Cyber Vigilante

To combat identify theft, a model was trained through machine learning by analyzing over 300,000 datasets. The model is ~94% accurate in detecting fraud when submitting a bank account application.

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Inspiration

To combat bank account fraud through machine learning and AI

What it does

The application trains a model through machine learning for institutions to detect bank account fraud

How we built it

Backend: Django/Flask
Frontend: React

Challenges we ran into

Some challenges we ran into were finding appropriate datasets, training a model, and learning new technologies

Accomplishments that we're proud of

Our model is ~94% accurate and can help institutions fight bank account fraud

What we learned

We learned how to integrate React with Django/Flask, how to train a machine learning model, and how to use Azure as a machine learning platform

What's next for Cyber Vigilante

As a machine learning model, the software will continue to improve its accuracy with the analysis of more and more datasets

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