Following the confirmed collaboration between Chargebacks911 and AlphaFintech, Payment Expert spoke to Monica Eaton-Cardone, Founder of the former company, as she discussed the partnership and what it means for fraud-fighting strategies within the payment space.
Payment Expert: Firstly, are you able to tell us what led to the partnership between Alpha Fintech and Chargebacks911 and why the collaboration is so well positioned to do well in the market?
Monica Eaton-Cardone: The Asia-Pacific region is one of the fastest-growing spaces for payments today, and with any payments comes the possibility of chargebacks. Global-branded cards issued in the Asia-Pacific region are expected to generate more than 288 billion purchase transactions in 2025, compared to 196 billion in 2020.
We know from our extensive experience in North America and Europe that merchants are facing a growing chargebacks and fraud problem, so a partnership with Alpha Fintech, who have proven themselves as one of the most forward-thinking merchant acquirers in the region, was ideal.
In the modern payments space, how crucial is the ability to simplify complex chargebacks?
The sheer amount of data that needs to be trawled through, in order to identify chargeback claims that are likely to be fraudulent and successfully dispute them is staggering, and far more than what most merchants should have to spend.
By simplifying the process and offloading much of the investigative and analytic work to artificial intelligence and machine learning we can significantly cut down costs, allowing merchants to invest in growing their business.
What are some of the key trends of the APAC market and how is this collaboration well prepared to deal with them?
Two of the key trends are in fact global: eCommerce is booming but fraud is also on the rise. When it comes to APAC in particular, eCommerce is expected to grow at a rate of 8.2% between 2020 and 2025, compared to 5.2% for the US and Europe. This growth means that there will be more first-time eCommerce users, and therefore more potential for fraud.
Mobile commerce is also a significant differentiator between APAC and the rest of the world. Almost a quarter of people in the region are under 15 and only 9% are above 65, and this is a prime demographic for smartphone use, which is why we see statistics like 70% year-on-year growth in smartphone usage.
Does the increase of card payments in the region elevate the threat of fraud, and how do you best combat fraud of this scale?
Based on what we’ve seen elsewhere in the world, more card payments inevitably means more fraud – there will be more new customers with insecure accounts that can be compromised and less resources to fight fraud.
When fraud reaches the levels we see today, having employees manually check transactions is impossible. Instead, merchants are increasingly using smart solutions like Fi911 to find the signs of fraud through analysis of the ‘big data’ that isn’t included in a chargeback report. AI and Machine Learning can automate almost every part of the process.
What can the collaboration do to ensure the most efficient utilisation of data?
One of the primary issues with post transaction fraud, also known as chargebacks; is misinterpreted data. The chargeback process is complex and carries hundreds of rules by region, card type, method, and category. Without a check and balance of the outcome data, ML models will be assumed to be accurate or optimised – when compared to other analytics, this could be far from ideal.
Besides ensuring that backend processes are finely tuned and working as effectively as possible; collaboration also brings about efficiency gains. Joined datasets form enriched insights as opposed to separate and duplicate segments.