Sequential fundraising in two sided online platforms enable peer to peer lending by sequentially bringing potential contributors, each of whose decisions impact other contributors in the market. However, understanding the dynamics of sequential contributions in online platforms for peer lending has been an open ended research question. The centralized investment mechanism in these platforms makes it difficult to understand the implicit competition that borrowers face from a single lender at any point in time. Matching markets are a model of pairing agents where the preferences of agents from both sides in terms of their preferred pairing for transactions can allow to decentralize the market. We study investment designs in two sided platforms using matching markets when the investors or lenders also face restrictions on the investments based on borrower preferences. This situation creates an implicit competition among the lenders in addition to the existing borrower competition, especially when the lenders are uncertain about their standing in the market and thereby the probability of their investments being accepted or the borrower loan requests for projects reaching the reserve price. We devise a technique based on sequential decision making that allows the lenders to adjust their choices based on the dynamics of uncertainty from competition over time. We simulate two sided market matchings in a sequential decision framework and show the dynamics of the lender regret amassed compared to the optimal borrower-lender matching and find that the lender regret depends on the initial preferences set by the lenders which could affect their learning over decision making steps.

翻译：双边在线平台中的顺序募资机制通过按序引入潜在贡献者实现P2P借贷，每个贡献者的决策都会影响市场中其他贡献者。然而，理解在线P2P借贷平台中顺序贡献的动态机制一直是一个开放性的研究问题。这些平台的集中投资机制使得借款人难以在任何时间点理解其面临的由单一贷款人造成的隐性竞争。匹配市场是一种代理配对模型，其中交易双方基于偏好的配对选择能够实现市场去中心化。我们研究当投资者或贷款人面临基于借款人偏好的投资限制时，双边平台中使用匹配市场的投资设计。这种情况在现有借款人竞争之外，还形成了贷款人之间的隐性竞争——特别是当贷款人无法确定自身市场地位，从而难以判断其投资被接受的概率或借款人项目贷款请求能否达到保留价格时。我们提出一种基于顺序决策的技术，使贷款人能够根据竞争带来的动态不确定性随时间调整选择。我们在顺序决策框架中模拟双边市场匹配，展示贷款人相对于最优借贷匹配的累积遗憾动态，发现贷款人的遗憾取决于其设定的初始偏好，而这些偏好会影响他们在决策步骤中的学习过程。