AL-AMIN (Algorithmic Learning and Automated Monitoring): Strategi Mitigasi Moral Hazard Fintech Syariah Melalui Integrasi API Point of Sales dalam Kerangka Triple Helix
DOI:
https://doi.org/10.30595/jesh.v4i1.473Keywords:
Fintech Syariah, Moral Hazard, Artificial Intelligence, AL-AMIN, Triple HelixAbstract
Pertumbuhan Islamic Fintech di Indonesia menghadapi paradoks fundamental: meskipun akses pembiayaan meluas, adopsi akad berbasis bagi hasil (Mudharabah) mengalami stagnasi akibat tingginya risiko pembiayaan. Akar permasalahannya adalah defisit kepercayaan (trust deficit) yang dipicu oleh asimetri informasi, di mana mitra UMKM memiliki peluang melakukan moral hazard melalui praktik double bookkeeping (pembukuan ganda) untuk memanipulasi laporan bagi hasil. Metode mitigasi konvensional terbukti inefisien dalam memvalidasi integritas laporan keuangan UMKM secara real-time. Penelitian ini bertujuan merekonstruksi model pengawasan fintech syariah menggunakan metode kualitatif deskriptif dengan pendekatan conceptual model building. Hasil penelitian merumuskan inovasi sistem AL-AMIN (Algorithmic Learning and Automated Monitoring). Sistem ini mengintegrasikan tiga lapisan teknologi pertahanan: (1) Integrasi API Point of Sales (POS) sebagai instrumen validasi arus kas digital (single source of truth); (2) AI Anomaly Detection yang berfungsi sebagai auditor cerdas untuk mendeteksi ketidakwajaran korelasi antara data stok inventori dan volume penjualan; serta (3) Smart Contract untuk otomasi distribusi bagi hasil. Keberlanjutan sistem diperkuat melalui kerangka Triple Helix, dimana OJK berperan dalam manajemen blacklist nasional dan DSN-MUI memberikan legitimasi sanksi syariah (taqsir). Implementasi AL-AMIN diharapkan mampu mentransformasi ekosistem fintech dari trust-based menjadi data-driven trust, mewujudkan iklim investasi yang transparan, aman, dan sesuai prinsip syariah.
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