Common Fraud Techniques and How to Prevent Them

  • Barley Laing, UK Managing Director at Melissa

  • 20.05.2021 02:30 pm
  • security , Barley Laing joined Melissa in 2014 during an exciting expansion phase of the California headquartered company. As UK Managing Director with 17 years of data industry experience, his role is focused on meeting the customer onboarding; data quality and ID/compliance needs for organisations in the UK and worldwide. The team that Barley heads at Melissa’s Canary Wharf office provides sales, data consultancy and technical support for their wide range of software solutions, which help businesses to achieve efficient data verification & management, meet ID, Anti-Money Laundering (AML) and Know your Customer (KYC) requirements. Under his leadership Melissa’s UK office has experienced strong growth during the last six years, with a 46% increase in annual turnover in 2019. Over this period, he has significantly grown the UK client base, which includes: Creditsafe, MetaBank, Tranzfar, BAE Systems, Caterpillar, GSK, NHS, and the Foreign and Commonwealth Office.



Both online retail and fraud are growing quickly. While e-commerce sales worldwide are set to increase from $4.9 trillion in 2021 to $6.5 trillion by 2023, it’s estimated that retailers operating online could lose almost $130 billion in revenue to fraud worldwide by 2023.

Those in financial services have a vital role to play in preventing this growth in fraud. To do so they need to be aware of the types of fraudulent activity taking place.

Common methods include:

  • Card not present fraud: Is when a criminal gets hold of someone’s credit or debit card details – the card number, name, CVV security code, expiry date as well as the billing address, usually due to phishing or other forms of cybercrime. Because online transactions and phone orders are made by the customer not being present it’s harder for the merchant to check if a fraud is taking place.
  • Chargebacks / friendly fraud: Is when a customer makes an online purchase then contacts the card issuers to force a refund, claiming it’s the merchant’s mistake. It’s a growing problem for card issuers and merchants, with this type of fraud set to cost the retail industry up to $31 billion per annum. 
  • Triangulation fraud: This sees fraudsters placing themselves as a middleman between a legitimate customer and an unsuspecting merchant (usually an SME one). The customer unwittingly places the order through the fraudster, the fraudster purchases the customer’s goods from a merchant using a stolen credit card. The merchant ships the order, the customer receives their goods, and the fraudster keeps the money. Eventually, however, the owner of the stolen card will report the fraudulent activity on their account, and the merchant will get hit with a chargeback.

Effective ID verification starts with the right data

Financial institutions need to do what they can to prevent all types of fraud. To start with they need to ensure they have a best practice approach to KYC and AML to confirm their customers are who they say they are.

This begins at the customer onboarding stage. When onboarding a new customer anywhere in the world financial organisations need access to a global dataset of billions of records. For real-time ID verification, fraud prevention and data accuracy purposes, it must allow them to perform sufficient cross checks of the contact information provided by the prospective customers – their name, telephone number, email address, or home address. To do this effectively the dataset must leverage government agency, credit agency and utility records, as well as access politically exposed person (PEP) watch lists. 

Take verification to the next level with biometrics

To ensure those looking to access their accounts are who they say they are financial institutions should take biometrics seriously. Once a customer has passed the ID checks at the onboarding stage, biometrics – which can operate across all devices – can confirm the customer's identity with facial comparison technology. However, organisations should use a biometric algorithm that checks for eye movement as part of their ID verification process. This ensures they engage with a real live person, not a static image or avatar, to prevent fraud. Also, with no passwords or time-consuming security questions it helps to deliver a positive customer experience.

Artificial intelligence (AI) helps stop fraud

AI can work well as part of the ID verification process. One form of AI, semantic technology, associates words with meanings and recognises the relationship between them. The machine reasoning and automated pattern recognition provided by semantic technology helps to identify possible fraudulent applications in real time.

Those in financial services need to be constantly identifying new types of fraud so they can evolve their procedures and also work closely with retailers to spot any fraudulent activity amongst their customer base. Those not yet doing so need to embrace best practice processes to deliver effective ID verification and prevent fraud, and encourage retailers to do the same, particularly as they are very cost effective and easy to integrate into existing systems.

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