Easy Accounting — A Local-First, Privacy-Focused Finance App

Designed for users who value privacy, prefer a clean interface, and want on-device intelligent analysis. All sensitive data stays on the device, and key insights are computed locally with TensorFlow Lite (or statistical fallback).

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Core Value

Privacy Protection: Local storage (SQLite) and on-device inference ensure sensitive financial data never leaves the device (advertising excluded).

Smart Insights: Generates spending trends, weekday/weekend behavior analysis, small-purchase accumulation alerts, and category growth warnings.

Offline Forecasting: Uses built-in models or fallback statistical algorithms to provide next-month expense predictions with confidence levels and category breakdowns.

Anomaly Detection: Automatically identifies unusual transactions and notifies the user based on severity.

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Key Features

Transaction Management: Add/edit/delete income and expenses; supports notes, categories, date/time, and currency selection.
Multi-Currency Support: Each entry can specify a currency; the home screen summarizes balances and transactions by currency.
Budget Module: Create monthly budgets with overspending alerts, warnings, and progress tracking.
Reports & Visualization: Daily/weekly/monthly trend charts, category breakdowns, and searchable detail views (interactive and smoothly rendered).
Smart Category Suggestions: Provides category recommendations based on notes and amount (model or keyword+statistics fallback).
Anomaly Detection & Severity Alerts: Highlights potentially abnormal transactions for review.

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Target Users
• Privacy-conscious users who prefer offline data and local intelligence.
• Users needing multi-currency tracking or frequent travelers.
• Anyone seeking data-driven insights to improve spending habits.

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Usage Scenarios
• Quickly record daily expenses and rely on budget alerts to avoid overspending.
• Review AI predictions monthly to adjust financial planning.
• Receive automatic alerts for unusually large expenses to prevent errors or unauthorized spending.

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Future Expansion (Suggested)
• Optional cloud backup/sync (prioritizing end-to-end encryption).
• Import/export via CSV or JSON.
• Customizable categories, rules, and batch editing.
• More model options: stronger or lighter inference models selectable by users.

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Implementation & Technical Notes (Suggested)
• Local Storage: SQLite (or Room / Core Data depending on platform).
• On-Device ML: TensorFlow Lite with statistical fallback for offline reliability.
• Multi-Currency: Normalize internally to a base currency; display formatted amounts in UI.
• Advertising: Optional AdMob integration with user-controllable personalization settings.

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Feature Highlights (For Presentation)
• Expense & Income Management: Add/edit/delete, filter by category and date.
• Multi-Currency Support: Currency selection per transaction with balance summaries.
• Budget Alerts: Monthly budgets with overspending and warning indicators.
• Visual Analytics: Daily/weekly/monthly trends and category breakdowns.
• Smart Analysis: On-device ML predictions, anomaly detection, category suggestions, and insights.
• Localization & Offline Use: Multi-language support, fully local processing and storage.
• Privacy-First: Sensitive data stays in SQLite; no external transmission (ads aside).