ChargeGuard: SaaS Payment Fraud Pattern Detector

3.05

Derivation Chain

Step 1 Recurring scam patterns targeting tech workers

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Step 2 SaaS Billing fraud detection

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Step 3 Fake subscription and refund fraud detection service for small SaaS operators

Problem

Solo/small SaaS operators are losing 5-15% of monthly revenue to fraud—including chargebacks from stolen credit card subscriptions, Free Trial abuse through repeated signups, and refund fraud. Tools like Stripe Radar specialize in global patterns and miss fraud patterns specific to Korea's payment environment (KakaoPay, NaverPay, virtual bank accounts).

Solution

(1) By integrating with TossPayments/Iamport webhooks, the service detects payment pattern anomalies in real time (multiple attempts in short intervals, foreign IP + domestic card, etc.), (2) blocks Free Trial abuse through device fingerprinting, and (3) sends preemptive alerts before chargebacks occur.

Target: Solo SaaS operators with $750-$37,500 monthly revenue, small E-commerce operators (1-5 employees)

Revenue Model: SaaS usage-based: $22/month base fee (1,000 transactions) + $0.02 per additional transaction. $3.75 performance bonus Per Transaction for successful chargeback prevention

Ecosystem Role: Supplier

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

4.0/5

M Market

2.0/5

R Realizability

3.0/5

V Validation

3.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (74%)

Tech Complexity

34.7/40

Data Availability

19.4/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (52/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

3.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Frontend [low] AI/ML [low]

Dashboard