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CHIMBUK.

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Neobank & money insightsConcept study — original Chimbuk design · not affiliated with any live product

FinPulse

A bank you can read: every taka labeled, every subscription caught, every plan explained.

AI that asks before it guesses — corrections train a per-user model

The brief we wrote ourselves

Consumer finance super-app concept: accounts, AI category insights, savings jars and a compliance backbone that would survive an audit.

The problem in this category

Banking apps store history; they don’t build understanding. People want the app to tell them what their money is doing.

How this concept answers it

Transaction enrichment with AI classification that asks for corrections (and learns per user), savings automation on natural moments (round-ups, payday rules), and privacy as a feature — local-first categorisation with opt-in cloud sync.

Feature set

  • AI transaction categorisation + correction loop
  • Subscription hunter with cancel letters
  • Goal jars with round-up engines
  • Bank-grade: MFA, device binding, anomaly flags
  • Open banking rails (account aggregation)

Begin the ascent

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