時間：2022年10月15日（周六） 地點：騰訊會議
開幕式
時間：8:50-9:00
緻辭人：吳 溪教授（中央财經大學會計學院，院長）
主持人：王彥超教授（副院長）
論文報告
時間：9:00-10:00
報告1：The Bundled Design of Institutional Loan Deals — An Information Asymmetry Perspective
報告人：唐仕斌（多倫多大學）
摘要：Institutional (i.e., non-bank) lenders have become major funding providers in the leveraged loan market. Certain loan facilities — institutional facilities — are designed to primarily attract funding from institutional lenders. For these facilities, bank lenders still dominate the loan origination business, but often distribute their loan shares to institutional lenders in the secondary market. Predominantly assuming the role of participant lenders in syndicated loans, institutional lenders suffer from an information disadvantage relative to bank lenders. In this paper, I find that institutional facilities are more likely to be issued along with a bank facility (thus forming a loan package) when institutional lenders’ information concerns are greater. Such a bundling mechanism ensures that bank lenders have “skin in the game” at the loan package level. Further, within the same loan package, contractual terms for institutional versus bank facilities can differ.
時間：10:00-11:00
報告2：Regulating by New Technology: The Impacts of SEC Data Analytics on SEC Investigations
報告人：鄧恬（新加坡管理大學）
摘要：The use of data analytics has long been emphasized by the Securities and Exchange Commission (SEC) in recent years, while little is known about whether the investment in data analytics achieves its goal of improving enforcement efficiency. This study examines the effects of the SEC regional offices’ use of data analytics on the investigation outcomes. Consistent with data analytics helping the SEC identify the most suspicious case to investigate and facilitate the investigation process, I find that the SEC’s use of data analytics is associated with a 12% increase in the SEC investigation success rate. The improvement in success rate is larger for complex firms and for firms that are distant from the SEC regional offices. In addition, I find that firms are less likely to commit fraud after the SEC’s use of data analytics because of the higher perceived detection likelihood. The investigation time is shorter and the detected fraud is more severe after the SEC’s use of data analytics. Overall, the results provide evidence that the SEC’s use of data analytics increases SEC enforcement efficiency and deters firms’ fraud occurrence likelihood.
時間：11:00-12:00
報告3：How Banks Understand R&D Investments: The Case of Standards Setting Organizations
報告人：柯俊強（北京大學）
摘要：This paper examines a specific channel, Standards Setting Organizations (SSOs), through which banks can extract proprietary soft information to understand a borrower’s R&D investments and price-in that information in loan contract terms. Using a sample of bank loans issued to U.S. listed firms from 1996 to 2017, we find that firms newly joining an SSO can obtain more favorable loan terms from a bank that has previously lent to other firms in the same SSO than from other banks. This relationship is stronger when the borrower’s R&D is hard to interpret or earnings are hard to forecast. We also find that firms are more likely to borrow from these SSO-connected banks. Overall, our study demonstrates how proprietary R&D information that spills over through SSO connections helps mitigate information asymmetries in the lending process.
