rules
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 80 | 3% | $60 | $720 |
| Month 6 | 400 | 6% | $576 | $6,912 |
AI rules catch BVN swaps & velocity fraud – integrate in minutes, $25/mo.
Join Nigerian Payments Forum on WhatsApp, offer free Pro for 1 week to 15 members with txn logs. Email cold to Opay/Moniepoint clones from LinkedIn. Demo at Lagos Fintech Meetup.
Advanced ML
Not tuned for Africa, high cost
NG rules + flat pricing
Transaction data moat for better anomaly models over time.
2024 NIBSS fraud reports up 50%, fintechs scaling transactions.
High txn volume overload
Queueing + edge functions
Data privacy (NDPR)
Anon data, consent flows
Success: Avg $5k/mo loss
Success: 95% accuracy
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