Inspiration:

We began by gathering quantitative data concerning the needs and pain points of people regarding the existing credit score system. This helped in identifying an opportunity to improve the credit score system.

What it does:

We offer a comprehensive service to empower users to view transparent and distributed credit information. We do this with an innovative credit score system and a Chrome plugin to present loan opportunities through Even's API.

How we built it:

  1. We created a Chrome plugin from scratch which interacted with amazon.com shopping cart page.
  2. We utilized a node.js boilerplate to create a functional backend routing server and an authorization protected credit score dashboard page.
  3. We made use of the Blockstack to manage our blockchain ledger which stores the nodes with each user’s data.
  4. We used Python 3 to build a logistic regression machine learning model to predict the desired parameters.

Challenges we ran into:

  1. CORS access preventing out-going API host without a local server.
  2. Integrating the Blockstack framework into our client-side pages.
  3. Making a call from the API to Jupyter Notebook in python with the machine learning model.

Accomplishments that we're proud of:

  1. We developed a comprehensive service which addresses both the prompts based on user needs.
  2. A fully integrated service which incorporates a Chome plugin, a blockchain framework, a transparent credit score dashboard, and a machine learning prediction model.

What we learned:

  1. Delivering a complex and many-fold project under the constraints of a short deadline.
  2. Collaborative work in a team with individuals with varying skill sets.
  3. A deeper knowledge and understanding of the credit score system and the ways to address it in a transparent and distributed form.

What's next for 'Even the Credit Score':

  1. We'll keep exploring the varies technologies implemented in this project and dig deeper into blockchain.
  2. Improve the machine learning model by training and testing it with more data.
  3. Increase the understanding of the credit score system to enhance it further.

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