On Tuesday, Apple unveiled its efforts to prevent fraudulent transactions through the App Store between 2020 and 2023. The Cupertino-based tech giant highlighted the rise of digital threats and the measures it has taken to protect users from fraud and phishing attacks. The company said it prevented a total of $7 billion (roughly Rs. 58,440 crore) worth of App Store transaction fraud during the period. It also blocked more than 14 million stolen credit cards and over 3.3 million accounts from retransacting.
Details of Apple’s efforts were released by the company in an editorial post, where it says: “As digital threats have evolved in scope and sophistication over the years, Apple has expanded its anti-fraud initiatives to address these challenges and help protect its users. Every day, Apple teams monitor and investigate fraudulent activity on the App Store and use advanced tools and technologies to weed out bad actors and help strengthen the App Store ecosystem.”
Sharing more data, the tech giant said that in 2023, it managed to prevent fraud worth $1.8 billion (roughly Rs. 15,030 crore). Additionally, it rejected more than 1.7 million app submissions from the App Store because they didn’t meet Apple’s privacy, security and content standards. It also terminated the accounts of approximately 374 million developers and customers and removed nearly 152 million ratings and reviews due to fraud concerns.
Apple has also taken steps to prevent malicious activity that can occur at the customer account level. Highlighting bot accounts created to spam or manipulate App Store ratings and reviews, the tech giant said it blocked the creation of more than 153 such fraudulent accounts and disabled another 374 million accounts.
Explaining the app review process, the company said its team of 500 employees evaluates every single app around the world before it appears on the App Store. This team reviews roughly 132,500 applications per week and reviewed approximately 6.9 million applications last year. The review team performs several checks and uses a combination of automated processes and human review to detect potentially dangerous and fraudulent applications.
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