Let's take a look at the advantages and disadvantages of each approach.
The risks of selective analysis of transactions
When businesses choose to use AI strategies to selectively analyze only transactions that appear to be fraudulent, they take on several risks.
• Difficulty distinguishing fraudulent from legitimate. Inexperienced merchants may misjudge fraudulent transactions that appear to be legitimate.
• Rejecting too many transactions. A low fraud rate may uk consumer data list indicate a high rejection rate that can negatively impact a merchant’s reputation.
• Fraud mutation. Traditional AI-based strategies may fail to detect new fraud trends. When fraudsters evolve their tactics and AI rules fail to keep up with the changes, a merchant’s fraud control service becomes ineffective. •
Gaming the system. Fraudsters are very good at slipping past a fraud filter. If they discover that a merchant has a minimum fraud rate of $1,000, they will keep their orders below $999 so that they are automatically approved.
• Complicated fraud filter management. Merchants often use multiple rules in their fraud filter to flag as many fraudulent transactions as possible. However, this can also increase risk exposure. If a merchant is not careful about the order in which rules are applied (which goes first, second, etc.), it is possible that some rules will override others, reducing the business’s protection.
• Not seeing the big picture. Dealing with individual transactions can lead a merchant to miss the big picture. For example, a purchase of a laptop for Tabapuã Street may appear legitimate. But if a merchant is not analyzing all transactions, they may not realize that 10 laptops were delivered to different addresses on the same street – all with close deliveries – which could indicate a fraud attack.
When the focus is on individual cases rather than a collection, preventing large attacks becomes more difficult.
The advantages of analyzing all transactions
If manually selecting transactions for analysis is not the answer, it may be better to analyze all transactions made using other tools as a complement.
What are the advantages of this?
• Low cost can still be a red flag. Fraudsters tend to place low-cost orders to see if a stolen credit card number works. If it does, it opens the door to larger fraudulent orders. Analyzing all transactions lets you find the small purchases that are made to test your fraud system—transactions that might otherwise go unnoticed.
• Analyzing more transactions allows you to build a bigger picture. When you analyze more transactions, you increase the amount of information in your transaction database so that you can make more informed decisions in the future. Consider our earlier example of the notebooks sent to Tabapuã Street. Each individual sale may seem innocent, but the true pattern of fraud only emerges when the transactions are viewed together in a larger context.
• Questionable transactions can be more closely evaluated. Some transactions will always remain unclear, with no way to tell whether they are fraudulent or not. Fraud control systems that rely solely on artificial intelligence will automatically reject all such orders. If you have a system that looks at these transactions, you’ll know that some of these orders are good and should be approved.
• Prevents large-scale fraud attacks. Professional fraudsters tend to work together to coordinate attacks on a company in a short amount of time. If a single company reviews the orders, it’s like throwing cold water on a fire; attacks can be identified, stopped, and prevented more quickly.
Artificial intelligence has made great strides in controlling fraud, but companies can’t rely on it alone to determine which orders are fraudulent and which are legitimate. Instead, companies that combine AI with a team of human analysts find that the team helps the AI solution become smarter and more efficient, allowing the correct transactions to be approved and increasing customer satisfaction, encouraging customers to continue buying.
Developing a Comprehensive Fraud Control Solution
While fraudsters are constantly improving their tactics, it is important for online merchants to develop a comprehensive approach to preventing fraud that includes:
• Advanced technology — to quickly accumulate data
• Statistical intelligence — to determine which data patterns are suspicious and require detailed analysis
• Sophisticated human analysis — to help companies gain a broader view to increase order approvals.