B

IRP Portfolio Rebalancing Simulator

2.75

Derivation Chain

Step 1 Digital financial product comparison and switch cost visualization
→
Step 2 Financial product switching cost visualization
→
Step 3 Tax and return impact simulation for IRP investment product changes

Competitor references

No usable source links are available for this idea. Its signal notes and scores need independent verification.

Problem

IRP (Individual Retirement Pension) holders want to adjust the balance between principal-guaranteed products (deposits) and performance-based products (funds/ETFs), but there is no tool that holistically shows sell/buy timing, tax deferral effects, and fee differences when changing investment products. Brokerage apps only display individual fund returns without offering portfolio-level rebalancing simulations. As a result, many holders leave their accounts parked in principal-guaranteed products for years, failing to even keep up with inflation.

Solution

Users input their IRP holdings and balances, and the tool auto-generates rebalancing scenarios aligned to target asset allocations (conservative/balanced/growth). It displays capital gains tax deferral effects, projected returns of new products, and total fee comparisons on a single screen. A 10-year 'hold current vs. switch' simulation shows the concrete dollar difference.

Target: Ages 45–58, IRP balance of $22,500+ (~30M KRW), with 70%+ allocated to principal-guaranteed products — salaried workers
Revenue Model: Free basic simulation. Custom asset allocation recommendations + quarterly rebalancing alerts subscription at $2.15/month (~2,900 KRW).
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
2.0/5
M Market
3.0/5
R Realizability
3.0/5
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 (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/ 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 (52/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
9.0/15
Pick-Axe Fit
7.5/15
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