AI-Driven Personal Finance Advisor Increased User Satisfaction by 42%
A fintech company specializing in personal finance management.
- Duration10 months
- Team9 engineers
- CompanyFinance management services
- IndustryFintech
Project Goal
With a diverse clientele ranging from savvy investors to those new to personal finance, the company aimed to democratize financial advice, making it accessible and actionable for all. They came to us with the idea of an AI-driven personal finance advisor. The feature needed to provide personalized investment recommendations and financial education tailored to each user's unique profile.
The Challenge
- Data Security & PrivacyThey needed a solution to personalize financial advice without compromising sensitive user data, a critical requirement in the fintech sector.
- Regulatory ComplianceOperating across multiple regions meant facing a patchwork of financial regulations. Staying compliant without slowing down innovation was a key concern.
- System IntegrationTo make the AI advisor truly useful, it had to connect smoothly with a range of external financial systems, like banks or investment platforms, without creating friction or downtime.
Our Solution
To address the identified challenges, we involved a team of 9 professionals: 1 Project Manager, 2 AI/Machine Learning Engineers, 2 Data Scientists, 2 Backend Developers, 1 Frontend Developer, and 1 QA Engineer.
What We Did
Personalized Investment Recommendations
Utilizing ML (machine learning) to analyze individual financial data, market trends, and economic indicators, offering users tailored advice on saving, investing, and debt management.
Enhanced Financial Education
Integrated an educational component that adapts to each user's understanding and interests, promoting financial literacy through interactive content and personalized learning paths.
Data Security and Privacy Measures, Regulatory Compliance
Implemented encryption and data anonymization techniques, and designed the platform with a deep understanding of financial regulations, ensuring the provided advice is compliant with current laws and guidelines.
Business Impact
- 01 - 42% Increase in User Satisfaction- Personalized financial advice significantly improved the user experience. 
- 02 - High Engagement & Longer Sessions- Interactive educational content boosted user engagement and time spent on the platform. 
- 03 - Trust Built In- End-to-end encryption, anonymized data, and region-aware compliance strengthened user confidence, making security and privacy a visible product feature. 
- 04 - High Retention & Repeat Use- Innovative, goal-based planning and dynamic content delivery kept users coming back, driving long-term value for the business. 
Technologies Used
Development
- .NET 
- React 
- React Native 
Predictive Analytics
- TensorFlow 
- PyTorch 
Natural Language Processing
- OpenAI's GPT 
Integrations
- Mulesoft 
Payment System
- Adyen 
- Stripe 
- CyberSource 
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