AI-Powered Banking Assistant 🚀

Inspiration 💡

Banking should be inclusive, accessible, and intuitive for everyone, regardless of physical abilities or location. Imagine a user who is blind, uses a wheelchair, or lives in a remote area—our solution provides them with a voice-enabled AI assistant to simplify their banking experience. The goal is to break barriers and ensure seamless financial management for all.

What It Does 🏦

Provides a conversational AI bot to manage finances via voice, enabling hands-free and effortless interactions.
Allows users to book appointments with their banker remotely, saving time and effort.
Helps users save for specific goals (e.g., $300 monthly for a new car) by analyzing spending patterns and suggesting actionable savings plans.
Offers a centralized hub for all banking features directly on a mobile device.
Enables users to explore and apply for credit cards, with personalized recommendations based on their financial data.
Provides detailed transaction insights and categorization for better financial awareness.

How We Built It 🛠️

Backend: Developed a Retrieval-Augmented Generation (RAG) system leveraging OpenAI’s text-embedding-ada-002 model to embed financial transactions and efficiently retrieve relevant data using ChromaDB.
Voice Interaction: Integrated Text-to-Speech (TTS) and Speech-to-Text (STT) libraries to create an accessible voice assistant.
Savings Advisor: Used AI-powered analysis to identify spending patterns and provide tailored financial advice.
Mobile App: Built using React Native for a smooth, cross-platform user experience.
Tech Stack: Python, OpenAI API, ChromaDB, Flask for backend services, and React Native for frontend development.

Challenges We Ran Into ⚡

Optimizing embeddings for a mix of structured (transactions) and unstructured (natural language queries) financial data.
Handling complex queries like "How can I save for a $15,000 vacation in 18 months?" and generating actionable responses.
Ensuring real-time performance while maintaining API rate limits for large datasets.
Seamlessly integrating accessibility features for blind and visually impaired users.

Accomplishments That We’re Proud Of 🎉

Created a fully functional AI banking assistant prototype in under 48 hours.
Designed a savings advisor that delivers personalized and actionable financial insights.
Successfully implemented accessibility features for users with disabilities.
Provided a one-stop solution for all banking needs using state-of-the-art AI and voice technologies.

What We Learned 📚

How to integrate multiple AI systems (RAG, TTS, STT) into a single cohesive solution.
The importance of inclusivity in financial applications and designing for accessibility.
Techniques for optimizing embeddings and ensuring consistent performance for large datasets.

What’s Next for AI-Powered Banking Assistant 🚀

Enhanced Accessibility: Expand support to include more languages, dialects, and regional banking features.
Advanced Budgeting Tools: Introduce advanced features like customizable budgeting goals, loan calculators, and automated expense tracking.
Secure Banking: Implement advanced security measures, including voiceprint authentication and encrypted data handling.
Financial Literacy: Add educational modules to improve users’ understanding of personal finance and investment options.

Built With 🛠️

Python: Backend development and AI processing.
OpenAI API: For embeddings and advanced language understanding.
ChromaDB: Vector database for efficient RAG implementation.
Flask: Backend API and service orchestration.
React Native: Mobile app frontend for cross-platform compatibility.
Text-to-Speech and Speech-to-Text: Accessibility features for voice-based interactions.