A

Rate-Hold Loan Refinancing Hub

3.65

Derivation Chain

Step 1 Bank of Korea base rate held at 2.50% for 6 consecutive meetings
→
Step 2 Borrower rate comparison and refinancing demand
→
Step 3 Integrated hidden-cost simulator for loan refinancing

Problem

With the prolonged base rate freeze widening interest rate gaps between commercial banks, mortgage and personal loan holders (salaried workers ages 30-50) consider refinancing but struggle to accurately calculate hidden costs like early repayment penalties, stamp duty, and mortgage registration fees. Bank branch consultations only recommend in-house products, and loan comparison platforms show only interest rates without revealing actual savings. Cases of losing $375-$1,500 (~500,000-2,000,000 KRW) from poorly-timed refinancing are frequent.

Solution

Users enter their current loan terms (remaining balance, interest rate, remaining term, early repayment penalty rate), and the system automatically compares total refinancing costs (penalties + stamp duty + registration fees) and actual savings across 10 major banks on 5-year/10-year/maturity bases. Visualizes the break-even point and optimal refinancing timing to support the 'should I refinance now?' decision within 1 minute.

Target: Salaried workers ages 30-50 with mortgages, loan balances between $75,000-$375,000 (~100 million-500 million KRW)
Revenue Model: Premium conversion model — basic comparison free, detailed simulation at $3.67/month (~4,900 KRW), CPA commission from financial institutions per executed loan referral.
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
2.0/5
U Urgency
4.0/5
M Market
5.0/5
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.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (70%)

Tech Complexity
29.3/40
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 (55/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
12.0/15
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

Backend [medium] Frontend [medium] Data Pipeline [low]
Dashboard