Budegtly

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  Architecture diagram

Inspiration

Many teens and adults struggle with managing their personal finances due to a lack of financial education, impulsive spending habits, and the absence of disciplined saving and investing routines. Teens often do not understand basic saving concepts and spend without limits, while adults find it hard to stick to planned budgets and develop long-term saving habits. This leads to financial stress and missed opportunities for wealth building. Existing finance apps either lack personalised guidance or fail to engage users effectively in developing healthy money habits.

What It Does

This solution leverages AI to automate financial insights, educates users on smart financial habits, and empowers them to save and invest wisely — making financial discipline easier and accessible for your audience. The assistant will: • Automatically categorise user expenses to provide a clear understanding of where money is spent. • Predict upcoming bills to help users plan better and avoid missed payments. • Suggest personalised savings options based on user income, spending, and goals, encouraging disciplined money management. • Generate monthly reports with summaries of expenditure and progress toward savings goals. • Offer financial education and tips to improve users' financial literacy gradually. • Prioritise security by ensuring all sensitive data (bank info, transactions) is encrypted and access-controlled. • Target busy earning employees and teens who need simple, effective tools to track and improve their personal finances.

How We Built It

User Interface (Frontend):

• Delivered via a web or mobile app hosted on AWS Amplify, the interface provides users with easy access to personalised dashboards, expense tracking, bill reminders, savings goals, and educational content. • It supports multiple languages and voice interaction for better accessibility.

Backend Services:

• Built largely on AWS Lambda for serverless compute, this layer implements core logic including expense categorisation, bill prediction, and financial advice generation. • The backend integrates with AI services (such as Amazon Bedrock and Lex) for natural language processing, personalised recommendations, and chatbot capabilities. Authentication and authorisation are managed using Amazon Cognito, ensuring secure user access.

Data Management and Security:

• User financial data, transaction history, and reports are stored securely using Amazon DynamoDB and S3, with encryption managed by AWS KMS. • Strict access controls are enforced via AWS IAM to protect sensitive information. • Monitoring and logging through Amazon CloudWatch ensures operational visibility and security auditing.

AI and ML Integration

• The system employs predictive modelling and machine learning to analyse spending habits, forecast upcoming bills, and tailor saving suggestions. NLP facilitates user queries via chatbot and voice assistant, enhancing user engagement and education.

Challenges We Encountered

During the development process, we faced several challenges, including integrating different features and ensuring the accuracy of expense tracking. We found it difficult to use AWS services as beginners. We hope to grasp efficient knowledge in the future.

Accomplishments We're Proud Of

We are proud of successfully creating a functional prototype.

What We Learned

Throughout this project, we learned valuable lessons about teamwork, effective communication, and the importance of user testing.

What's Next for Budegtly

Moving forward, we plan to enhance the system with additional features based on user feedback and explore potential partnerships for wider distribution.

Built With

• css3
• html5
• typescript