Fintech app development (React/Python) with CAMS & KFintech data parsing

FINTECH2026 We are seeking a full-stack developer or agency to build a secure, multi-tenant B2B wealth-tech SaaS platform for Indian mutual fund advisors. The core backend requires an automated ingestion and decryption pipeline using tools like Python, Pandas, and worker queues to parse daily CAMS and KFintech mailback files including Folio Master, Transaction feeds, and Daily NAV updates. The platform must feature a high-precision calculation engine to compute total portfolio valuations, asset allocations, and exact XIRR for irregular, multi-date transaction flows using a strict FIFO method for partial redemptions. The database architecture must implement absolute multi-tenant data isolation via a mandatory tenant_id structure to fully eliminate cross-advisor data leaks while offering white-label customizations such as custom subdomains, primary/secondary colors, and advisor branding. For investors, the system requires a mobile-responsive portal featuring passwordless login via PAN and mobile OTP through local Indian gateways, multi-PAN family grouping capabilities, and detailed FIFO-based Short-Term and Long-Term Capital Gains tax reporting. For advisors, the administrative web panel must provide macro-level business insights tracking firm-wide AUM growth, net capital inflows or outflows, and an active SIP monitor to identify upcoming renewals or missed/bounced payments. The preferred technology stack includes React/Next.js for web administration, Flutter or React Native for the client app, and a robust PostgreSQL database with historical time-series extensions. In your proposal, please summarize your direct experience with wealth-tech architectures, your technical strategy for scaling complex XIRR database math, your familiarity with CAMS/KFintech file layouts, and a rough timeline to deploy a functional core Minimum Viable Product.