Community Intelligence — Global Rule Repository

Collective Categorisation Intelligence

SpeyBooks now learns from how businesses categorise their bank transactions and surfaces that knowledge back to every user. When enough businesses agree on how to categorise a merchant, a global consensus rule is created — giving new users instant auto-categorisation from day one.

This is a foundational shift from single-tenant rules to community-powered intelligence, delivered through a new system called the Global Rule Repository (GRR).

How It Works

• Signal collection — every time you categorise a transaction (during import, via rules, or manually), SpeyBooks records an anonymous signal capturing the pattern, operator, and target category.
• Consensus evaluation — a background process aggregates signals across all tenants using a confidence-weighted voting system. When enough distinct businesses agree (meeting the promotion threshold), a global rule is created.
• Provenance-aware matching — the rules engine now evaluates local rules, verified defaults, and global consensus rules together. A 7-dimension lattice score determines the winner, with your local rules always taking priority over community suggestions.

Provenance System

Every categorisation match now carries a provenance level explaining where the rule came from:

• Local — your own rules, created manually or during import.
• Verified — seed rules provided by SpeyBooks as sensible defaults.
• Global — community consensus rules, backed by agreement across multiple businesses.
• System — fallback behaviour (Suspense account).

Your local rules always win. Global consensus is a suggestion, never an override.

Rules Page Enhancements

• Provenance tabs — filter rules by Local, Verified, or Global to see exactly what’s driving your categorisation.
• Global consensus section — read-only view of community rules showing confidence scores, the number of businesses that agree, and how each global category maps to your chart of accounts.
• Enhanced test panel — test any transaction description and see the full score vector as labelled chips, the provenance badge, and social proof for global matches.
• Override indicators — when your local rule disagrees with global consensus, an amber banner shows what the community thinks, letting you make an informed choice.

Import Preview Enhancements

• Provenance dots — each auto-categorised row in the import preview shows a coloured dot indicating whether a local rule (blue) or global consensus (green) made the suggestion.
• Global consensus matching — the import engine now evaluates global rules alongside your local rules, increasing auto-categorisation rates for new users.

Privacy

All signals are aggregated using blind hashing. No tenant can see another tenant’s rules, accounts, or categorisation decisions. The global rules table contains only normalised merchant keys, standard categories, and aggregate statistics.

Known Issues

• Global rules currently operate at the Universal level only. Business-type partitioning (where “SCREWFIX” maps to Materials for construction businesses but Equipment for IT contractors) is designed but not yet active.
• The taxonomy mapping for OtherExpense resolves to Repairs and Renewals, which may not be the most intuitive default for all businesses. This will be refined as more signal data is collected.