Finvest Advisor

Finvest Advisor Landing Page

Inspiration

Our project was inspired by the movie recommendation system algorithms used by companies like Netflix to recommend content to their users. Following along on this, our project uses a similar algorithm to recommend investment options to individuals based on their profiles.

What Finvest Advisor does

This app suggests investment options for users based on the information they have provided about their own unique profiles. Using machine learning algorithms, we harness the data of previous customers to make the best recommendations that we can.

How it works

We built our web app to work together with a machine-learning model that we designed. Using the cosine similarity algorithm, we compare how similar the user's profile is compared to other individuals already in our database. Then, based on this, our model is able to recommend investments that would be ideal for the user, given the parameters they have entered

Our biggest challenge

Acquiring the data to get this project functional was nearly impossible, given that individuals' financial information is very well protected and banks would (for obvious reasons) not allow us to work with any real data that they would have had. Constructing our database was challenging, but we overcame it by constructing our own data that was modelled to be similar to real-world statistics.

Going forward...

We hope to further improve the accuracy of our model by testing different kinds of algorithms with different kinds of data. Not to mention, we would also look forward to possibly pitching our project to larger financial firms, such as local banks, and getting their help to improve upon our model even more. With access to real-world data, we could make our model even more accurate, and give more specific recommendations.