### Problem and Challenge

Achieving 100% financial inclusion where all have access to financial services still remains a difficult challenge. Particularly, a huge percentage of the unbanked adults comprise of women [1]. There are various barriers worldwide that prevent women from accessing formal financial services, including lower levels of income, lack of financial literacy, time and mobility constraints as well as cultural constraints and an overall lack of gender parity [1]. With this problem present, our team wanted to take on Scotiabank's challenge to build a FinTech tool/hack for females.

### Our Inspiration

Inspired by LinkedIn, Ten Thousands Coffee, and Forte Foundation, we wanted to build a platform that combines networking opportunities, mentorship programs, and learning resources of personal finance management and investment opportunities to empower women in managing their own finance; thereby increasing financial inclusion of females.

## What it does

The three main pillars of Elevate consists of safe community, continuous learning, and mentor support with features including personal financial tracking.

### Continuous Learning

Based on the participant's interests, the platform will suggest suitable learning tracks that are available on the current platform. The participant will be able to keep track of their learning progress and apply the lessons learned in real life, for example, tracking their personal financial activity.

### Safe Community

The Forum will allow participants to post questions from their learning tracks, current financial news, or discuss any relevant financial topics. Upon signing up, mentors and mentees should abide by the guidelines for respectful and appropriate interactions between parties. Account will be taken off if any events occur.

### Mentor Support

Elevate pairs the participant with a mentor that has expertise in the area that the mentor wishes to learn more about. The participant can schedule sessions with the mentor to discuss financial topics that they are insecure about, or discuss questions they have about their lessons learned on the Elevate platform.

### Personal Financial Activity Tracking

Elevate participants will be able to track their financial expenses. They would receive notifications and analytics results to help them achieve their financial goals.

## How we built it

Before we started implementing, we prototyped the workflow with Webflow.
We then built the platform as a web application using html, CSS, JavaScript, and collaborated real-time using git.

## Challenges we ran into

* There are a lot of features to incorporate. However we were able to demonstrate the core concepts of our project - to make financing more inclusive.

## Accomplishments that we're proud of

* The idea of incorporating several features into one platform.
* Deployed a demo web application.
* The sophisticated design of the interface and flow of navigation.

## What we learned

We learned about the gender parity in finance, and how technology can remove the barriers and create a strong and supportive community for all to understand the important role that finance plays in their lives.

## What's next for Elevate

* Partner with financial institutions to create and curate a list of credible learning tracks/resources for mentees
* Recruit financial experts as mentees to help enable the program
* Add credit/debit cards onto the system to make financial tracking easier. Security issues should be addressed.
* Strengthen and implement the backend of the platform to include:
Instant messaging, admin page to monitor participants

## Resources and Citation

[1] 2020. REMOVING THE BARRIERS TO WOMEN’S FINANCIAL INCLUSION. [ebook] Toronto: Toronto Centre. Available at: <https://res.torontocentre.org/guidedocs/Barriers%20to%20Womens%20Financial%20Inclusion.pdf>.
## Inspiration

It’s Friday afternoon, and as you return from your final class of the day cutting through the trailing winds of the Bay, you suddenly remember the Saturday trek you had planned with your friends. Equipment-less and desperate you race down to a nearby sports store and fish out $$$, not realising that the kid living two floors above you has the same equipment collecting dust. While this hypothetical may be based on real-life events, we see thousands of students and people alike impulsively spending money on goods that would eventually end up in their storage lockers. This cycle of buy-store-collect dust inspired us to develop Lendit this product aims to stagnate the growing waste economy and generate passive income for the users on the platform.

## What it does

A peer-to-peer lending and borrowing platform that allows users to generate passive income from the goods and garments collecting dust in the garage.

## How we built it

Our Smart Lockers are built with RaspberryPi3 (64bit, 1GB RAM, ARM-64) microcontrollers and are connected to our app through interfacing with Google's Firebase. The locker also uses Facial Recognition powered by OpenCV and object detection with Google's Cloud Vision API.

For our App, we've used Flutter/ Dart and interfaced with Firebase. To ensure *trust* - which is core to borrowing and lending, we've experimented with Ripple's API to create an Escrow system.

## Challenges we ran into

We learned that building a hardware hack can be quite challenging and can leave you with a few bald patches on your head. With no hardware equipment, half our team spent the first few hours running around the hotel and even the streets to arrange stepper motors and Micro-HDMI wires. In fact, we even borrowed another team's 3-D print to build the latch for our locker!

On the Flutter/ Dart side, we were sceptical about how the interfacing with Firebase and Raspberry Pi would work. Our App Developer previously worked with only Web Apps with SQL databases. However, NoSQL works a little differently and doesn't have a robust referential system. Therefore writing Queries for our Read Operations was tricky.

With the core tech of the project relying heavily on the Google Cloud Platform, we had to resolve to unconventional methods to utilize its capabilities with an internet that played Russian roulette.

## Accomplishments that we're proud of

The project has various hardware and software components like raspberry pi, Flutter, XRP Ledger Escrow, and Firebase, which all have their own independent frameworks. Integrating all of them together and making an end-to-end automated system for the users, is the biggest accomplishment we are proud of.

## What's next for LendIt

We believe that LendIt can be more than just a hackathon project. Over the course of the hackathon, we discussed the idea with friends and fellow participants and gained a pretty good Proof of Concept giving us the confidence that we can do a city-wide launch of the project in the near future. In order to see these ambitions come to life, we would have to improve our Object Detection and Facial Recognition models. From cardboard, we would like to see our lockers carved in metal at every corner of this city. As we continue to grow our skills as programmers we believe our product Lendit will grow with it. We would be honoured if we can contribute in any way to reduce the growing waste economy.
## How to use

First, you need an OpenAI account for a unique API key to plug into the openai.api\_key field in the generate\_transcript.py file. You'll also need to authenticate the text-to-speech API with a .json key from Google Cloud. Then, run the following code in the terminal:

```
python3 generate_transcript.py
cd newscast
npm start

```

You'll be able to use Newscast in your browser at <http://localhost:3000/>. Just log in with your Gmail account and you're good to go!

## Inspiration

Newsletters are an underpreciated medium and the experience of accessing them each morning could be made much more convenient if they didn't have to be clicked through one by one. Furthermore, with all the craze around AI, why not have an artificial companion deliver these morning updates to us?

## What it does

Newscast aggregates all newsletters a Gmail user has received during the day and narrates the most salient points from each one using personable AI-generated summaries powered by OpenAI and deployed with React and MUI.

## How we built it

Fetching mail from Gmail API -> Generating transcripts in OpenAI -> Converting text to speech via Google Cloud -> Running on MUI frontend

## Challenges we ran into

Gmail API was surprisingly trickly to operate with; it took a long time to bring the email strings to the form where OpenAi wouldn't struggle with them too much.

## Accomplishments that we're proud of

Building a full-stack app that we could see ourselves using! Successfully tackling a front-end solution on React after spending most of our time doing backend and algos in school.

## What we learned

Integrating APIs with one another, building a workable frontend solution in React and MUI.

## What's next for Newscast

Generating narratives grouped by publication/day/genre. Adding more UI features, e.g. cards pertaining to indidividual newspapers. Building a proper backend (Flask?) to support users and e.g. saving transcripts.