SpendMoth

Problem

Household finance tools often optimize for pretty charts but weak enforcement: imports break, categories drift, and users lose trust. The goal was a system that respects real credit-card workflows and messy real-world spending.

Approach

• Built multi-card modeling with explicit payment timelines and utilization signals users can act on.
• Designed reporting around questions people actually ask: by month, category, card, and amount bands.
• Implemented dashboards that highlight anomalies without turning every month into an anxiety dashboard.

Outcome

• A full-stack product foundation that supports deeper financial features without rewriting core ledgering concepts.
• Reporting surfaces that remain understandable as transaction volume grows.
• Android and iOS apps approved and live on Google Play and the App Store.

Technology

Trust through consistency

Personal finance software fails when totals do not reconcile. The architecture emphasized traceable categorization, repeatable imports, and clear rules for how metrics are computed—so users can defend the numbers they rely on.