The mobile payments market is now an estimated $58 billion dollar global industry, with experts predicting that it will overtake the traditional online transactions. As smartphone penetration continues to climb globally, so has the number of security breaches carried out by fraudsters who are targeting this sector.
From being used as a payment gateway for fraudulent activities such as money laundering to the emergence of new forms of cyber-crime, mobile payments are at growing risk of becoming a popular target for fraudsters.
Fortunately, startups and tech firms alike are countering these threats by launching AI-powered solutions that provide users with more sophisticated security checks than traditional payment systems to protect them against fraudulent attacks.
Defining Fraud
Fraud is something that every bank will have to deal with, regardless of its size or global reach. This is particularly true in the mobile payments sector where cyber-criminals are constantly looking for new ways to steal data and commit fraudulent activities.
Fraud can take different forms, from money laundering to phishing attacks to account takeover attempts.
For a transaction to be classified as fraud, there has to have been an intent on the user’s part to deceive and cause financial loss for another party. This includes any activity that goes against the company’s policies and terms and conditions.
Predictive models are being increasingly used by banks in mobile payments to better understand how customers interact with financial institutions. This is particularly important in countries where there are high incidences of financial crimes, where the aim is to prevent fraudulent transactions and accounts from being opened in the first place.
How Does AI for Fraud Detection Work?
These solutions are powered by machine learning and natural language processing, which enable the AI platform to understand the context within unstructured data. This helps it to identify if there is any suspicious activity taking place with regard to the account.
Some of the most prominent use cases for this technology include combating money laundering, establishing stronger identity verification processes, halting cyber-attacks, and countering terrorist financing efforts.
The system constantly analyses the unstructured data of its users while also learning how each type detects any alerts that indicate potential threats. If there is a risk of fraud detected, the AI solution will immediately prevent transactions from going through until further verification can be carried out by humans.
In addition to this, the AI technology also helps to prevent transactions from being declined when a user is based in a different country to where they are trying to make the payment.
The types of data that can be analyzed through machine learning and natural language processing include emails, chat messages, and social media posts. For instance, the system will monitor the text and online tone of voice of the user to make sure that they are behaving as expected.
AI and Fraud Detection Use Cases in Mobile Banking
On the finance front, AI is now being used by banks to help them fight against fraudsters who constantly look for ways to breach their security systems. AI not only helps these institutions improve customer experience but also better protect their services from cyber-attacks.
In a bid to fight against money laundering, AI is playing a crucial role in helping banks comply with strict regulations surrounding anti-money laundering (AML) and counterterrorist financing efforts (CTF).
Risk assessment processes can be carried out by banks through the use of this technology to make it easier for them to monitor spending activity on customer accounts.
Future of AI Fraud Detection
New technologies like AI are predicted to make it easier for financial institutions around the world to prevent their services from falling victim to cyber-crime.
While some may be worried about how this technology could one day evolve, others believe that these innovations can help companies better protect their services and keep customers safe.
At the moment most banks only use AI to monitor spending activity on a customer account, but it is predicted that this could one day expand to cover other areas of the industry.
This includes helping banks to analyze data surrounding previous scams and the people who have been affected by them. This gives companies a better understanding of how they can go about coming up with new ways to combat such attacks in the future.
As AI-based fraud detection technology continues to grow, banks will begin to rely even more heavily on it to verify account holders and their purchases before they take place.
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