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While KakaoBank rapidly rolls out AI features like AI Invitations, customers aged 60+ are dropping out of digital finance because they can't adapt to AI-driven interface changes. Regional financial institutions with high Senior customer ratios (credit unions, community banks, local bank branches) must use teller staff to individually guide customers through AI features, averaging 30 minutes of in-person Education time per customer.
An interactive tutorial SaaS with senior-friendly UX (large text, voice guidance, step-by-step screenshots) that guides users through banking app AI features. Financial institutions upload their own app screenshots to auto-generate customized tutorials, which customers access via QR code to learn at their own pace.
| 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. |