B
Pre-Retirement In-House Benefits Settlement Checklist
3.85
Derivation Chain
Step 1
Interest in senior workers and EITC
→
Step 2
Missing out on in-house welfare and benefits settlement before retirement
→
Step 3
Action guide for in-house benefits often missed at retirement (education loan repayment deferral, employee stock handling, leave settlement) by item
Problem
Employees aged 53-58 at large corporations and mid-sized companies often miss out on hundreds of thousands to millions of KRW in in-house benefits settlement before retirement. There are more than 10 settlement items, including compensation for unused annual leave, optimal timing for withdrawing employee stock ownership (tax differences before vs. after retirement), handling outstanding company education loans, whether group insurance can be converted to individual coverage, and using up remaining welfare points. However, HR does not provide a comprehensive guide, and employees must inquire individually. Many items cannot be claimed retroactively after the retirement date, leading to frequent regrets like 'I should have taken care of that then.'
Solution
Users select their tenure, company type (large corporation, mid-sized company, public enterprise), and held welfare benefits on the web, and the service generates a checklist of settlement items that must be addressed before retirement. For each item, it provides the optimal timing (60 days before retirement, 30 days before, or on the retirement date), responsible department, required documents, and how to estimate the expected amount. The checklist is sorted by schedule and presented as a timeline from D-60 to D-Day.
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. |
N=.15 U=.20 M=.15 R=.30 V=.20
Feasibility (75%)
Data Availability
23.3/25
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 (56/100)
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
Frontend [low]
Backend [medium]