Recent cybersecurity breaches have started to be much more dangerous, ranging from a spyware attack case on Meta’s WhatsApp to credential stealing by the Lazarus Group. It’s pretty much clear that fraud prevention standards need to do better.
Facing these most recent cybersecurity attacks requires the most versatile tools and cutting-edge technologies. Only by giving themselves better fraud prevention standards can businesses combat this long-lasting tough battle.
But the question remains: what can businesses do to protect themselves against this conflict between companies and fraudsters? Look no further, as this article will explain the new strategies to wage a war against fraud.
Why Fraud Prevention Can’t Stay the Same Anymore
The current fraud prevention tools actually did their job well to secure customers and businesses. However, as fraudsters continuously evolve, the same tools will not be able to protect anymore, mainly because:
- Fraudsters constantly research a way to bypass any fraud prevention systems. They can learn how to leverage AI to bypass biometric authentication or undermine device checks to be able to intercept authentication messages.
- Current available tools are based on obsolete models. As a result, it simply can’t keep up with future advanced fraud models, resulting in vulnerabilities that fraudsters can exploit for their own benefit.
How Recent Breaches Are Changing Fraud Prevention
Recent cybersecurity threats have something in common: they serve as a testament for businesses to change their fraud prevention. But how exactly do they push fraud prevention standards to change for the better?
Focus on Real-Time Monitoring
To ensure no frauds ever come close to breaching the system, businesses have to prevent them by using a proactive approach. This can be done by focusing on real-time monitoring as the real-time fraud detection.
Real-time monitoring works by using machine learning-based systems. It will perform by collecting and transforming data in order to have pattern recognition. Once a fraud has been detected, it will prompt an alert and take an automated action.
This fraud prevention tool greatly reduces potential fraud because of the immediate and proactive reaction. The machine learning-based systems can also add an adaptability to combat emerging new cybersecurity threats.
Behavioral Analytics Becomes Core System
In order for real-time fraud detection to do any good, it also needs advanced cybersecurity techniques like behavioral analytics as its core system. Its main purpose is to identify strange behavior when examining collected transaction data.
What exactly is considered strange behavior? It all depends on the data the businesses collect. For instance, customers who unexpectedly make large transactions or customers who have multiple failed login attempts.
Of course, these are just a few examples of what behavioral analytics can do. The main power of this tool is how it can set rules of what is considered strange behavior, helping businesses to detect potential fraud as fast as possible.
Data-Driven Insights Replace Gut-Based Decisions
There are times when gut feelings come in handy, but this is not one of those times. If fraudsters don’t use gut-based decisions to find an exploit, then why should businesses make it? Especially that:
- Decisions from assumptions and bias are often lacking concrete proof. Lacking solid data as a proof will result in businesses making limited decisions.
- Business leaders might face distress if their decisions come out wrong. Plus, it will be a challenge for businesses to hold individuals accountable for the results.
Instead, businesses should embrace an insight that is based on the right data. By using historical patterns and behavioral analytics, businesses can increase the accuracy of the outcome and proactively fend off potential fraud that may already be in motion.
Risk-Based Authentication
Recent cybersecurity issues force fraud prevention to be able to determine the severity of the potential fraud based on their risks. This can be done by utilizing AI-driven fraud detection that can examine a customer’s device and behavior to identify a risk.
For example, if a customer logs in and authenticates by using a one-time password, the tool starts determining a risk. However, if the customer logs in using a known device, trusted IP network, and no signs of strange behavior, then they are allowed to log in.
Not only can this greatly improve fraud detection, but AI-driven tools can also reduce false positives in risk-based authentication. It can also reduce friction by making sure the tool runs in the background during the process.
Intelligence Sharing Across Platforms
Recent cybersecurity breaches indicate the thriveness because of fraudsters’ willingness to share intelligence amongst themselves. This idea can actually be used by businesses to increase their defense against fraud.
However, anything is easier said than done. Each platform must uphold the security when companies share their collaborative networks with advanced encryption and AI technologies, ensuring complete proactive measures to the digital ecosystem.
Stronger Vendor & Third-Party Risk Management
As the main issue with the current fraud prevention is because of outdated fraud models, businesses also need to migrate to the better vendor and third party. There are many factors that can assess their risk management:
- Identify the scope of their capabilities that suits businesses. Decide on whether they can be trusted on preventing data breaches by how they manage data and whether they follow regulatory requirements.
- Conduct due diligence to determine their risk management. Include background checks, assessments, and their practices in the due diligence.
- Monitor their performance to identify any vulnerabilities. This can help businesses quickly assess risks to prevent data breaches and security risks.
What New Standards Are Emerging in Fraud Prevention?
It’s clear that recent cybersecurity breaches influence the change for new fraud prevention standards. But what exactly are the new standards that all businesses should follow to adapt to the future fraud schemes?
It is easy to say that using AI is the new standard for fraud prevention, according to Mitek’s 2025 fraud predictions. AI-driven fraud prevention has all the necessary capabilities that meet all six main points discussed above.
What You Can Do Today to Strengthen Your Fraud Defense
It’s understandable how all of these might simply feel overwhelming for new businesses. Still, it is better to start somewhere than just be sitting ducks, and using Keypaz as an AI-powered fraud prevention solution is a good start.
Keypaz, however, is more than just fraud prevention. It also offers seamless authentication to increase user experience, as well as device intelligence that is effortlessly adaptive to any kind of business.
By using Keypaz’s AI-powered fraud prevention, businesses can enhance their security against any of the recent cybersecurity breaches. Start your journey for a better fraud prevention standard with Keypaz now!