Context-Aware Form Completion Helper for Banking Paperwork

Added Nov 2025 3 design docs

Banking paperwork defeats a surprising number of applicants: forms ask for nomination details, occupation codes, and declarations that first-time customers do not understand, and errors mean rejected applications and repeat branch visits. An assistant that explains each field and suggests appropriate entries removes a real barrier to access. The intern builds the assistant as a streamlit application in python. Common banking form templates, along with field-by-field guidance, are embedded and stored in a vector database. When a user selects a form, such as an account opening or nomination form, a retrieval-augmented generation pipeline retrieves the matching template and its guidance, and generative AI produces context-aware help: what each field means, what a valid entry looks like, and suggestions based on the user's described situation. The interface walks through the form section by section, with RAG keeping every suggestion tied to the actual template rather than generic advice. The project introduces template retrieval, contextual suggestion generation, and assistive interface design, and shows the intern how AI plus retrieval can be packaged into a genuinely helpful consumer-facing banking tool.

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