Fraud Is Not A Problem to Solve

As we've covered in our previous posts, card fraud is a threat that never stops evolving. Fraud is not a problem to solve but a continual challenge that one learns to fight off with confidence.  Over the last few years, massive shocks like Covid-19, lockdowns, supply chain disruptions, and labor problems have tested the resiliency of companies and consumers. 

In the world of card fraud, threats continue to evolve, including synthetic fraud, account takeover, ransomware, crypto, and BIN Attacks, which leave your team exhausted. As a result, they shift into reactive mode. Our clients often tell us they are constantly worrying about what will happen next and what type of development or threat is hiding around the corner.

These events create a downward spiral where cardholders are frustrated, your team is tired, morale is low, losses are piling up, growth slows, and you become at risk of losing your card portfolio business.  

A strategy of building a resilient fraud operation will help you manage both today's risk and tomorrow's threats. Adopting the right tools, data, and processes will reduce fraud, improve your bottom line, and build the institutional confidence you need to face an uncertain future.

Investing In Tech And Training Helps You Avoid Falling Behind

The majority of the financial institutions we speak to struggle to keep up with modern-day fraud threats. This is primarily due to outdated, manual processes requiring fraud teams to comb through data to find relevant insights. This takes up a considerable amount of time, and produces limited results. Simply put, you are spending a ton of person-hours and still not reviewing the amount of data or getting the results you need.

An automated solution that leverages AI and machine learning can review millions of data points in minutes. It will then analyze this data and identify fraud trends before impacting your customers. A solution like Rules Assist will suggest optimal rules based on this data. As a result, your fraud team spends more time strategizing than analyzing. Rather than pouring over spreadsheets with limited results, the team spends more time understanding fraud trends, deciding which rules to implement, monitoring performance, and developing more strategic skills.

Investing in your team’s growth and skills will help them work with more confidence, leading to increased success and less turnover. A well-run winning operation attracts talent and makes recruiting easier. The right automated machine learning solution improves not only your fraud performance but also your fraud team’s overall skills and confidence. 

Become More Efficient, Strategic and Resilient

Building a strategic, resilient fraud operation requires the right organizational mindset. A way of thinking that agrees that fraud is a never-ending battle that can only be won with the right technological investment and implementation. This type of vision allows your team to spend their time making strategic decisions based on relevant data.

Machine learning and automation are transforming several areas in the financial industry, from lending to customer service. This is especially the case for fraud prevention, where machine learning is quickly becoming a must-have technology. In addition, this technology can provide your team with data and insights gathered from the entire market instead of just one financial institution. As a result, your team will be better equipped to handle current and evolving threats and always be prepared for what’s around the corner.

About Rippleshot and Rules Assist

Since 2013, Rippleshot has been leveraging the power of machine learning and automation to protect your customers from card fraud.

Rules Assist is the perfect blend of these tools. Together, they help your institution avoid falling behind the competition by providing the automation, machine learning, and data you need to implement effective rule writing strategies.

To learn more about how we can reduce cost, increase efficiency, and keep your fraud strategies up to date, please click the button below.