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feat(frontend): automated invoice matching engine for lender-invoice fit #230

Description

@samjay8

Summary

Build an automated matching engine that suggests invoice-lender pairs based on risk profile, currency preference, yield requirements, and historical performance.

Problem

Lenders manually browse the marketplace to find suitable invoices. This is time-consuming and often results in missed opportunities or poor fits.

Requirements

  • Lender risk profile (conservative, moderate, aggressive)
  • Currency preference (XLM, USDC, both)
  • Yield requirement (minimum APY)
  • Invoice matching algorithm: score = f(risk, currency, yield, history)
  • Suggested matches displayed in marketplace
  • Match quality indicator (excellent, good, fair)
  • Override: lender can still browse all invoices

Technical Details

  • Scoring algorithm: weighted sum of match factors
  • Risk assessment: invoice age, originator history, amount
  • Currency match: exact match vs. conversion cost
  • Yield comparison: required vs. available
  • ML potential: train on historical offer-acceptance patterns

Acceptance Criteria

  • Lender can set preferences
  • Matching algorithm produces scores
  • Suggested matches displayed
  • Match quality shown
  • Override to browse all available
  • Performance <100ms for 1000 invoices

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GrantFox OSSIssue tracked in GrantFox OSSMaybe RewardedIssue may be eligible for a GrantFox rewardThird CampaignCampaign: Third CampaignfrontendNext.js frontend workhigh-complexityLarge multi-part effort — new subsystems, cross-cutting changes

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