What type of steps does the proactive method of fraud detection encompass?

The proactive method of fraud detection is fundamentally centered on identifying potential fraud before it occurs rather than merely reacting to incidents after they have taken place. This approach involves several critical steps that align well with the components described in the chosen option.

The analytical step involves examining data trends, patterns, and anomalies that may indicate suspicious activity. Analysts often employ various techniques, such as data mining and statistical analysis, to preemptively uncover signs that could lead to fraud. This enables organizations to proactively refine their fraud detection systems and enhance the effectiveness of their preventive strategies.

Technological steps refer to implementing tools and systems specifically designed to detect irregularities and flag unusual transactions. Advanced technologies, such as artificial intelligence and machine learning, can assist in automatic monitoring and detection, enhancing the likelihood of identifying potential fraud before it escalates.

Investigative steps are crucial as they relate to the follow-up on suspicious findings. Having a structured investigative process allows organizations to delve deeper into flagged transactions or behaviors, ensuring that they thoroughly assess and understand any potential fraud, rather than letting it go unchecked.

This combination of analytical, technological, and investigative steps forms a comprehensive framework for proactive fraud detection, effectively enabling organizations to safeguard against fraud risks before they manifest.