Real-time fraud alerts and USSD verification for African mobile procurement
African supply chain businesses are increasingly victimized by surging cyber fraud as they adopt digital procurement and mobile payments without adequate protections.
LipaGuard integrates directly with mobile money APIs (M-Pesa, MTN MoMo, Airtel) to monitor supply chain payments in real time. It applies localized risk rules and basic ML models to flag suspicious transactions, then requires secondary confirmation via biometric, SMS, or USSD before funds move. This creates a protective layer that works even on low-data networks common across African SMEs.
Supply chain operators, procurement managers, and SME owners in African businesses implementing digital payments and procurement
Built from the ground up for African mobile money rails with offline USSD fallback — unlike Western tools that assume constant internet and credit cards.
supportive
Connect to M-Pesa, MTN MoMo, and Airtel Money via official APIs for real-time transaction visibility
Rule-based + lightweight ML model that scores every transaction for fraud probability using amount, vendor history, and velocity
Forces biometric or USSD approval for any transaction above risk threshold
Push notifications, SMS, and automated voice calls when fraud is suspected
Mobile-first dashboard showing all procurement activity with risk history and exportable logs
Add multiple users with approver vs viewer permissions
Weekly PDF reports showing blocked attempts and trends
Shared (opt-in anonymized) list of known fraudulent vendors
Forecast risk of new vendors based on network data
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| name | text | No |
| country | text | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| org_id | uuid | No |
| phone | text | No |
| role | text | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| org_id | uuid | No |
| external_id | text | Yes |
| amount | int | No |
| vendor_name | text | No |
| risk_score | int | No |
| status | text | No |
| verified | bool | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| transaction_id | uuid | No |
| message | text | No |
| resolved | bool | No |
| resolved_at | timestamp | Yes |
Relationships:
/api/transactionsList organization's transactions with risk scores
/api/transactionsWebhook receiver from mobile money providers
/api/verifySubmit secondary verification decision (biometric/USSD)
/api/alertsFetch pending alerts for current user
/api/reportsGenerate monthly fraud summary
100 transactions/month
None
Unlimited
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 140 | 9% | $315 | $3,780 |
| Month 6 | 720 | 19% | $3,420 | $41,040 |
Real-time protection layer for African supply chains. Get USSD/biometric verification on every risky procurement payment.
1. Post targeted offers in 12 active East African supply chain WhatsApp groups offering 6 months free for the first 8 businesses that complete a 20-minute interview. 2. Run LinkedIn outreach to 80 procurement managers in Kenya, Uganda, and Ghana with a personalized Loom video audit of their current fraud exposure. 3. Partner with two regional SME associations (Kenya Manufacturers Association and Ghana Chamber of Commerce) to present at their monthly virtual meetups.
Mature ML models
No native African mobile money or USSD support
Deep integration with M-Pesa/MTN and offline-first design
Strong African presence
Generic fraud rules not tailored to procurement/supply chain
Specialized risk models for vendor invoices and repeat orders
Proprietary dataset of African mobile money fraud patterns that improves detection accuracy as more businesses contribute anonymized signals
Mobile money transaction volume in Sub-Saharan Africa surpassed $1 trillion in 2023 while reported cyber fraud cases rose over 400% in the same period according to Interpol Africa reports.
API reliability of multiple mobile money providers
Build with sandbox-first approach, implement circuit breakers, and start with only top 3 providers
Slow adoption by non-tech-savvy SME owners
Heavy emphasis on simple USSD flows and localized onboarding videos in Swahili, French, and English
Data residency and privacy laws (NDPR Nigeria, Kenya DPA)
Local legal review in launch countries and explicit consent at every data collection point
Success: Clear willingness to pay $20-30/month and identification of top 3 fraud scenarios
Success: At least 9 businesses renew and report at least one prevented fraud incident
Success: 150 sign-ups and 25 paid conversions in first 30 days
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Slash payment fees to 0.8% with seamless ACH checkouts for high-ticket creators.
Accept crypto payments at 1% fees, auto-convert to USD for creators.
Global bank transfers at 0.4% fees for international high-value creator sales.