How can different tools improve scam prevention?
We are looking for your data-diving skills OR user insights OR digital prowess (AI, Machine learning, a fantastic set of IF functions) and anything else you have in your toolkit to provide us with new thinking around scam prevention.
If you think you or your friends and family won’t be scammed, think again. Australians lost $340 million due to scams in 2017. The amounts lost by an individual range from $1 to $10 million dollars. What worse is it’s not just losing $$, there is a mental and emotional stress, plus the impact on your personal safety, security if a scammer has managed to get personal details such as DOB, email login, bank account login, address, driver’s license, passport number – it’s a terrifying list.
Can YOU use data to stop an online scammer?
Most people don’t think they will ever fall for a scam.
At the same time, online scams are evolving very quickly.
Use data to provide insights, identify online intervention points and/or possible digital solutions that could prevent users from falling for any type of online scam.
Questions to consider when unpacking the data…
1. WHO is most susceptible to being scammed?
2. HOW do scammers incentivize users to part with their $$?
3. WHAT makes a user susceptible to scams?
4. WHAT online behavior can scammers exploit?
5. WHEN are online users most susceptible to being scammed? What are they doing online?
6. Are there platforms that are more susceptible to scammers than others?
7. WHAT are the vulnerabilities of scammers? How could this be exploited to prevent online scams?
Eligibility: Show that you have used at least one Victorian Government Dataset in our submission.
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