Even with projected strong success, with 851,000 people intending to make purchases, according to Mercado Livre data, Black Friday always raises a red flag for retailers. This is because, in the last year, a Clearsale survey revealed over 400 fraud attempts per hour during the period, which would equate to a loss of R$8,500 per minute. Furthermore, a Serasa Experian survey estimates 89,000 fraudulent attempts between Friday and the weekend of the date in 2024, corresponding to approximate losses of R$500 million.
While much of the damage from scams targets end-consumers, retailers often end up bearing the brunt of the loss. This is because, in the event of data breaches on their platform, they are obligated to compensate their harmed consumers, as it is their responsibility to ensure a secure environment for their users to shop peacefully. Furthermore, one of the most common types of fraud in e-commerce involves individuals purchasing products, receiving them normally, and then claiming the store failed to ship them, thus obtaining a refund. This leaves the merchant without the sale's proceeds and without the merchandise, which is then resold by the scammer.
By maintaining a safe environment for its users, the e-commerce platform maintains its online reputation, which is essential for ensuring customer loyalty, as data from Opinion Box shows that 73% of users typically research the reputation of online stores before making a purchase. Furthermore, the E-Commerce Trends 2024 research is categorical: 92% of people have stopped buying online due to fraud concerns. Another data point, from EY, indicates that 71% of Brazilian consumers are afraid of having their data stolen online.
How can retailers protect themselves from common scams and ensure success during Black Friday? An effective solution has been implementing anti-fraud tools that enhance their systems with AI and Machine Learning. This type of technology is capable of evaluating diverse transactional data from customers, determining consumption patterns, and thereby building an information base. This allows them to have a complete picture of a given consumer's online behavior, such as their preferred payment methods, most sought-after products, most frequented locations, and favorite days to make purchases, etc.
Therefore, if any transaction deviates from the matrix defined by the technology, the system identifies it as potentially fraudulent and signals the retailer. The most interesting aspect is that the Machine Learning solution improves itself, as the more transactions it evaluates, the more information it adds to its database, thereby increasing its accuracy in detecting fraudulent operations. This means the technology stays up-to-date with even the most current virtual fraud schemes.
To give you an idea, an Accenture survey showed that companies that adopted AI and machine learning technologies to combat fraud saw a decrease of up to 70% in financial losses from scams. Therefore, investing in this type of solution is essential to protect your operations and guarantee a secure shopping environment for consumers. Beyond minimizing financial losses, this strengthens your reputation during periods of high demand, such as Black Friday, contributing to the success and longevity of the brand in e-commerce. **Note:** "70%" is not a standard numerical representation. It's likely a typo or a placeholder for a percentage or specific figure. If you have the correct value, please provide it, and the translation will be adjusted accordingly.
