The Data-Driven Approach to Proactively Getting Ahead of Fraud Risks

The fight against fraud never ends. Fraudsters are getting smarter and leveraging new tools and technologies to perpetrate new fraud schemes at speed and scale. Every day fraudsters are finding new ways to infiltrate your card portfolio, which puts your entire organization at risk. You need to be leveraging the same sophisticated tools and technologies to proactively combat these risks. This is where predictive AI, machine learning and automation can be a game changer for your fraud operations.

The reason so many financial institutions are turning to machine learning and automation is simple. It drastically improves the performance of their entire fraud team and strategy. Today, we will talk about how these two tools, when used in unison, will save your company time, money and keep up with the competition when it comes to fraud detection.

Automatically Analyze Data to Get Ahead of Fraud Risks

When fighting evolving fraud risks, you must think like them. Fraudsters are leveraging the latest technology in a never-ending attempt to steal your customers' card numbers. Therefore, your team must be taking the same approach. Unfortunately, most fraud teams are still manually pulling and reviewing data to detect the most basic fraud patterns. Machine learning levels the playing field.

Unlike traditional analysis methods, predictive AI and machine learning can analyze millions of data points and thousands of variables in minutes. Mix in the power of consortium data to better pinpoint where the greatest fraud risks exist across your portfolio and you can have the intel you need to proactively prevent fraud. Not only can machine learning ingest massive amounts of data far faster than a human could ever compute but it does this consistently, without bias and without missing a beat. This approach allows it to detect more complex fraud patterns and create more effective rules to mitigate fraud.  As a result, your team is provided with consistent, automated, comprehensive analysis to help them stay ahead of the latest fraud threats before they occur. 

Free Up Time and Expand the Impact of Your Fraud Team Resources

Automating fraud mitigation with predictive AI and machine learning can do the heavy lifting and daily analysis that is currently swamping your fraud managers, giving them a significant amount of time and resources back. Instead of spending valuable hours manually combing through data, they can shift their attention to more pressing matters and use the data to be more proactive with their existing fraud strategy.

The best way to detect fraud trends is to review daily transactions for patterns. When you automate this process, your team can spend less time analyzing the data and more time strategizing how to best use it. The right fraud mitigation automation tool will deliver the intel needed to quickly identify and block high-risk merchants and fraud. Faster fraud data delivery means your team can quickly write and implement the rules needed to prevent future fraud to efficiently get ahead of emerging threats.  

Focus Less on Analyzing Data, More on Driving Results

Applying tools that rely on AI and Machine learning are about enhancing the fraud-fighting strategy you already have in place. These tools are the weapons your fraud managers and data analysts need to make the daily battle against fraudsters faster, easier and more effective. When combining the power of people, technology and data, you get a solution that provides a consistent approach to fraud detection, prevention and rule writing.

Currently, many financial institutions have limited insights into how well (or not well) their current rules are performing. Automation allows you to pull back the curtain and determine what works well and needs to be adjusted. As a result, your team will implement the most optimal rules possible. Together, this combination will help you stay on top of evolving fraud threats and analyze significantly more data without having to increase the size of your fraud team.

About Rippleshot and Rules Assist

Since 2013, Rippleshot has been leveraging the power of AI, machine learning and automation to protect customers from card fraud. Rules Assist is the perfect blend of these tools. Together, they help banks and credit unions prevent fraud by providing the automation, intel and data needed to implement effective rule writing strategies.

Rules Assist works with financial institutions like yours to build comprehensive and effective rule writing strategies. Together, we can prevent fraud from damaging both your customer relationships and brand reputation. With Rippleshot, FIs can:

• Take additional action on emerging fraud trends to achieve greater savings and protect their customer or member‘s reputation

• Validate fraud patterns  and ensure their fraud rules are effective

• Get proactive rules to block more fraud and continually reduce their FPR

• Access intel from a consortium data from +5,000 banks and credit unions

• Have direct input into the merchant blocking process to boost fraud detection performance to provide more stable fraud patterns over time

• Leverage fraud insights to create a proactive blocking rule to prevent fraud from merchants before the fraud occurred

To learn more about how machine learning and automation can solve your fraud challenges, connect with our team.