One Queensland man lost more than $166,000 to an investment scam constructed by AI. One Queensland man lost more than $166,000 to an investment scam constructed by AI. A Queensland man enjoyed soaring profits from a crypto trading app. Within days of clicking on an online ad for a cryptocurrency trading app, a 29-year-old Queensland man watched his dashboard soar with profits. Making investment gains was as simple as downloading the slick-looking app and browser extension linked to his crypto wallet.

Australians could see fewer deepfake images of celebrities being hauled off in handcuffs, or promoting a fraudulent cryptocurrency investment on Facebook, after Meta launched a new one-stop shop for banks to share information on scams that has blocked 8,000 pages and 9,000 celebrity scams in its first six months of operation. From January to August 2024, Australians reported 43.4m in losses from scams on social media to Scamwatch, with close to 30m relating to fake investment scams. Meta, the parent company of Facebook and Instagram, has faced pressure from politicians and regulators in the past few years to tackle the plague of scams featuring deepfake images of public figures such as David Koch, Gina Rinehart, Anthony Albanese, Larry Emdur, Guy Sebastian and others which are used to promote investment scams. The company is being sued by the mining magnate Andrew Forrest over the company's alleged failure to tackle scams using his image. Meta announced on Wednesday it had partnered with the Australian Financial Crimes Exchange (AFCX) to launch the Fraud Intelligence Reciprocal Exchange (Fire) that provides a dedicated reporting channel for scams between Meta and financial providers of the victims of the scams.

In today's world, with the rise of numerous social platforms, it has become relatively easy for anyone to spread false information and lure people into traps. Fraudulent schemes and traps are growing rapidly in the investment world. Due to this, countries and individuals face huge financial risks. We present an awareness system with the use of machine learning and gamification techniques to educate the people about investment scams and traps. Our system applies machine learning techniques to provide a personalized learning experience to the user. The system chooses distinct game-design elements and scams from the knowledge pool crafted by domain experts for each individual. The objective of the research project is to reduce inequalities in all countries by educating investors via Active Learning. Our goal is to assist the regulators in assuring a conducive environment for a fair, efficient, and inclusive capital market. In the paper, we discuss the impact of the problem, provide implementation details, and showcase the potentiality of the system through preliminary experiments and results.