This research addresses issues related to the debt relationship in the peer-to-peer lending scheme in Indonesia, focusing on creditors' rights to file for bankruptcy against debtors and the concept of an insolvency test. In the context of technological advancements, peer-to-peer lending serves as a digital solution for the interaction between debtors and creditors. Despite providing an efficient alternative, this scheme is not without risks, especially when debtors are unable to repay their debts. Concerns arise regarding whether aggrieved creditors can directly file for bankruptcy without adequate assessment of the debtor's assets. The insolvency test concept is crucial to prevent premature bankruptcy decisions. This research employs legal research methods with literature, historical, and artificial intelligence (AI) approaches. Through literature analysis, legal regulation evaluations, and historical approaches, the study aims to understand the norms, principles, and legal aspects involved in peer-to-peer lending bankruptcy. AI and machine learning are utilized for analyzing large datasets related to bankruptcy cases, while natural language processing expedites the analysis of legal regulation texts and related documents. The research results discuss the development of bankruptcy laws in Indonesia and the regulation of peer-to-peer lending. It is argued that a profound understanding of creditor rights, insolvency tests, and the dynamics of the peer-to-peer lending scheme is essential in developing legal policies that align with technological advancements and societal needs.