How Predictive Analytics Is Affecting Cybercrime

In the world of cybercrime, AI is helping to reduce the risk of crime and is making life a lot easier for those trying to stop these attacks. Predictive analytics can be used as an added form of security to help ward off sophisticated cyber-attacks by companies with a limited amount of security measures at hand.

Predictive modeling is a type of data analytics that helps to forecast potential events that could take place in the future. It involves taking both current and past data into account to determine future events while keeping on top of emerging new data trends.

This type of analytics has been used in the marketing and banking industries, and now security professionals are examining its potential to help decrease cyber attacks. This can be done in a variety of different ways, including the following:

Identify User Behavior

If a criminal should ever steal an employee's password to hack into a computer, cybercrime software can send out an alarm about the suspicious activity. In addition, AI can identify different behavior patterns between individuals to identify the risk of a stolen password. Everybody has usage habits that are distinctly their own, and AI can learn the practices of employees to help determine any potential breaches by other individuals.

Determine Vulnerabilities

Predictive analytics can help companies understand exactly what risks they are facing. For example, while cybercrime should always be viewed as an overall threat to business, certain attacks are more commonly experienced by different industries. By using analytics, the most threatening types of cybercrimes can be isolated based on similar past and current crimes that are happening to similar business types.

Streamline Cyber Insurance

When a data breach occurs, it can be very expensive, which is why cyber insurance has become so popular over the years. Businesses that need this type of insurance coverage can use AI in predictive analytics to estimate how much insurance would be required based on the likelihood of an attack. It can be difficult to understand all of the relevant risk factors, so it's always best to leave the forecasting in the hands of high-quality AI software.

Crimes in the physical world always remain a concern, and predictive analytics can also determine risk factors in this area. While cybercrime has the potential to drain an organization of its funds and bring it to its knees, physical crimes can be violent and cause bodily harm. 

When a personal injury lawyer needs to be called in for a crime-related event that has occurred in a place of business, a company can also experience significant financial losses.

AI can keep a business protected from cybercrimes and physical types of crimes by using predictive analytics. For example, data analysis can point out security weaknesses and determine what types of crimes are most likely to occur in the future based on past and current trends.