B
Luggage Loss Insurance Settlement Automator
2.55
Derivation Chain
Step 1
Airport zero-loss baggage systems
→
Step 2
Aviation baggage loss insurance
→
Step 3
Lost baggage insurance claim auto-settlement SaaS
Problem
Insurance claim settlement between travel insurance companies and airlines for lost baggage is entirely manual. Insurance adjusters collect supporting documents (PIR, boarding pass, baggage tag copies) via fax/email and manage them in spreadsheets, taking an average of 3-5 days per claim. Of the approximately 20,000 annual baggage loss claims in Korea, 25% are rejected due to incomplete documentation.
Solution
A SaaS platform that automates the document collection → verification → settlement workflow for baggage loss insurance claims. Three core features — OCR-based automatic document recognition, airline PIR data integration, and policy-specific automatic compensation calculation — reduce processing time from 3-5 days to hours.
NUMR-V Scores
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 (69%)
Data Availability
19.4/25
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)
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
AI/ML [medium]
Backend [medium]
Frontend [low]