Real-time Gold Trading Fee Comparison

3.70

Derivation Chain

Step 1 Gold price surge and Trump risk

→

Step 2 Rapid increase in individual gold investment

→

Step 3 Demand for comparing fees and spreads across gold trading channels

Problem

As gold prices recover to $5,200, individual gold investors are surging, but channels such as bank gold passbooks, the KRX gold market, gold bars, and gold ETFs each have different fee, spread, and tax structures, causing investors to spend an average of 2-3 hours comparing optimal channels. In particular, fee differences can reach hundreds of thousands of KRW depending on buy/sell timing, but there is no tool to compare them in real time, leading to unnecessary costs from trading on suboptimal channels.

Solution

A service that compares real-time buy/sell prices, fees, and taxes of bank gold passbooks (5 major banks), the KRX gold market, major gold dealers, and gold ETFs on one screen, and simulates net returns by channel when users input investment amount and holding period. Differentiated by providing price alerts and a monthly fee savings report.

Target: Individual gold investors in their 30s-50s, office workers and self-employed individuals interested in asset management with investment assets ranging from 10,000,000 to 500,000,000 KRW (approx. $7,500 to $375,000).

Revenue Model: Premium SaaS 29,000 KRW (approx. $21.75) per month per account (real-time alerts + simulation), free tier limited to 3 queries per day. 20% discount for annual payment.

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

4.0/5

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.

N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (64%)

Tech Complexity

24.0/40

Data Availability

20.0/25

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 (58/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

16.0/20

Revenue Signals

10.5/15

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 [medium] Data Pipeline [medium]

Dashboard