Choosing and Evaluating P2P Lending with Value Engineering as a Decision Support System: An Indonesian Case Study

Peer-to-peer (P2P) lending has gained significant traction in the financial landscape, particularly in developing economies such as Indonesia, where access to traditional banking services remains a challenge for many. The aim of this study is to investigate the application of value engineering as a decision support system for choosing and evaluating P2P lending platforms, using Indonesia as a case study. P2P lending is a relatively new service in the digital economy for lending money to individuals through online financial intermediaries, where borrowers and lenders often have no prior relationship. Value engineering, a systematic approach to improving the value of a product or service, can be a valuable tool in the context of P2P lending. Through applying value engineering principles, P2P lending platforms can identify and prioritize the key factors that influence lending decisions, such as risk, return, and data privacy, to enhance the overall value proposition for both borrowers and lenders. Both value engineering and P2P lending are technoeconomic systems that aim to enhance the overall value and efficiency of a system or process, albeit through different approaches. This study presents a comprehensive framework for applying value engineering as a decision support system for P2P lending in Indonesia. The findings reveal that the value engineering index developed in this study effectively differentiates between P2P lending platforms based on their performance. Specifically, platforms with a high-value index were found to offer competitive interest rates, lower fees, and superior risk management, as evidenced by their non-performing loan (NPL) rates. In contrast, platforms with a low-value index were associated with higher NPLs and less favorable terms for stakeholders. These insights provide practical guidance for P2P lending platforms, regulators, and consumers; highlight the importance of a value engineering approach in optimizing platform selection; and enhance the P2P lending ecosystem's sustainability in Indonesia.