Optimal Design and Ownership Structures of Innovative Retail Payment Systems

In response to the Fintech trend, an ongoing debate in the banking industry is how to design the new-generation interbank retail payment and settlement system. We propose a two-stage analytical model that takes into account the value–risk tradeoff in the new payment system design, as well as banks’ participation incentives and adoption timing decisions. We find that, as the system base value increases, banks tend to synchronize their investment and adoption decisions. When the system base value is low and banks are heterogeneous, bank association ownership maximizes social welfare. When both the system base value and bank heterogeneity are moderate, government mandate leads to the socially optimal solution. When the system base value is high and banks are relatively homogenous, government ownership is socially optimal. We offer important policy implications regarding the optimal system design and the government regulator’s role in shaping the banking industry in future financial innovation

How to Enable Future Faster Payments? An Evaluation of a Hybrid Payments Settlement Mechanism

In the era of Fintech innovation and e-commerce, faster settlement of massive retail transactions is crucial for business growth and financial system stability. However, speeding up payments settlement can create periodic liquidity shortfalls to banks which would incur high cost of funds in the settlement process. We propose a new hybrid settlement mechanism design that integrates features of real-time gross settlement, deferred net settlement, and central queue management structure. The hybrid mechanism is managed by an intermediary and is particularly suitable to settle large volume of small-value retail payments. We evaluate the mechanism using computer experiments and simulation. We find that central-queue netting is an effective means to achieve high system performance. Our results also show that the intermediary plays an important role in coordinating multilateral central-queue netting and supplying liquidity as needed to banks. We offer some policy insights into future faster payments settlement mechanism design and implementation

An Economic Analysis of Disintermediation on Crowdfunding Platforms

Prosocial crowdfunding platforms can work through direct peer-to-peer (P2P) lending or through intermediaries, incurring different costs to borrowers and lenders. This study investigates the incentives of lenders and borrowers’ and how they would choose between the two types of platforms. We model the intermediary as a profit maximizer who filters projects, provides high quality borrowers with access to the platform, and ensures repayment rate to lenders. Our initial findings suggest that the introduction of direct P2P lending platform enables the intermediary to reduce its interest rate and to raise its screening threshold on the intermediated platform. The P2P lending platform also incentivizes more altruistic lenders to shift to the direct funding platform, which enables riskier borrowers to get funded. These findings suggest that the introduction of disintermediated P2P platform improves social welfare on the prosocial crowdfunding platforms

Personalized Recommendation for Balancing Content Generation and Usage on Two-Sided Entertainment Platforms

Online entertainment platforms such as Youtube host a vast amount of user-generated content (UGC). The unique feature of two-sided UGC entertainment platforms is that creators’ content generation and users’ content usage can influence each other. However, traditional recommender systems often emphasize content usage but ignore content generation, leading to a misalignment between these two goals. To address the challenge, this paper proposes a prescriptive uplift framework to balance content generation and usage through personalized recommendations. Specifically, we first predict the heterogeneous treatment effects (HTEs) of recommended contents on creators’ content generation and users’ content usage, then consider these two predicted HTEs simultaneously in an optimization model to determine the recommended contents for each user. Using a large-scale real-world dataset, we demonstrate that the proposed recommendation method better balances content generation and usage and brings a 42% increase in participants’ activity compared to existing benchmark methods

An Economic Analysis of Consumer Learning on Entertainment Shopping Websites

Online entertainment shopping, normally supported by the pay-to-bid auction mechanism, represents an innovative business model in e-commerce. Because the unique selling mechanism combines features of shopping and online auction, consumers expect both monetary return and entertainment value from their participation. We propose a dynamic structural model to analyze consumer behaviors on entertainment shopping websites. The model captures the consumer learning process, based both on individual participation experiences and also on observational learning of historical auction information. We estimate the model using a large data set from an online entertainment shopping website. Results show that consumers’ initial participation incentives mainly come from a significant overestimation of the entertainment value and an obvious underestimation of the auction competition. Both types of learning contribute to a general decreasing participation trend among consumers over time. Our model provides both a theoretical explanation and empirical evidence of the consumer churn issue. It further identifies two groups of consumers with different risk characteristics: One group is risk-averse and quits using the website before effective learning takes place, while the other group exhibits risk-seeking behavior and overly commits to the auction games. Based on the estimated parameters of the model, we perform counterfactual analyses to evaluate the effects of policy changes on consumers’ participation behaviors. We discuss several important design implications and recommend strategies for building a sustainable business model in the entertainment shopping industry