Rental Income Health Insurance Impact Predictor

4.10

Derivation Chain

Step 1 Housing downsizing simulation

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Step 2 Rental income generated from small property investment after downsizing

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Step 3 Pre-simulating the cascading impact of rental income on health insurance premiums and comprehensive income tax

Problem

Retirees aged 55-65 considering small property rental investments with surplus funds overlook the cascading impact of rental income on health insurance premiums (when switching to regional subscriber status) and comprehensive income tax. An 800,000 won (~$600) monthly rental income can add 150,000-250,000 won (~$112-$187) in monthly health insurance premiums plus 6-15% in additional income tax, potentially cutting the effective yield by more than half. There are no tools to calculate this in advance, so investors only discover the 'tax bomb' after making the investment.

Solution

Users enter expected rental income, current income (pension, financial, other), and health insurance enrollment type on a web interface. The system auto-calculates health insurance premium changes + comprehensive income tax changes + net effective yield when rental income is added. It provides a comparison table across rental income brackets (500,000/1,000,000/1,500,000 won per month, i.e., ~$375/$750/$1,125) and suggests alternatives like 'if this yield is lower, ETF dividends might be better.'

Target: Retirees aged 55-65, surplus funds of 50-200 million won (~$37,500-$150,000), considering small property rental investment, currently regional health insurance subscribers or dependents

Revenue Model: Basic simulation (1 scenario) free; Multi-scenario comparison + alternative investment yield comparison Report at 5,000 won (~$3.75) Per Transaction

Ecosystem Role: Education

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

4.0/5

U Urgency

4.0/5

M Market

3.0/5

R Realizability

5.0/5

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

32.0/40

Data Availability

22.5/25

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

7.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

8.0/10

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]

Dashboard