# Scaling
In order to bootstrap and scale 3Jane’s unsecured credit marketplace without sacrificing risk discipline, we’re running the protocol through a deliberately sequenced flywheel. Each loop tightens our underwriting, boosts creditor confidence, unlocks progressively larger credit capacity, and compresses credit spreads.
**Phase 1 – 3CA Data Tuning**\
Initially, we ingest granular Credit Karma data from early participants to refine the 3CA underwriting algorithm. This data allows us to recalibrate probability-of-default bands and credit limit LTV's, ensuring that 3CA integrates conventional bureau metrics with on-chain behavioral indicators. As a result, robust probability-of-default (PD) curves and loss-given-default (LGD) are established before any capital is deployed.
**Phase 2 – Open USD3 / sUSD3 Deposits**\
Once the underwriting framework has been calibrated, the pool is opened to suppliers. Depositors receive USD3 (or sUSD3), and begin accruing yield immediately from Aave. Smart-contract safeguards, including per-asset LTV ceilings, automated circuit breakers, and real-time utilization throttles, constrains tail risk as the protocol demonstrates its net-interest-spread capture.
**Phase 3 – Extend Credit Unsecured**\
As the protocol opens to new merchants, we extend an initial tranche of unsecured credit lines to a curated cohort of high-signal wallets. Performance data such as repayments, delinquencies, and defaults feeds directly into 3CA, where it is used to re-estimate probability-of-default curves, recalibrate loss-given-default assumptions, and fine-tune credit limit parameters on a rolling basis.
**Phase 4 - Leveraged Scaling (Repeat Phase 1)**
With each completed vintage, two reinforcing effects materialize. (1) Credit-data flywheel**.** Newly observed repayments, delinquencies, and defaults are ingested into 3CA, enabling the model to re-estimate probability-of-default curves, adjust loss-given-default assumptions, and tighten credit limit parameters. The richer the dataset, the smaller the model-error buffer required. (2) Rate-compression flywheel**.** As empirical default rates remain below the levels priced into earlier cohorts, 3CA can justify narrower risk spreads and modestly higher pull-to-value ceilings. Lower all-in cost of capital broaden the addressable merchant base, lifting utilization and generating yet more performance data. Simultaneously, the publication of low realized PDs and a growing first-loss reserve demonstrates asset quality to the market, attracting additional USD3 & sUSD3 deposits and deepening the liquidity cushion.
Rinse, refine, repeat. The flywheel ensures 3Jane grows credit volume only as fast as our data proves we can underwrite it.
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