讲座题目：Dynamic Trade Finance in the Presence of Information Frictions and FinTech
张宇轩，清华大学工业工程系管理科学与工程博士，即将加入对外经济贸易大学信息学院为助理教授。主要研究领域为供应链金融、金融科技与可持续性运营管理。研究工作已被国际一流学术期刊接收或修改后在审，如Naval Research Logistics，Manufacturing & Service Operations Management。曾获清华大学未来学者奖学金、北京市优秀毕业生等荣誉称号。
We study the value of a type of innovative bank-intermediated trade finance contract, which we call dynamic trade finance (DTF, under which banks dynamically adjust loan interest rates as an order passes through different steps in the trade process) in the presence of information frictions related to process uncertainties, and its strategic interaction with FinTech. We construct a parsimonious model of a supply chain process consisting of two steps: the duration of each step is uncertain, and the process may fail at either step. The seller borrows from a bank to finance this 2-step process either through uniform financing (the interest rate remains constant over the process) or DTF (the interest rates are adjusted as the process passes each step). While lending, the bank faces either ex-post information opacity (the bank may experience a time delay to verify information about the order's passing of a step) or ex-ante information asymmetry (the seller possesses more accurate information about the trade process than the bank). FinTech may help to alleviate such information frictions. We find that the value of DTF increases as the trade process becomes more reliable or lengthier. The severity of ex-post information opacity hurts the value of DTF convexly. FinTech that enables speedy information verification and automatic execution complements DTF. In the presence of ex-ante information asymmetry, DTF enables separating the more reliable sellers from the less so ones, and hence, substitutes FinTech that alleviates information asymmetry. Our results shed light on how the underlying trade process dynamics and the type of information frictions involved affect the optimal deployment of contract innovations (DTF) and FinTech in trade finance.