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Development of an AI-Driven Financial Management Platform with Personalized Advisory Features

reenbit

Financial services

Information technology

Challenges in Personal Financial Management

Users struggle with fragmented financial data across multiple accounts, lack of personalized financial advice, and difficulty predicting future financial needs. Existing solutions fail to provide actionable insights for optimizing spending, savings, and investments.

About the Client

UK-based fintech startup specializing in AI-powered personal finance solutions

Goals for the Financial Management Platform

Centralize financial data from multiple sources into a unified dashboard
Implement AI-driven transaction categorization and spending pattern analysis
Develop personalized financial recommendations engine
Create interactive financial forecasting and goal planning tools
Establish secure, real-time data synchronization with financial institutions

Core System Functionalities

Multi-account data aggregation and visualization
AI-driven transaction categorization and habit analysis
Personalized budget optimization recommendations
Interactive financial forecasting with scenario modeling
Smart payment reminders and obligation tracking
Goal-based savings calculator with progress tracking
AI chatbot for financial advice and support

Technology Stack Requirements

.NET

Cosmos DB

Azure DevOps

ML.NET

OpenAI API

Azure OpenAI SDK

Semantic Kernel

RAG (Retrieval-Augmented Generation)

Ollama

System Integration Needs

Banking APIs (Open Banking/PSD2)
Payment gateway integrations
Push notification services
Third-party financial data providers

Performance and Security Requirements

High-availability architecture with 99.9% uptime
End-to-end encryption for financial data
Real-time data processing capabilities
GDPR and financial data compliance
Scalable infrastructure for growing user base

Expected Impact on Financial Management and User Empowerment

The platform will enable users to achieve 360-degree financial visibility, reduce overspending through AI insights, and improve savings rates by 25-40%. Financial forecasting tools will enhance long-term planning capabilities, while personalized recommendations will increase user financial literacy and decision-making confidence. The solution is expected to reduce financial stress for 70%+ of users within six months of adoption.