Cybersecurity for digital banking: main types of online fraud

Press Release

Madrid, 5th Nov 2020

Technology and innovation are critical for detecting fraud and keeping one step ahead of fraudsters. This is the only way that financial organisations can manage risk effectively.
GDS Modellica takes a look at the main types of online fraud and describes their intelligent solutions that combat fraud using algorithms based on decision-making technologies and machine learning.
Fraud is evolving at the same pace as technology, so innovation is key for keeping ahead of fraudsters. Risk management is currently undergoing a transformation as a result of the changing model for approving credit, with a strong trend towards a more personalised, digital, multi-channel service. However, data theft and filtering make it easier for cybercriminals to access to personal information and subsequently steal real identities or create virtual ones. These days, reduced personal interaction allows scammers to hide behind stolen or fake identities, making it easier to open accounts and access money, assets and services that they have no intention of paying for. As a result, fraudulent credit applications using fake or stolen identities has led to a significant rise in non-payments for banking organisations.
Anyone can fall victim to hackers or fraudsters, so understanding how online fraud works is the first step towards ensuring a positive experience when browsing the web or carrying out online transactions. GDS Modellica, a software company specialising in credit risk management, provides intelligent solutions to combat fraud using algorithms based on the latest decision-making technology and machine learning, which, combined with multiple sources of data such as digital verification, social networking footprints, the deep web or credit information, allow organisations to quickly detect fraudulent activities and prevent a significant proportion of fraud.
Some of the main types of online fraud highlighted by GDS Modellica include:
  • Phishing – one of the most common scams. Customers are sent an e-mail claiming to be from their bank asking them for passwords or personal data.
  • Vishing – involves impersonating the identity of a legitimate customer using VoIP, (Voice over IP). Fraudsters recreate an automated voice similar to the answer machines used by banks to make or respond to calls. The customer receives a call to confirm a credit card purchase that they actually haven’t made.
  • Smishing – the customer receives a text or WhatsApp message informing them of a suspicious credit card purchase.
  • Pharming – similar to phishing, except using websites. Legitimate customer traffic to a website is redirected towards fake websites that look real. There are two different types of attack: an attack on users or individuals and an attack on organisations. In the first type, hackers install a virus or some malware on the victim’s device. Then, when they navigate to a particular site (like their bank or an online shop) the virus redirects them to a fake website that looks exactly the same. In the second type of attack, hackers infect the company’s server so that all users are automatically redirected to the fake site. This fraud represents a much greater risk because, if the hackers do it convincingly, it’s almost impossible for customers to tell the fake site from the real one.
  • Sim Swapping – this consists of duplicating SIM cards. Every year, around 300,000 mobile phones are stolen, roughly 30 phones every hour. However, it’s not the mobile phone that the thief wants but the SIM card to pass on to hackers.
  • Scam Attacks – these are known as common scams. An e-mail is sent with the aim of tricking the recipient. The most common scams offer some sort of a financial gain in exchange for making a deposit to a current account. These scams aren’t new, but sadly, scammers still find people are easily taken in by it.
GDS Modellica managing director, Antonio García Rouco, says, “we have the technology and knowledge to support the decision-making processes for all of a financial organisation’s products and services, providing a stand-out omnichannel experience for the end customer. These include decisions such as approving a card application in minutes using an online process, assessing a loan application, or consolidating debts via smartphone, tablet, computer, etc. These processes are carried out using technology, algorithms and better practices so that financial organisations can more easily implement the required intelligence according to their business objectives.” New technologies and artificial intelligence generate benefits and opportunities to optimise business processes whilst improving cybersecurity and fraud prevention, thereby providing customers with increasingly personalised products and services according to their needs.

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