zLend：一种用于链上信贷承销的双范围现金流重构框架
zLend: A Dual-Scope Cash-Flow Reconstruction Framework for On-Chain Credit Underwriting
- Zeru AI（泽鲁人工智能公司）
- Ohio State University（俄亥俄州立大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
zLend是一种已部署的链上信贷承销框架，通过双范围现金流重构技术解决去中心化借贷的信用评估问题，其层级分配由参考贷款规模主导，已用于实际借贷决策。
AI中文摘要：
去中心化借贷缺乏信用局：借款人的还款能力必须完全从公开链上活动中推断，无需收入验证或负债记录。本文提出zLend，一种已部署的现金流承销框架，该框架从原始代币转账中重构钱包的每日余额历史，并从中推导短期还款能力信号。该重构针对每个钱包执行两次：一次限于固定稳定币篮子，另一次覆盖所有可替代代币转账，前提是钱包的总代币持有量与其可流动的可支出余额是不同的量，将二者混同会导致风险定价错误。从每个序列中，我们推导针对固定贷款规模的流动性覆盖率、现金流波动性与规律性、一种改编自量化金融的回撤与恢复统计量，以及仅通过转账时间识别类薪资支付节奏的 recurring-counterparty（ recurring-counterparty检测器）。随后比较两种视角：总持有量巨大但稳定币储备极少覆盖贷款规模的钱包会被标记为流动性错配，与其总财富无关。我们正式指定该流水线，记录用于验证跨语言生产迁移至数值容差1e-9的黄金主方法，并通过与已部署系统的参考夹具完全一致（78个现场断言中的78个）的独立重新实现，表征层级函数的参数敏感性。层级分配主要由参考贷款规模决定，6个参考钱包中有4个在贷款规模从10美元变为25000美元时改变层级；回撤与覆盖标准作用于互不重叠的钱包，因此二者互不包含；且层级规则中没有任何标准是无效的。zLend已部署在生产环境中，通过第三方API集成为实际借贷决策提供信息。
英文摘要：
Decentralized lending lacks a credit bureau: a borrower's capacity to repay must be inferred entirely from public on-chain activity, without income verification or a liability record. This paper presents zLend, a deployed cash-flow underwriting framework that reconstructs a wallet's daily balance history from raw token transfers and derives short-duration repayment-capacity signals from it. The reconstruction is performed twice per wallet, once restricted to a fixed stablecoin basket and once over all fungible transfers, on the premise that a wallet's total token holdings and its liquid, spendable balance are distinct quantities whose conflation misprices risk. From each series we derive liquidity coverage against a fixed loan size, cash-flow volatility and regularity, a drawdown-and-recovery statistic adapted from quantitative finance, and a recurring-counterparty detector that identifies salary-like payment cadence from transfer timing alone. The two views are then compared: a wallet with large aggregate holdings whose stablecoin reserve rarely covers the loan size is flagged as a liquidity mismatch irrespective of total wealth. We specify the pipeline formally, document the golden-master methodology used to verify a cross-language production migration to numerical tolerance 1e-9, and characterize the tier function's parameter sensitivity with an independent reimplementation validated to exact agreement (78 of 78 field assertions) against the deployed system's reference fixtures. Tier assignment is governed predominantly by the reference loan size, with four of six reference wallets changing tier across loan sizes from USD 10 to USD 25,000; the drawdown and coverage criteria bind on disjoint wallets, so neither subsumes the other; and no criterion in the tier rule is inert. zLend is deployed in production, informing real lending decisions via third-party API integrations.
