Diarmuid Thoma, Head of fraud and data strategy at AtData, discusses the importance of email data in fraud prevention. He highlights the extensive email database they have built and how email is the most consistent fraud predictor. Other topics include the use of AI/ML in fraud models, their recent white paper on balancing customer experience and fraud prevention, and the increasing presence of high risk domains in email addresses.
Email data is a crucial tool in fraud prevention for financial institutions, enabling assessment of risk based on factors like account age, activity level, and domain association.
Leveraging email data with AI/ML technologies allows businesses to strike a balance between fraud prevention and seamless customer experience, improving marketing strategies and personalized offerings.
Deep dives
Importance of Email Data in Fraud Prevention
Email data is a valuable tool in fraud prevention, particularly in the financial services industry. During loan applications, verifying email addresses can help detect fraudulent activities. By analyzing factors like the age of the email account, its activity level, and the domain associated with it, financial institutions can assess the risk of potential fraud. High-risk domains and disposable email addresses are areas of concern that require attention in order to combat evolving fraud methods. Leveraging artificial intelligence and machine learning technologies, companies like AtData are able to provide real-time analysis and scores to assess the risk associated with email addresses. This enables businesses to strike a balance between fraud prevention and delivering a seamless customer experience.
The Value of Email Data in Marketing
Email data also plays a crucial role in marketing strategies. By validating and enhancing email lists, companies can improve deliverability rates and better target customers. The atData Quality Score offers insights into customer engagement, activity levels, and spending propensity. This score helps businesses identify valuable customers and tailor marketing campaigns accordingly. Additionally, this data can be used to enhance customer identification processes and improve KYC (Know Your Customer) efforts. With AI-driven models, businesses can leverage this data to qualify customers and personalize offerings.
Challenges and Trends in Email Data
One of the major challenges in handling email data is the increasing number of high-risk domains and disposable email addresses used for fraudulent activities. These domains are constantly evolving, with thousands of new ones being created daily. Companies need to update their systems and adapt quickly to stay ahead of fraudsters. The integration of AI and ML technologies plays a vital role in effectively managing and analyzing the vast amount of email data. Financial institutions and businesses should continuously monitor and adapt to emerging trends to ensure their fraud prevention systems remain robust and future-ready.
The Intersection of Customer Experience and Fraud Prevention
Balancing customer experience with fraud prevention is a critical consideration for businesses. While preventing fraud is essential, it should not hinder the customer journey or create unnecessary friction. Effective fraud prevention strategies should aim to enable new revenue opportunities, open up markets, and cater to evolving customer expectations. By leveraging technology, businesses can enhance their fraud prevention capabilities without compromising customer experience. The continuous evolution of AI and ML in fraud detection and prevention ensures a proactive and efficient approach to maintaining a secure environment for customers while delivering excellent service.
Consider the humble email address. Most of us don't give this part of our identity a second thought but there is a wealth of information that can be gleaned from this one piece of data. And when it comes to fraud the email address is the most consistent predictor, more than any other data point.
My next guest on the Fintech One-on-One podcast is Diarmuid Thoma, the head of fraud and data strategy at AtData. He has spent most of his 23-year career focused on fraud prevention and today he leads a team that has built the most extensive email database in the industry.
In this podcast you will learn:
The history of TowerData and the merger that resulted in the creation of AtData.
The two areas of the company that Diarmuid leads.
Why banks and fintech should care about email data.
Why email is the most consistent fraud predictor.
What other data points they take into consideration in their fraud models.
The staggering percentage of every email in existence that are in their database.
The number of new high risk domains that are being created every day.
What is returned to the client when they provide an email address to AtData's API.
How banks and fintechs are using this data today.
Why they are included very early in the funnel for lenders.
How the AtData quality score works and what it can tell their clients.
How they have incorporated AI/ML into their fraud models.
Details of their recent white paper on balance customer experience and fraud prevention.
The trends that banks and fintechs should be paying attention to when it comes to email data.
