Machine learning and artificial intelligence are revolutionising the online world. They are capable of reducing costs, analysing data, recognising patterns and trends we can’t see with the human eye and making real-time decisions. Now, they are being used to help prevent financial fraud and they’re learning how to do it better every day.
Currently it is estimated that cybercrime costs the global economy approximately $600 billion, with one of the most common forms being credit card fraud which has grown considerably with the increase in the online market. As more and more people chose to transact online it is becoming increasingly important for financial services to invest in better, faster and more accurate fraud detection and prevention techniques.
Thanks to there being such a large amount of online transactions, this means that there is a huge amount of customer data available which can be studied and learnt by AI. They can learn how to identify valid credit card behavioural patterns and how to detect irregular behaviour which could be fraudulent.
Identity theft is just one of the types of fraud which has plagued the financial services. Many services now use a translytical database which performs real-time fraud analysis when you use a credit card and make payments. This means that every time you make a payment the system learns your behaviour, if this behaviour changes or shows something unusual, the system will flag it as being fraudulent.
“These models are constantly learning and being trained with real data from fraudulent transactions and real transactions so that they can better protect you. Of course, false positives are still possible but the more the system learns, the less frequent these results become,” says Mavis Hucks, chief analytics officer and writer for Last Minute Writing and Researchpapersuk.
In order to achieve the best protection for their customers, financial services often adopt a multi-layered technique, using multiple different tools including AI to deter fraudsters and protect customers. Cybersecurity companies are blossoming as their services are vital to keep businesses, customers and financial services safe. Their algorithms have improved over the last few years to help increase their accuracy.
AI is learning human behaviour at a level which understands when and where you use your credit card. For example, if you used your card abroad it would often get flagged as fraud. Now the AI has learnt how to detect an underlying pattern, it can see that people will often buy a plane ticket, accommodation and then make a transaction in a foreign country. It will compare this data to previous transactions in order to decide if the transaction should be successful or be declined.
This not only helps to protect us, but it also increases customer satisfaction by reducing the number of false positives produced by the algorithm. After all, no one likes to have their card declined when all they want is to relax on vacation!
The future of fraud detection is looking even brighter thanks to a new generation of algorithms known as Convolutional Neural Networks which are based on the way people think. They are designed on the visual cortex and use images directly as input. “The neural networks study the relationships between a user and their spending at a much deeper level than ever before. Once this technology is widely implemented cybercrime is likely to drastically be reduced,” adds Blain Meserve, senior principal consultant at Draftbeyond and Writinity.
AI provides a win-win situation for the financial sector and for anyone who uses a credit card. It saves both the banks and their customers huge costs every year. As it learns and understands more about us and the criminals, it becomes better at protecting us. It is hoped that the AI technology will continue to become more advanced and will crush financial fraud in its wake.
Martina Sanchez is an entrepreneur and content marketing specialist at Lucky Assignments and Gum Essays. She is absorbed with article writing and is a constant contributor to her blog where she touches such topics as digital marketing, SEO tips and tricks etc.