Mastering Fraud Solution Implementation - Importance of Leadership and Unified Priorities

• Ivan Skula
• 31.7.2024

Mastering fraud solution implementation means having a great executive sponsor and company-wide support. Key factors include leadership, clear priorities, and effective communication to ensure project success.

Essential Skills for the Modern Fraud Fighter

• Ivan Skula
• 12.7.2024

Overwhelmed by information overload and an ever-evolving fraud landscape? We feel the same. Let’s explore how to stay up-to-date by prioritizing foundational skills for effective day-to-day work.

Mastering Fraud Solution Implementation - The Art of Defining 'What' and 'How'

• Ivan Skula
• 24.6.2024

Discover the keys to successful fraud solution implementation by understanding the critical roles of 'What' and 'How' in avoiding scope creep and achieving project goals.

Don't make the headlines! Or everyone is the target - its a fact!

• Ivan Skula
• 16.11.2023

We already know that indirectly fraud impacts everyone. But that's not the end of it. For fraudsters - everyone is a target.

The dawn of the vishing!

• Ivan Skula
• 08.11.2023

Article explores a potentially ominous evolution of vishing, where AI-driven models could replace human call center agents, making vishing even more scalable, adaptable, and convincing.

Customer in Control: Reducing Fraud Risk by Allowing Customers to Manage Their Own Exposure

• Ivan Skula
• 13.7.2023

Shift in Fraud Landscape: Account Takeover Fraud loses ground to Authorized Push Payments, raising challenges for banks in fraud detection. UK Government takes action to protect APP fraud victims, signaling potential glo

Why don't we just block the fraudster's IP address and be done with it?

• Ivan Skula
• 06.7.2023

Leveraging IP addresses is a common practice in fraud mitigation. However, understanding their limitations is crucial. This article explores the technical aspects of IP addresses, the role of IPv4 and IPv6, network addre

Approve or Decline - are these all our options?

• Ivan Skula
• 25.6.2023

Initially, when an organization deploys a real-time fraud prevention system, at least two responses are inherently required - Approve and Decline. But are there any other options?

Device fingerprinting - how it works and where it fits in fraud detection?

• Ivan Skula
• 16.6.2023

Like a human fingerprint, a device fingerprint is a unique digital representation of a particular device. Lets look at how it works and where it fits in fraud-prevention?

Fraud rules basics or How to design a rule?

• Ivan Skula
• 22.5.2023

In this blog, we return to the very foundation of fraud detection and delve into the basics of the fraud rules creation process by tackling the ATM cash withdrawal fraud scenario.

Confusion matrix and the False-Positive Ratio mantra

• Ivan Skula
• 18.4.2023

What is confusion matrix? How do we calculate the most common KPIs? Which of the KPIs are the most relevant and which can be misleading?

Are you sharing your secrets with ChatGPT?

• Ivan Skula
• 05.4.2023

One of the aspects of new technology is the lack of awareness of its potential nefarious use among the general public; here, the ChatGPT is the perfect storm. It's new; there is huge hype around it to the point of being

Fraud and cyber crime - how much worse can it get?

• Ivan Skula
• 31.3.2023

Despite the advancements and deployment of more advanced techniques than before, we don't see the decrease in fraud or cyber crime but exactly the opposite. So how much worse can it get?

Don't trade the go-live date for more functionality.

• Ivan Skula
• 26.11.2022

A lot of effort goes into planning and framing the scope of a new fraud management solution. It is especially tricky when the organization is going through this process for the very first time. Based on my experience fr

How (not) to train the fraud detection model! (Part 2)

• Ivan Skula
• 13.11.2022

In the follow-up to last week's story, Milo will further widen his view on possible routes he can take. He will also realize how overwhelming it could become to improve the predictive model through additional features an