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Making Use of Data Science to Avoid Fraud

A lot of people will at the very least know a person that has fallen into the trap of online fraud. Current figures from Cifras showed that a total of 89,000 instances of fraud which happen to be record-breaking occurred in the first six months of the year in the United Kingdom. The researchers noted that as the amount of identity fraud tries against bank accounts and plastic cards has fallen; these still account for over half of the cases. Only last year, payment card fraud summed up to $21.84 billion all over the world.
Advances have been made to gain personal and financial information to commit fraud. However, this has evolved to very high sophisticated operations. It is not a case of sending out emails optimistically about princes from another country endeavoring to send you a huge amount of money. Fraudsters now purchase credit card that is stolen as well as personal information in large quantity on the dark web and as well writes programs and code to keep testing every card to know if they can be mined to gain financially.
The genesis of fraudulent payments can usually be traced back to a data breach of a company or organization. The case of Equifax which is most recent, the United State-based consumer credit reporting agency which included 143 data of individuals, is the main case study of this. Now, Equifax directed users to a spoofed user support page, not indicating that it was deception and portraying how stresses it is to copy a business’ page.
The high demand on merchants
As getting a person’s card information stolen and utilized for fraudulent payment is agreeably stressful and uncomfortable, it’s straightforward for the money to be refunded via the person’s bank. For sellers, fraudulent payments stand for a challenge that is different. For a user to get their funds back, their bank receives a refund from the seller. However, if the seller has shipped the products or carried out the service, they can always have small recourse to recover expenses. Research has proven that any dollar that is spent fraudulently costs sellers $2.40. The meaning of that is that sellers, especially the ones that are into goods and services online where the card is not present physically, must be very vigilant to try and decide if the individual purchasing the goods is who they claim to be.
One powerful way to deal with risk is to simply refuse any transaction that trips a card issuer’s fraud process – for instance, if the card has been utilized in another country that it’s given out, or if the billing address is not the same as the shipping address. While this may reduce fraud, there is every tendency that the seller will as well lose legitimate income opportunities because of that. Preventing legitimate transactions because they trip a fraud process is called ‘false positive,' and it’s said to cost sellers almost $8.6 billion just last year. There are some tools like 3D secure that can assist you with this by asking for extra information on a stand-alone secure site before concluding the transaction. However, they are not fool-proof, and consumers always regard it as friction to the experience of customers. In a trend where customers ask for an experience that is friction-free, as Uber, as well as Airbnb, have become known for, including the 3D secure surface can be dangerous to conversion.
Knowing the shopper that is behind the transaction
It is not a case anymore that the aims of online frauds are old folks who become a victim of email scams – Cifas study claims that it’s individuals in their 30s that are likely to get trapped in it. The ones that are in their 60s and above are the only age grades that have fallen for fraud cases this year. Pinpointing the consumer involved in the transaction is the solution to fraudulent transactions.
Device fingerprinting is a powerful solution for making a more vivid picture for the individual involved in the transaction. This is the system of knowing the device that a shopper utilizes to buy and can help to eradicate false positives. For instance, individuals purchasing gifts for their loved ones in other countries can be a general red flag to fraud detection process, due to it is a foreign card buying something that is shipped to a different foreign address which the card is not registered to. As the case may be, if the purchase were carried out on a device that the customer normally uses, the fingerprint of its device would be dictated, and the risk to the seller is greatly diminished. Extra data analysis utilizing algorithmic matching as well as behavioral analytics also plays an exceptional role to find a purchaser correctly.
The fight of data breaches with data science
If the fraudsters are making use of algorithms as well as data science to quickly test and validate card details that are stolen in bulk, sellers must as well make use of data science as well as predictive analysis to get ahead of the game.
Strategic uses of risk management solutions combine transaction as well as technology to set up strategic risk profiles meant to spot fraudsters on time and as well eradicate friction for customers that are legitimate.
At Adyen, for example, processing of payment is carried out for over 4,500 sellers worldwide, and also some of the world’s biggest organizations. This dataset that is comprehensive aids an intelligent assessment of every transaction so that if a seller spots a fraudulent card in use, it can be examined and as well treated with caution all over the network.
We can start predicting fraudulent act with the help of data science and machine learning and stop these transactions from occurring. An active strategy to it is to see transactions as not just one stand-alone entity. There are lots of valuable data which can be clustered with a transaction to have a holistic understanding of the shopper – like email address, card details, and login credentials. We apply enhanced linking algorithms to these clusters, with the company of individual proprietary device fingerprinting as well as network intelligence, networks, to track devices and online personas. This helps sellers to track and prevent fraudsters as they adapt to minimize risk and chargebacks (this is a system whereby fraudulent payments are refunded).
Reducing risk in the process of reducing friction
In the age of Omni channel, e-commerce and the need for frictionless payment systems, hindering fraud is not only about keeping payments that are bad out, but also about letting the good payments through. Data is the key – fraudsters crave it in their schemes to get money. However, it’s as well the best strategy to tackle fraudulent payments. It helps sellers to appreciate good customers by rewarding them and give them seamless checkout experience, and at the same time blocking fraudsters who would try out stolen cards on many devices, email addresses, and networks.