Auto-Payment Ghost Spend Detector

3.05

Derivation Chain

Step 1 Digital Subscription cleanup

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Step 2 Unable to track auto-payments/Subscriptions

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Step 3 Automatic ghost payment detection via card statement pattern analysis

Problem

Workers in their 50s trying to clean up a decade of accumulated card auto-payments have to check statements across 3-4 different card company apps separately. Small charges like ~$3.70/month fly under the radar, and unused app Subscriptions or add-on services silently drain $150-$375 annually. Even canceling is painful — each service has a different cancellation flow, taking 10-20 minutes per item.

Solution

Users upload their last 6 months of card statements (CSV/Excel), and the tool automatically identifies recurring payment patterns to compile an 'active Subscriptions' inventory. For each item, it shows estimated last actual usage date, a direct link to the cancellation page, and projected annual savings.

Target: Ages 45-60, holding 2+ credit cards with 5 or more auto-payment items per month, at a point of financial reorganization (Retirement planning, year-end tax settlement, etc.)

Revenue Model: Free basic analysis (Subscription list extraction). Cancellation guide + annual savings Report at ~$2.20 Per Transaction. Future Subscription management monthly monitoring service at ~$1.40/month (Monthly Subscription).

Ecosystem Role: Consumer

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

4.0/5

M Market

4.0/5

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 (67%)

Tech Complexity

24.0/40

Data Availability

23.1/25

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 (54/100)

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

5.0/10

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

Frontend [medium] Backend [medium]

Dashboard