Fintelite

Fintelite is a Singapore-based intelligent process automation platform that streamlines loan application processing for financial institutions — using OCR document extraction, AI-powered bank statement analysis, and fraud detection to automate the manual document verification and credit assessment steps that slow down loan origination. Founded in 2021 by Nadia Amalia and Nadia Fadhila, Fintelite raised $815,000 from investors including the AI Institute for Progress and Global FinTech Hackcelerator, achieving $4.2 million in revenue in 2024 with a 20-person team.\n\nFintelite's platform processes loan applications by automatically extracting and structuring data from submitted documents (identity cards, pay slips, bank statements, tax returns), analyzing bank statement transaction patterns for income verification and financial behavior assessment, and flagging anomalies or inconsistencies that indicate potential fraud. This automation reduces loan processing time from days to hours and reduces the cost of underwriter labor for routine document verification. The system integrates with existing loan origination systems (LOS) used by banks and finance companies in Southeast Asia.\n\nIn 2025, Fintelite competes in the document AI and fintech automation market for Southeast Asian financial institutions alongside Ocrolus (US, bank statement analysis), Inscribe (fraud detection from financial documents), and regional document AI providers for automated lending document processing. Southeast Asia's rapidly growing digital lending market — driven by rising smartphone penetration, e-wallet adoption, and demand from the unbanked/underbanked population — creates strong demand for loan processing automation. Singapore's position as the region's fintech hub provides Fintelite with a strong launch market and access to regional financial institutions. The 2025 strategy focuses on expanding to more Southeast Asian markets (Indonesia, Malaysia, Philippines), deepening fraud detection models, and adding more document types to the automated processing capability.