AI systems can handle large amounts of data considerably faster than humans, and they regularly find relationships in the data that human eyes would otherwise miss. AI can also work without being burdened by things like the need for breaks or being limited to a set number of hours in a day.
1. Statistical Analysis
Data analysis to forecast future patterns and results is known as predictive analytics. By doing this, organizations may enhance crucial performance indicators like customer retention and revenue growth and make better judgments.
It also enables businesses to turn over low-risk, routine decision-making to predictive technologies, freeing humans for more valuable or high-risk strategic tasks. For example, predictive analytics can automatically map the likely success rates of new treatments for cancer or identify patients who would benefit, saving human medical professionals time and effort.
To create a predictive analytics model, data must be gathered, important influencers must be identified, and models must forecast the most likely outcome depending on numerous characteristics. These models are based on different algorithms and statistical techniques.
For example, decision trees – which rely on a schematic, tree-shaped diagram to show every possible path a choice could take and the probability of each – can be used for forecasting, while regression analysis – which can be linear or nonlinear – helps users understand and visualize relationships between dependent and independent variables.
Neural networks use “neural pathways” to predict behavior from data. In the case of account takeover prevention, machine learning software might detect that a user is attempting to log in from an unfamiliar geographic location, for instance, as an early warning sign that their account has been compromised.
2. Behavioral Analysis
Account takeover (ATO) attacks are often committed using bad bots that gain access to real users’ accounts to steal their personal information or to sabotage financial transactions. This type of fraud can be complex to detect because attackers use techniques such as social engineering, malware, and brute force attacks to hide their actions.
AI can help combat this fraud by analyzing user behavior patterns to identify anomalies. It is known as behavioral analysis and includes a wide range of data from how a person usually interacts with apps or websites, their standard log-on times, the devices they use to connect to their accounts, etc. It is a critical part of any security solution because it can identify phishing attempts, identity theft, and other malicious activities that are difficult for humans to pick up on.
Another way AI can help prevent ATO is by detecting anomalies in device fingerprinting. It is done by comparing device characteristics to a database of typical devices users log on to. If a new device is detected that is not in the database, this can be an indicator of suspicious activity and trigger a rapid response by a security team.
A good AI fraud detection solution will monitor a customer’s activity in real time and automatically block fraudulent activities before they occur. It will save money, resources, and customers from the effects of ATO fraud.
3. Real-Time Threat Detection
Detecting and stopping account takeover (ATO) attacks is a top priority for any website or company that offers credential-protected accounts. If not stopped in time, cybercrime can wreak havoc on your company’s reputation and cause significant losses in the short term.
To minimize the impact of ATO, a security platform should include real-time threat detection to catch lateral movement in its tracks and stop attacks that use stolen credentials. To do this, your security platform should be able to scan for anomalies in network activity and behavior, such as sudden changes in login activity or new devices used to access your networks.
Traditional monitoring tools can provide some visibility into suspicious behavior. Still, only an AI-driven security system can spot and model risks with the level of sophistication required to stop cyberattacks in their tracks quickly. Vectra AI is a complete ATO prevention solution that uses advanced threat intelligence to help you see and stop attackers using stolen credentials to attack your network and cloud data.
Artificial Intelligence is a broad category that encompasses a wide range of technologies, from narrow AI like Google Search to machine learning algorithms used in predictive analytics or virtual assistants. To effectively deploy AI, it is crucial for business, IT, and data and analytics leaders to collaborate and establish a shared definition that aligns with their goals. By doing so, they can pave the way for successful AI implementation and reap its benefits. Otherwise, you may need help to design a robust AI strategy that delivers value for your organization.
4. Deepfakes
Deepfakes are videos or images created using AI to show people saying or doing things they didn’t say or do. Cybercriminals increasingly use deepfakes to commit fraud and access services they couldn’t get with their real identity. It can include synthetic identity fraud, new account fraud, and even account takeover fraud.
This technology has become so sophisticated that it can spoof a person’s biometrics and clone their face. With the help of fake media, scammers can create a false identity and deceive their targets into sharing sensitive information or participating in fraudulent activities. In fact, according to a study, 20% of successful fraud attacks in 2023 will utilize deep fakes as part of their social engineering schemes.
The emergence represents a significant challenge for both consumers and businesses. CISOs should consider how to keep ahead of this threat and deploy detection technologies that can spot these types of scams before they can cause financial harm or impact the reputation of their businesses.
Conclusion
As criminals find it harder to carry out old-fashioned fraud techniques, such as phishing and credit card fraud, we can expect to see a rise in the use of AI to identify and prevent account takeover fraud. This technology will help keep our accounts safe and secure from unauthorized access.
In addition, the rise of AI can also help with other areas of fraud prevention, such as personalized fraud detection, where machines can identify unique patterns and behaviors that are more indicative of fraud and offer a more tailored approach to detecting those activities.
