SharkFin

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  Bank account access landing page

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  This is an example of how we analyze the user's habits to give them recommendations to save money.

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  Sentiment analysis of social media can be used to indicate to the user certain spending habits that may be affecting their online presence.

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  We use a combination of API's to figure out where the user can enact recurring, necessary purchases at a cheaper cost.

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  Our program identifies exactly which local supermarket or store where a user can buy a certain item for cheaper.

Inspiration

Too many times have broke college students looked at their bank statements and lament on how much money they could've saved if they had known about alternative purchases or savings earlier.

What it does

SharkFin helps people analyze and improve their personal spending habits. SharkFin uses bank statements and online banking information to determine areas in which the user could save money. We identified multiple different patterns in spending that we then provide feedback on to help the user save money and spend less.

How we built it

We used Node.js to create the backend for SharkFin, and we used the Viacom DataPoint API to manage multiple other API's. The front end, in the form of a web app, is written in JavaScript.

Challenges we ran into

The Viacom DataPoint API, although extremely useful, was something brand new to our team, and there were few online resources we could look at We had to understand completely how the API simplified and managed all the APIs we were using.

Accomplishments that we're proud of

Our data processing routine is highly streamlined and modular and our statistical model identifies and tags recurring events, or "habits," very accurately. By using the DataPoint API, our app can very easily accept new APIs without structurally modifying the back-end.

What we learned

What's next for SharkFin

Built With

• viacom-datapoint-api
• node.js
• javascript
• express.js