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When 226 local governments nationwide distribute public relief funds (100,000–300,000 KRW (~$75–$225) per person), claim rates stall at 95–98%, and staff spend over 20 hours per week manually calling and texting the 2–5% of unclaimed residents. Without a dedicated analysis tool to identify non-claim causes (elderly residents, address mismatches, unregistered bank accounts), municipalities repeatedly miss claim rate targets just before deadlines.
Integrates with municipal relief fund disbursement systems to provide a real-time dashboard segmented by district, age group, and non-claim reason. Automatically generates targeted outreach messages per unclaimed segment. Recommends optimal contact channels (SMS/mail/in-person visit) by non-claim reason, with automated alerts at D-7, D-3, and D-1 before deadlines.
| 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. |
| 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. |
| 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. |