AI Loan Rate Comparison Dashboard

3.20

Derivation Chain

Step 1 Proliferation of AI loan rate care services

→

Step 2 AI financial product recommendation engines

→

Step 3 AI financial recommendation cross-verification SaaS

Problem

While commercial banks like NongHyup are rapidly launching AI-based loan rate care services, individual borrowers must manually check each bank's app for rate changes. Small Business Owners with annual revenue of $75K–$225K typically manage loans across 2–3 banks and miss rate adjustment windows, losing $375–$1,500 per year in potential interest savings.

Solution

Aggregates AI rate-care results from multiple banks into a single view, automatically alerting users to optimal rate-switching timing and estimated savings. Core features: (1) Integrated loan status via MyData API, (2) Cross-bank AI recommended rate comparison, (3) Estimated savings simulation for rate switching. The key differentiator is cross-bank comparison rather than a single bank's app.

Target: Small Business Owners with $75K–$375K annual revenue and salaried workers aged 30–50 with multiple outstanding loans

Revenue Model: Premium SaaS monthly flat rate of $3.70/account; 2 banks free, 3+ banks Paid. Optional 5% performance fee on realized savings from successful rate switches

Ecosystem Role: Consumer

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

4.0/5

M Market

4.0/5

R Realizability

3.0/5

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 (67%)

Tech Complexity

29.3/40

Data Availability

17.5/25

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 (50/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

7.5/15

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 [low] Data Pipeline [medium]

Dashboard