Us studying over a million cases of fraud and illegal money laundering going on in society and that we realized that there actually is no real solution that is currently out on the market that solves this issue. We decided that the time is now and that our app will put an end to this problem.
What it does
It is an IOS app that uses Machine Learning, Neural Networks, and a device’s camera to keeps track of transactions of the user. It not only tracks the transactions, it shows exactly where the user spent money, that is, on a map. Furthermore, the user sets pinpoints on locations he or she visits or spends at a regular basis. Thus, when the app detects a transaction at an unknown or “un-pinpointed” location, the app classifies this as fraud. It helps people be smart with their money and provides them with financial security as a result, too.
How I built it
We used Firebase as a database to store all the transactions as well as the locations of each event. We used Xcode and primarily used swift to do the app’s backend and front end. Then, we trained a model that shows whether or not the pin-points are following the “trend”, that is, the normalcy of the placement of the original pinpoints at the usual locations.
Challenges I ran into
Updating Firebase with the transactions and its corresponding locations. Furthermore, even more harder and time-consuming was training the model.
Accomplishments that I'm proud of
The Firebase getting updated with the correct transactions and the locations.
What I learned
How Firebase interacts with Xcode and that machine learning has an almost infinitesimal amount of applications, whether it be health or financial.
What's next for Bread
Make the map pin-pointing more accurate and extending our service to banks and other financial places, as our app would greatly reduce theft and money fraud.