Antifraud: what it is and how it helps companies prevent scams

In the eternal fight against scammers and fraudsters, companies now have an extra ally: the so-called fraud score, an Artificial Intelligence tool capable of identifying suspicious transactions in real time and thus preventing potential fraud. 

If you've never suffered a financial scam on the Internet, you surely know a friend or relative who has fallen victim in some way. The fact that fraud is on the increase is not just your perception, but is confirmed by statistics.

To give you an idea of the size of the problem, the payment fraud attempts in fintechs increased by 70% in 2021according to the Digital Trust and Security Index released by Sift, a global fraud prevention company based in the United States.

Without a doubt, the exponential growth of digital transactions has made our lives easier in many ways (just think of how PIX is revolutionizing the way we handle financial transactions), but it has also left us much more vulnerable. 

In 2021, the banking and cards sector was the main target of scammers, with 2.3 million fraud attempts, an increase of 33% compared to 2020, according to data from Serasa Experian. Consumers aged between 36 and 50 were the main victims.

What 4KST Antifraud is like and how it helps prevent scams

To defend themselves against scammers, companies are turning to Machine Learning to improve their anti-fraud systems. 

At 4KST, we develop a Predictive Anti-Fraud Model based on the client's own data. The client may already have an anti-fraud model, but we improve it with our technology to guarantee detection and adaptation of the models in real time. We meet this demand in two ways:

- Origination Fraud: Detecting fraud in credit card origination.

- Transactional Fraud: Detection of fraudulent transactions (in person, e-commerce, etc.).

Advantages of using anti-fraud

The growing digitalization of the economy means that the fight against fraud and financial scams on the internet will continue for a long time to come. For this reason, tools such as Predictive Anti-Fraud Models have become indispensable for defending the financial health and reputation of companies.

Preventing traps is essential, first and foremost, to avoid financial losses. An e-commerce site that is the victim of a scam can lose money because of lost goods, as well as the expense it may have to compensate the eventual injured customer. The same can happen to a card company or financial institution that authorizes a fraudulent transaction.

Not to mention the fact that, although it is a victim, a company that falls into a trap can have its image affected in the eyes of consumers who no longer trust the services it offers. In this case, reputational damage can be incalculable.