Investment Scam Message Detector

4.00

Derivation Chain

Step 1 AI ethics and security issues

→

Step 2 Adults in their 40s-60s can't distinguish stock, crypto, and Real Estate investment scam texts and messages

→

Step 3 A service that instantly determines whether a pasted suspicious message is a scam and provides reporting guidance

Problem

Adults in their 50s-60s receive 2-3 investment scam texts or KakaoTalk messages per week — 'stock tip groups,' 'guaranteed 30% returns,' 'recommended stocks from a famous brokerage employee.' Sophisticated scams disguised as recommendations from acquaintances are hard to distinguish, and actual investment fraud losses among people in their 50s-60s exceeded KRW 2 trillion (~$1.5 billion) annually as of 2025. Even when suspicious, the 'what if it's real' mindset leads them to investigate further, which is exactly how they get victimized.

Solution

Paste a suspicious text or KakaoTalk message into the web service, and within 10 seconds get a scam probability (%), scam type classification (stock tip group / Ponzi / phishing / fake brokerage), and the top 3 red flags. A 'Report' button links directly to the Financial Supervisory Service reporting page, and 3 similar scam cases are shown to aid judgment. A weekly briefing on trending scam tactics is also provided.

Target: Adults aged 50-65 interested in stocks, Real Estate, or crypto who frequently receive investment-related messages, or those whose family members have been scam victims

Revenue Model: Free web service. Financial institution partnerships (fraud prevention campaign partner). Premium (KRW 1,900/month, ~$1.40/month): real-time new scam alerts, family protection mode (notifies me when a family member requests a scam check).

Ecosystem Role: Education

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

5.0/5

M Market

4.0/5

R Realizability

4.0/5

V Validation

4.0/5

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 (76%)

Tech Complexity

34.7/40

Data Availability

20.8/25

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 (59/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

20.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

7.0/10

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] Data Pipeline [low]

Dashboard