S.C.A.M.S.

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  S.C.A.M.S. User Interface

S.C.A.M.S. (Senior Checks Against Malicious Scams) Team: Scam Squad (Carol Ibrahim, Leen Elwasila, Maya AbuZolof)

Inspiration The inspiration for S.C.A.M.S. came from a harsh reality: in 2025 alone, Canadians lost over $704 million to fraud. As we looked closer at our local community in Hamilton, we realized that our large aging population is being disproportionately targeted. Seniors represent approximately 26% of all stolen funds, often because they are targeted by sophisticated phishing emails that mimic trusted institutions.

We wanted to build more than just a tool; we wanted to create a "digital shield" that aligns with the Canadian National Anti-Fraud Strategy. We believe that while the government is investing hundreds of millions into protection, individuals need a simple, immediate way to fight back.

What it Does S.C.A.M.S. is a web application designed specifically for older adults. The interface is very easy to navigate. A user simply pastes the contents of a suspicious email into the app, and our system analyzes the text for: Urgency/Fear-based language (e.g., "Your account will be closed in 2 hours"). Suspicious Metadata and linguistic patterns common in scammers. Fraudulent Links disguised as official URLs.

How We Built It We used Google Colab to build the brain of our app. We started by finding a large dataset filled with real examples of common scam emails and regular "safe" emails. We split this data into two parts: 80% was used to teach the model what a scam looks like, and the other 20% was saved to test if it actually worked. After training, our model achieved a perfect 100% accuracy score on the test set. This means it correctly identified every single scam and safe email we threw at it, making it a very reliable tool for seniors to use.

Challenges We Faced Since this is one of our first hackathons ever, the biggest challenge was the learning curve. We had to learn how to use new coding languages and tools on the spot while the clock was ticking.

Learning to Code: We spent a lot of time figuring out how to connect our data to a working website. Accuracy: We worked hard to make sure the model was actually helpful and not just guessing. Time: Trying to finish everything, the code, the logic, and the design, in just one day was a huge rush.

What We Learned We learned that you could pick up a brand-new skill very fast when you have a good reason to. We had to learn brand-new programming skills very fast on a deadline and teach ourselves new languages to get the model running and the website live. We also learned how important it is to make technology simple. For seniors, we had to make sure the app was easy to read and didn't have any confusing "tech talk."

The Future Our mission is to keep growing S.C.A.M.S. from a project into a full "digital shield." We want to eventually make it work directly inside email apps so it can stop scammers before they even reach a senior's inbox, helping protect the most vulnerable people in our local community.

Built With

• gemini
• google-colab
• kaggle-datasets