What Is Big Data’s Role in Fraud Prevention?
Fraud prevention technology continues to improve on a regular basis. With criminals often looking for every opportunity to exploit critical information for lucrative or nefarious purposes, financial institutions must stay up to speed to protect their customers and their bottom lines. Data analytics is taking on a stronger position to help in this capacity. On the most basic level, it can help identify key attack strategies more effectively to create proper defenses and mitigate any threats before they come to pass. Big data can also analyze patterns over multiple sectors to confirm how attackers enter the system and what they look for. Transposed onto a machine learning-based fraud prevention platform, it means a company has the best chance of withstanding a possible attack.
Predicting where the next attack comes from
One aspect where big data can play an important role in the development of an effective anti-fraud system is in information gathering. Financial tech blog Bank Info Security noted that one of analytics’ strong suits is identifying patterns over broad sections of an entire network. Instead of looking at an area where an attack occurred, a series of trained algorithms can point discrepancies over multiple channels that have some connection. It helps banks integrate all their platforms to determine where an attack can happen next.
An analytics platform can also look at entry points to find not only bottlenecks but weaknesses that allow for easy entry. For example, a mobile device with a weak password and no two-step authentication can be a great way for a hacker to enter a system. A system trained to detect structural faults in entry can quickly assess this and address it quickly.
Forensics in the data world
Another area where big data can help improve fraud detection and prevention is in the field of forensic data analysis. Consulting firm Ernst and Young defines the practice as establishing patterns and correlations with existing data to establish possible reasons for an eventual attack. In conjunction with predictive analytics, businesses can use this forensic evidence to predict when and where the next attempt will occur and implement the proper safeguards.
There are many benefits to have a forensic data analysis system in place. For one, as Tech Republic noted, it helps companies exceed, not just meet, regulator expectations for compliance in protecting their customers. By utilizing a pattern-based analytics system that FDA provides faster detection times on fraud prevention, businesses can increase the return on investment from implementing this system. When attacks do happen, banks and other financial institutions are in a better position to recover, since they can quickly determine the target of a fraud scheme, isolate it and restore it to its original state much more quickly than without these tools. This helps reduce the costs of damages and restores operations for the particular customer in a shorter duration.
By identifying patterns and anomalies through analytics, big data can help banks and financial services firms prepare and prevent attacks, as well as mitigate the losses when the worst happens.
Subscribe to stay infomed