B
Export Voucher Settlement Automation SaaS
3.50
Derivation Chain
Step 1
Expansion of the export voucher program
→
Step 2
Settlement workload overload for voucher-recipient SMEs
→
Step 3
Automated voucher settlement document collection & submission service
Problem
SMEs receiving export vouchers (annual revenue $3.7M-$75M) must manually submit supporting documents to the KOTRA system after using vouchers for marketing, translation, and design services. Each settlement takes 2-3 hours on average, and missing documentation risks voucher clawback. Staff waste 15-20 hours per month repeatedly cross-referencing receipts, contracts, and deliverable reports.
Solution
A SaaS that auto-collects voucher usage records (card payments, tax invoices, email-attached deliverables), assembles documentation packages matching KOTRA settlement forms, and pre-validates before submission. Core features: (1) Automated document collection via email/card provider integration, (2) Auto-mapping to settlement form fields, (3) Missing item pre-alerts.
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 (72%)
Data Availability
23.1/25
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 (54/100)
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
Backend [medium]
Frontend [low]
AI/ML [medium]