FinancePlanner

Inspiration

The inspiration for this product was when a majority of the team was required to complete the Economics Personal Finance class online. We realized that even though we would be learning the skills by practicing the skill over and over again, we decided that building a program that completed the same task would enforce our learning even more.

What it does

It allows for people to easily plan out their future purchases and resource allocation for the next year. It takes into account spouse, # of children, and recurring and one-off payments to more accurately predict the best time to order the item(s) in question. It has a log-in page and stores customer data in the program itself, therefore eliminating the need for cookies or cache.

It allows for people to easily plan out their future purchases and resource allocation for the next year. It takes into account spouse and their salary, # of children, and recurring and one-off payments to more accurately predict the best time to order the item(s) in question. It has a log-in page and stores customer data with a unique method that eliminates the need for cookies or cache.

How we built it

FinancePlanner was built around the Google Firebase database. A pivotal program that inspired this project to come to fruition is the Capital One API. Its ease of use and clear provided documentation made the integration of the API seamless. The JavaScript algorithms that power this software in the background allow for unparalleled comprehension and analysis by a machine to have ever been seen at HackTJ. Lastly, the large amounts of time the team spent Bootstrapping most of the website in conjunction with the CSS at play creates a clean and professional look that simply isn't achieved anywhere else at HackTJ.

FinancePlanner was built around the Google Firebase database. A pivotal program that inspired this project to come to fruition is the Capital One API. Its ease of use and clear provided documentation made the integration of the API seamless. The JavaScript algorithms that power this software in the background allow for unparalleled comprehension and analysis by a machine to have ever been seen at HackTJ. Lastly, the large amounts of time the team spent using Bootstrap to style most of the website, with the rest styled by the shorter CSS 3, creates a clean and professional look that simply isn't achieved anywhere else.

Challenges we ran into

The API's that are such an integral part of FinancePlanner were the components of the program that gave us the most trouble. After debating with many database options such as Firebase and MongoDB, we decided to start writing some code. Once we had come to a decision, the easier of the two API's, Firebase, was still confusing due to the included documentation having a steep learning curve, the documentation not being designed for beginners, and the unusual design of the API itself. This required us to rewrite much of our core product components. A problem that affected many of our fellow teams today was the laughably slow internet connection (we know this couldn't be avoided, it was simply a challenge we ran into). This, in turn, led to the API slowing down due to its innate cloud-based processing. However, this pain was alleviated during off hours when many teams were either asleep or playing ping pong. The final issue the FinancePlanner team had to overcome was that our computers kept crashing, requiring us to work on Google Docs to avoid the chance of data loss.

The API's that are such an integral part of FinancePlanner were the components of the program that gave us the most trouble. After debating with many database options such as Firebase and MongoDB, we decided to start writing some code. Once we had come to a decision, the easier of the two API's, Firebase, was still confusing due to the included documentation having a steep learning curve, the documentation not being designed for beginners, and the unusual design of the API itself. This required us to rewrite much of our core product components. A problem that affected us and many of our fellow teams today was the laughably slow internet connection (we know this couldn't be avoided, it was simply a challenge we ran into). This, in turn, led to the API slowing down due to its innate cloud-based processing. However, this pain was alleviated during off hours when many teams were either asleep or playing ping pong. The final issue the FinancePlanner team had to overcome was that our computers kept crashing, requiring us to back up often to avoid the chance of data loss.

Accomplishments that we're proud of

We are very excited that we were able to create a proprietary algorithm that actually works according to multiple sets of test data. The culminating experience that we are the proudest of is when we had undergone not only a myriad of technical issues but also questions about the idea as a whole. The recovery was made possible by moving to the Franklin commons and staying persistent with the help of mentors, other students, and online resources.

We are very excited that by working together we were able to create a proprietary algorithm that actually works according to multiple sets of test data. The culminating experience that we are the proudest of is when we had undergone not only a myriad of technical issues but also questions about the idea as a whole. The recovery was made possible by using the fastest computers and staying persistent with the help of mentors, other students, and online resources.

What we learned

FinancePlanner learned that taking small steps that consumed more time was far more efficient in the long run as we only had to deal with a few bugs each time as opposed to many more bugs with much larger sources of error (making troubleshooting harder). The team also learned that even though it may take more time to come to a decision, the time lost through the process is far less argumentative and produces better overall results. The final lesson worth mentioning (other than all of the new syntax, of course), was the entire experience of condensing the process of creating an idea and bringing it to life. This gives us an insight into the world of entrepreneurship and all fo the factors involved in bringing a product to market that is ready for the consumer base it is aimed for.

What's next for FinancePlanner

FinancePlanner, with more time, would like to expand the functionality of its algorithm. Right now, improvements we are thinking of making are including seasonal purchase factors, analyzing best price for a product on multiple websites, machine learning capabilities (probably through TensorFlow), a Watson API to assist as a chat bot, and an integration of an Alexa skill for voice control and ease of use. In regards to the UI of the website, we would definitely like to spend more time on improving the look and feel to create a more professional and secure atmosphere for the consumer. On the horizon, FinancePlanner sees a market of younger students looking to learn more about economics and their financial future as an adult. We plan to transform our current project into a subset of a much larger website that will have courses for both students and adults to take, direct connections with many of the larger bank corporations today, and the integration of a news feed that only contains information relevant to the site. Our largest improvements that we would like to make are to be able to integrate credit card information from other banking websites as to reduce the total number of accounts needed for full functionality. The most prominent issue that needs to be addressed is that mobile apps must be produced to make our product a viable solution to the growing financial distress many people across the globe suffer from due to a simple lack of planning and background knowledge.