A

Retirement Health Insurance Premium Shock Defense Simulator

4.10

Derivation Chain

Step 1 Strengthened public data center security standards → Strengthened sensitive data protection policies
→
Step 2 Government digital policies also affect personal data and social insurance systems
→
Step 3 Simulation to prepare for the surge in premiums based on owned assets when converting from workplace to regional health insurance after retirement

Problem

When employees aged 55-60 retire, their workplace health insurance converts to regional health insurance, and at that time all owned real estate, financial assets, and vehicles are reflected in the premium calculation, causing monthly premiums to surge from the previous 100,000-150,000 KRW (approx. $75-$112.50) to 300,000-800,000 KRW (approx. $225-$600). The National Health Insurance Service website allows mock calculations, but users must separately check and input real estate official prices, financial income, and pension income, and there is no scenario comparison feature to show 'which assets should be adjusted before retirement to reduce premiums.' Most people are shocked only after receiving the first bill post-retirement, missing the opportunity for advance preparation.

Solution

By inputting real estate holdings (official prices), financial assets, vehicles, and expected pension income, the service automatically calculates the expected monthly premium after retirement when converting to regional health insurance. It shows 3-5 cost-saving scenarios in a comparison table, such as 'when selling real estate,' 'when using voluntary continued enrollment (maintaining workplace health insurance for 36 months after retirement),' and 'when diversifying financial income,' along with the legal requirements and precautions for each scenario.

Target: Employees aged 53-60, 1-3 years before retirement, owning at least one real estate property, and needing to verify whether they can maintain dependent status for their spouse.
Revenue Model: Free basic premium calculation, PDF download of savings scenario comparison report (5 scenarios + voluntary continued enrollment profit/loss analysis) for 7,900 KRW (approx. $5.93), and per-transaction brokerage fee for tax accountant consultation reservations.
Ecosystem Role: Regulation
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
4.0/5
V Validation
3.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (65%)

Tech Complexity
24.0/40
Data Availability
20.8/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (56/100)

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
7.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Frontend [medium] Backend [medium]
Dashboard