Consumers around the globe are experiencing a huge transformation. Digital and globalized everything is radically revolutionizing the way we live, creating better choices, more opportunities, extra conveniences, and lower prices. Research reveals that more than 40% of the world’s population has access to the internet, with over 3.2 billion active users on social media sites and digital platforms.
The spread of the digital ecosystem has resulted in a significant increase in cyberattacks, posing data security threats to end users. While earlier, cybercrime mostly affected website owners, now end users too are the victims. The number of internet frauds has increased over the past few years. Research shows that in 2017 there was a 45% increase in online account or profile takeovers, 70% of content viewed online was found to be harmful or unsuitable for viewing, and around 10.6 million fake news articles were published in 2016-2017.
Cybercriminals have been targeting corporate brands and users alike with fraudulent accounts, identity theft, travel frauds, fake delivery, fake shopping, coupon or loyalty abuse, fake job offers, phishing emails, harmful content, bot-based fraud etc. They impersonate brands and users, offering counterfeit products and services, and phishing for personally identifiable information (PII). These lead to financial loss and loss of reputation for brands and the end users. Hence, online trust and safety is a growing and an urgent need for businesses and communities today.
Trust and safety framework
In order to ensure a safe and secure digital environment, a well-structured trust and safety framework powered by technology solutions and processes is needed. A framework with a mix of Optical Character Recognition, Image Processing, Computer Vision, Soft Computer technology, Natural Language Processing, Artificial Intelligence and Robotics to auto segment content and a human layer will ensure effective results.
Machine Learning (ML) techniques will help businesses accurately predict fraud. Pattern documentation will assist ML to weed out risks through patterns and modus operandi-based investigations. For example, businesses can train bots or robotic process automation (RPA) engines to prevent transactions that are fraudulent in nature. If a customer makes a purchase online, a bot can check if the purchase is in line with that particular customer’s past buying behavior and make an assessment whether the purchase is genuine or fake. Applying automation can produce definitive reports with essential documentation based on the frauds predicted by the system.
Predictive analytics will help businesses analyze historical data to increase preparedness and reliability of future fraud inspections. It also comes with deep computational capabilities, which train the bots based on historical data to resolve issues without human intervention. Basis the trend seen today, bots learn for tomorrow. The best part about ML models is that they automatically learn from data without having to rely on pre-determined rules.
Trust and Safety framework should include guidelines that will enable businesses to review advertisements by monitoring text, images, videos and destination URLs for safety and relevance. Besides, they will also monitor products for IP, originality, product information and pricing details by performing product quality and review.
Humans can take appropriate actions towards flagged issues and concerns, reach out and notify customers about suspected issues, as well as provide customer support on technical issues or policy related violations. For example, if an online transaction is blocked and a customer writes asking the reason, the support team can check and verify the required customer details, and allow or disallow the transaction.
An efficient Trust and Safety framework will empower businesses to review suspicious transactions and accounts for fraudulent activity, check payment instruments for discrepancies, and deliver accurate ways to predict risks, prevent probable dangers, and act on flagged concerns.
Businesses need to implement innovative digital technologies within their systems to stay competitive in the ever-evolving market scenario. If businesses fail to provide a safer environment to the users, they are most likely to move to safer avenues - Just the way one would prefer to take a longer but safer route over a shorter route, which is a dark deserted alley!