Using machine learning in fraud detection is significant because it improves the accuracy and efficiency of identifying fraudulent activities. Traditional techniques often depend on fixed rules, which can be easily circumvented by savvy fraudsters. Machine learning systems, on the other hand, dynamically adjust their models based on ongoing data, enhancing their predictive capabilities. This leads to fewer false positives, faster investigation responses, and ultimately, a more fortified financial ecosystem that can adapt to the ever-evolving tactics of fraudsters.