Proof-of-Account-Transactions (PAT)

User Journey

Sarah wants to apply for a mortgage with a decentralized lending protocol that requires verification of stable income and positive cash flow patterns. Using zkTLS capability, she securely connects to her primary bank account through an encrypted tunnel. The system analyzes her transaction history, including income deposits, recurring expenses, and spending patterns; without exposing specific merchant names, transaction amounts, or counterparty details. This Credential enables her to access customized financial products based on her verified transaction patterns while maintaining complete privacy over her sensitive financial activity.

Why Verify Transaction History?

Transaction history analysis represents the most granular level of financial intelligence in Anti-Money Laundering (AML), and risk management frameworks. Financial institutions and DeFi platforms need to verify that users' transaction patterns.

Why zkMe PAT

Traditional transaction verification requires users to submit complete bank statements, revealing every payment, purchase, and transfer to the verifier. zkMe's zkAML-integrated transaction verification transforms this process by enabling platforms to detect suspicious patterns and verify legitimate financial behavior while ensuring that specific transaction details, merchant information, and counterparty identities remain completely private. This approach meets the highest standards of transaction monitoring requirements while protecting users' financial privacy.

• Advanced Pattern Analysis: Our system goes beyond simple transaction counting to analyze complex financial behaviors, cash flow patterns, and temporal trends while maintaining zero-knowledge of specific transaction details.

• Temporal zkTLS Verification: Unlike balance checks, our transaction verification incorporates time-series analysis, allowing verification of financial behavior consistency over weeks, months, or years through secure historical data access.

• Behavioral Finance Integration: The protocol enables sophisticated financial personality assessment based on actual transaction behaviors that are typically only available to traditional banks' advanced scoring systems.

• Privacy-Preserving: We've developed specialized ZKP circuits that can detect suspicious transaction patterns (like structuring or rapid circular movements) without revealing the underlying transactions to any party.

How It Works

The Proof-of-Account-Transactions procedure uses zkTLS to create a secure, privacy-preserving analysis of financial transaction patterns and histories.

Transaction Analysis & Verification Flow:

1. Secure Transaction History Access

   • QR Code Initiation: The zkMe widget generates a unique QR code for transaction history access

   • Timeframe Selection: Users specify the verification period (e.g., 3, 6, or 12 months)

   • Secure Authentication: Users log in directly to their financial institution through zkTLS secure tunnel

   • Scope Authorization: Users authorize access to transaction history within specified date ranges

2. Privacy-Preserving Transaction Analysis

   • Pattern Recognition: System analyzes transaction flows for income consistency, expense categories, and cash flow patterns

   • Behavioral Metrics: Calculates key indicators (income stability, savings rate, debt service coverage)

   • AML Pattern Screening: Transaction flows are screened for suspicious patterns through zkAML integration

   • Categorization Without Exposure: Transactions are classified into categories (income, essential expenses, discretionary spending) without revealing specifics

   • Data Minimization: Raw transaction details, merchant names, and exact amounts are discarded after analysis

3. Zero-Knowledge Proof Generation

   • Commitment Phase: The user's device generates cryptographic commitments encoding transaction patterns and behavioral metrics

   • Challenge Phase: The verifier sends random challenges to ensure the validity of transaction pattern proofs

   • Response Generation: The user's device processes challenges with aggregated transaction data

   • Pattern Verification: Platform verifies financial behavior claims without accessing any individual transactions

4. Credential Issuance & Behavioral Scoring

   • SBT Minting: A Proof-of-Account-Transactions Soulbound Token is issued to the user's wallet

   • Behavioral Proofs: The credential contains ZKPs of specific transaction patterns (e.g., "consistent monthly income > $5,000", "savings rate > 20%", "no overdrafts in 6 months")

   • Temporal Validity: Credentials include time-bound proofs reflecting the most recent analysis period

Key Benefits

• Granular Financial Underwriting: Lenders can assess income stability, spending habits, and financial responsibility based on actual transaction history without viewing sensitive spending details

• Pattern-Based AML Compliance: Platforms can detect money laundering patterns (structuring, rapid movement, suspicious counterparts) while preserving transaction privacy

• Behavioral Risk Assessment: Enables evaluation of financial habits and stability through verified patterns rather than self-reported information or single-point balance checks

• Cash Flow Verification: Provides proof of consistent income and responsible cash management for credit underwriting without exposing salary sources or employer information

• Category-Based Analysis: Allows verification of spending categories and financial behaviors while keeping specific merchants and payment details completely private

• Historical Trend Verification: Enables proof of improving financial habits or long-term stability through multi-period analysis

Use Cases to Benefit

• Income Verification & Mortgage Underwriting. DeFi real estate platforms and traditional lenders can verify stable income history and responsible financial behavior for mortgage applications without requiring pay stubs or tax returns.

• Small Business Lending. Business lenders can assess cash flow stability, revenue patterns, and financial health through transaction history analysis while protecting sensitive business counterparty information.

• Subscription Service Risk Assessment. High-value subscription services and membership platforms can verify financial stability and payment capability through transaction pattern analysis.

• Employment & Contractor Screening. Companies can verify financial stability and income history for employment screening, particularly for remote workers and contractors where traditional verification is challenging.

• Regulatory Compliance Reporting. Financial institutions can demonstrate transaction monitoring compliance to regulators by proving they detect suspicious patterns while maintaining customer privacy.

• Financial Health Products. Fintech applications can provide personalized financial advice and products based on verified transaction patterns without continuously monitoring user transactions.

• Insurance Underwriting. Insurance companies can assess financial stability and risk profiles through transaction behavior analysis for customized premium pricing.

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Pricing & Integration

Drop us a line at [email protected] and let’s kick things off!