Top 3 AI Innovations You Need to Transform How Fraud Prevention is Done
For the past century, brilliant minds have been working on developing and advancing artificial intelligence. Progress in the field of artificial intelligence can be traced back to 1935 when computer pioneer Alan Mathison Turing presented his first substantial work on an abstract concept resembling AI. Fast forward to 1997, IBM's chess computer, Deep Blue, defeated the world champion Garry Kasparov, marking another milestone in AI's progress. However, the 2000s witnessed a lull in significant advancements until OpenAI released GPT-2 in 2019. That event has leapfrogged everything before it ushering in a new world of transformational potential. .
In the world of fraud, the most challenging area is payment fraud prevention for digital goods and services. The increasing anonymity of privacy rules and the invisibility the digital realm clearly raised the stakes for selling online. Moreover, the fact that the fraud prevention decision needs to take place in less than a fraction of a second only makes it harder to effectively screen. Fraudsters use cutting-edge technologies and various types of camouflaged attacks to steal thousands or even millions of dollars in as little as 30 minutes. To identify the hundreds of different types of fraud attempts taking place in an ocean of reliable customer transactions, legacy methods just wouldn’t cut it.
A new world of fraud prevention
nSure.ai is using a similar methodology and infrastructure to stop payment fraud in digital goods and services. This is how nSure.ai is developing and using the most advanced capabilities of AI to stop it.
An Architecture that Gives Every Customer Their Own Dedicated AI Model:
Using multi-tenant architecture, nSure.ai has created a fraud prevention architecture that can best utilize AI for its mission. In places where most fraud prevention solutions pollute their models with legacy commerce or irrelevant data that hurt the performance, nSure.ai create dedicated models for each customer (and each customer’s separate businesses) in a smart, efficient way designed to optimize fraud prevention results. This way each merchant gets the most efficient model, built, and trained solely on the cleanest, most relevant specific data.
Changing the Paradigm from Supervised to Supervised and Unsupervised Learning
Of the fraud protectors who use AI, almost all are solely relying on supervised AI/ML. Of course, this is a MUST; but it’s not enough. nSure.ai takes the fraud prevention game to the next level using unsupervised learning, as well, to trace anomalies across the whole of merchant activity. This helps take advantage of the real power of AI to trace and detect abnormal scalable fraud patterns. With that merchants can prevent complicated fraud attacks in a way never seen before, from a completely new angle.
Engineering that Thinks Like A Fraudster
The DNA of nSure.ai is rooted with people who felt the pain of fraud while trying to sell digital goods. They built this software from the exact experience current customers have today. That perspective comes from the inside out; not the reverse. It’s the difference between a basic model to an upgraded one. nSure.ai engineered special features that come from thinking like a fraudster or how to combat one. It was parlayed into further utilization of the solution’s AI abilities. For example “Time travel” acts like a real travel in time in the sense of copying an existing present pattern the model encounters. The model then is simulating it into the whole historical database to get insights and build predictions that better protect the merchant. Another example would be to take an offense vs defense approach. The nSure.ai Stingback feature empowers a customer to add a service that would strike back at the fraudster. It uses artificial intelligence to identify with extremely high certainty that the transaction is fraudulent. Rather than declining the transaction, the merchant approves the transaction and delivers a zero-balance prepaid card which the fraudster would then sell, thereby taking a bite out of their underworld reputation.
You can’t win fraud in digital goods without AI
We’d like to think that the same way OpenAI advanced Artificial intelligence to what we’re all witnessing with ChatGPT has a similar path for the kind of impact AI can have in the fraud prevention world. While it’s not likely to be as pervasive, it can be significantly more measurable to the top and bottom line. Furthermore, we can clearly see a path where enterprises selling online will not effectively keep up with the fraudsters if they are without it. In this cat-and-mouse game, we have to stay ahead.
*If you want to witness how the AI revolution methodology nSure.ai brings to the table transforms the digital goods world. Look at one of the next resources: