There are a variety of fraud prevention tools available to enterprise level businesses. Each enterprise must evaluate their own processes and undergo serious vetting when it comes to finding fraud prevention solutions that work for their specific circumstances. Automated fraud prevention tools are a good solution for businesses. To evaluate whether or not an automated system is needed for your business, here are some pros and cons of automated systems that can prevent, detect and stop fraud.
The Advantages and Disadvantages of Automated Systems
Continuously working systems that evolve as new data is collected and act without the need for human instruction are an appealing solution for businesses looking to prevent data breaches and fraud. While automation can be extremely efficient with time, taking away manual oversight in fraud detection processes may be difficult. Automated systems usually require very specific and rigid parameters. These parameters may miss specialized types of fraud that are harder to detect. However, automated systems with machine-learning capabilities can grow and adjust as new data becomes available. Automated systems can detect fraud using known and evolving patterns in data.
The Role of Machine Learning
Machine learning plays a big role in running automated detection systems for fraud management. Machine learning platforms can learn to adjust calculations and behaviors dynamically based on the input. This means that machine learning platforms are able to keep up with new threats when they emerge and follow existing threats while they evolve and become less predictable. When fraudulent activity is based on conditional statements, expressions and constructs that are based on if-then statements, machine learning can learn and grow with every unique variable.
Sophisticated Monitoring for Enterprises at Every Level
While giant corporations like PayPal are already taking advantage of machine learning to fight fraud, this technology is not restricted to high-profile enterprises. Small businesses can take advantage of the benefits of machine learning by utilizing third-party systems to enjoy sophisticated fraud prevention. Payroll fraud, cash theft, false invoicing and external breaches are all some of the common threats faced by small businesses. An automated detection system is one of the key ways to stay ahead of both common and sophisticated threats.