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III. The DreamPass Architecture

Core Strategy: Data Before Capital

Traditional approach:

1. Raise money for lending
2. Spend heavily on customer acquisition
3. Hope you attract creditworthy borrowers

DreamPass approach:

1. Give users valuable AI tool (free)
2. Build comprehensive financial dataset (consensual)
3. Launch lending when you have meaningful data

Phase 1: The AI Copilot (NOW - Recently Launched)

Free financial assistant that:

  • Connects to bank accounts (via Plaid)
  • Analyzes spending patterns
  • Finds subscription waste
  • Provides bill negotiation scripts
  • Offers personalized financial guidance

Why users care: Many save $50-150/month on average (subscription cuts, bill negotiations)

Why this matters strategically:

  1. Zero CAC: Users join for value, not because we marketed to them
  2. Natural selection: Financially engaged users are better credit risks
  3. Data advantage: Build comprehensive financial behavior dataset
  4. Trust foundation: Prove value before asking for trust with loans

Reality check on user economics:

  • Not everyone saves $150/month
  • Results vary by user's financial situation
  • Some users save nothing (already optimized)
  • But enough save enough to create viral growth

Phase 2: Reputation Layer (Q4 2025 - Q1 2026)

Zero-knowledge proof system:

User generates cryptographic badges locally:
├─ "3-month emergency fund" (verifiable)
├─ "12-month payment streak" (verifiable)
├─ "Reduced debt 30% in 6 months" (verifiable)
└─ "Top quartile savings rate vs peers" (verifiable)

Badges are:
├─ Cryptographically verifiable
├─ User-controlled (can revoke)
├─ Time-stamped (expire if not maintained)
└─ Portable (work across protocols)

DreamPass Credit Score:

  • Considers 100+ signals (vs FICO's 5 categories)
  • Updates in real-time (vs FICO's monthly)
  • Fully transparent (show exactly what matters)
  • Users can see how to improve

Reality check:

  • More signals ≠ automatically better predictions
  • Need to validate against actual default data
  • Will start conservatively, improve over time
  • Regulatory approval required for actual lending use

Phase 3: Lending Protocol (Q2-Q3 2026)

Smart contract-based lending:

Loan Application

AI + Traditional Underwriting (hybrid approach initially)
├─ DreamPass Score (behavior data)
├─ Traditional credit check (FICO/bureau data)
├─ Income verification
└─ Risk pool assignment

Rate Calculation (transparent formula)

User Accepts Terms

Smart Contract Deployment
├─ Terms encoded on-chain
├─ Payment automation
└─ Transparent to community

Funds Transfer (stablecoin → fiat via Circle/Bridge)

Pricing structure (transparent):

Your APR = Base + Risk + Insurance + Operations

Base Rate: 5-7% (cost of capital, varies with markets)
Risk Premium: 4-10% (based on credit assessment)
Insurance Pool: 1-2% (default protection)
Operations: 0.5-1% (actual costs, no profit margin)
─────
Target Range: 12-20% (vs typical 20-30% for similar credit)

Note: These are target ranges. Actual rates will be
determined by market conditions, regulatory requirements,
and actual default experience.

Three risk pools:

Conservative Pool (DreamPass Score: 700+)

  • Target default rate: 1-2%
  • Insurance premium: 1.0%
  • Typical APR range: 12-15%
  • Features: Larger loans, longer terms, rate reduction opportunities

Balanced Pool (DreamPass Score: 640-699)

  • Target default rate: 3-5%
  • Insurance premium: 1.5%
  • Typical APR range: 15-18%
  • Features: Standard terms, clear path to Conservative pool

Growth Pool (DreamPass Score: 600-639)

  • Target default rate: 6-8%
  • Insurance premium: 2.0%
  • Typical APR range: 18-22%
  • Features: Smaller loans, shorter terms, intensive support

Reality check:

  • These ranges are estimates based on traditional lending data
  • Actual rates will depend on cost of capital, defaults, regulations
  • We may not be able to beat all competitors on rate
  • Our advantage is transparency + alignment, not necessarily lowest APR
  • Initial loans will likely be at higher end of ranges (risk management)