Collective Practices

The previous two sections discussed two individual approaches along with their limitations. This section will shift the focus to collective practices performed by manual reviewers, particularly to overcome the limitations of individual fraud assessments. It was previously argued, constructionist perspectives suggest that everyday knowledge is constructed through the use of language (Burr, 2015; Gergen, 2015). Language is considered as a medium through which shared understandings are created and realities are proposed (Burr, 2015). Social interaction also plays a crucial role in the collective assessment of fraud.

The collective evaluation of fraud entails an assessment process involving two or more members of the manual order review team, whereby different fraud understandings, ideas, judgements and realities are proposed and communicated, and some arguments are given more weight than others. Fraud then results from the outcome of the negotiations between the team members. This practice is performed particularly when manual reviewers examine challenging and conflicting cases, as illustrated below:

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I make some decisions by myself and some also in the team. In the team in particular, as I said, when the amount is too high and when I also have doubts due to the area (Agent, Female 23).

With some orders, what we do first is to ask others. We work a lot as a team in this sense, I don’t know, if I am being too suspicious towards

the order or the person. Can you look at it for me (Agent, Female 22)? You can also definitely talk about it together, just to also hear other information and opinions. Others search online completely differently

than yourself. Then it is better than pursing a trace that doesn’t get you

anywhere (Agent, 55 Female).

These quotes reflect individual reasons for performing a collective fraud assessment. As outlined, manual reviewers consult their team to compare between their own assessment and the assessment of others, in order to address their doubts. This is because some cases are considered particularly unique, in which case the group discussion helps fraud agents to review, challenge or confirm their individual assessments. What counts as fraud is then influenced, for example, by whether the case is discussed in the group, how many agents are involved in the discussion, what data are used for the assessments, whose arguments are stronger and given more weight, how experienced the agents are and how they understand risk.

The following quote shows how fraud construction results from the combination of various individual and collective practices:

Well, I look for arguments which stand for or against the case and then present them and listen to counterarguments. We weigh up how it can be. We check it again on the internet or the data the customer provided us with and decide based on the discussion which is the more likely version (Team Leader, Male 33).

This quote underlines that many approaches are taken within the same process and for examining the same case. The aim, however, is not be 100% certain in the identification of genuine or fraudulent customers, as manual reviewers are aware of

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the limitations of these proactive fraud assessments, but rather to make as accurate a decision as possible. Collective fraud examinations can also be challenging, though, because many reviewers vary in their understanding and assessments of fraud:

I prefer to cancel the suspicious order, but another colleague prefers to call them. She is not ready to cancel it. Our client returned to us on a chargeback case. She asks me what I think, and I say cancel it, but she is like no, maybe he is not a fraudster and I give him a chance. No, cancel it. Sometimes, I can cancel too many. Like a normal customer tries 20 times and I cancel, cancel and cancel and she asks me why did you do it? For me, it was not okay (Agent, Female 26).

This is a good example of how two different fraud understandings can clash in the examination of the same case. As the quote shows, while one agent aims to accept the transaction, the other prefers to cancel it. These two different views are then negotiated, with one of them representing the final outcome based on the arguments both agents bring to the discussion and which is given more weight. Furthermore, it is outlined in the following example how varying understandings of team members influence the assessments of their co-workers:

I would ask A., who would say cancel it. Had I asked M., then he would have said release it. Well, you can see, everyone has other experiences and they can point you towards something which you did not think about (Agent, 25 Female).

As outlined in the quote, the outcome of the collective fraud assessment can vary based on which co-worker is consulted. Furthermore, the quote also shows that the willingness to accept others’ fraud understandings over one’s own views can depend on the degree of experience the other person might have.

Another collective method performed by manual reviewers is the examination of chargeback-related transactions. As previously discussed, chargeback claims are usually made when a transaction was not authorised by the cardholder. This means that these transactions were initially labelled as genuine but are then re-categorised

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due to the receipt of a chargeback. Such cases are usually examined individually and discussed in the team with the aim of developing a common understanding, as outlined below:

I think we see a chargeback from Visa, MasterCard and American Express once a week or so, or every two weeks. What we do now is that

one of us works on the chargebacks and blocks the customer’s email

address, credit card and so on. We have an Excel table, so we can see who did what. We write the names, so I can pay more attention to, for instance, this country combination or maybe I need to pay attention to customers who place an order twice a day with little time between the two (Fraud Agent, 22 Female).

As the quote underlines, chargebacks can be used to review individual and collective fraud assessments, as they serve as proof that some previous assessments were incorrect. Similarly, the lack of any chargeback can be understood as a confirmation that the fraud assessments made automatically or by manual reviewers were correct. However, as addressed in Chapter One, using a chargeback as an indication of fraud is problematic, because not all fraud cases come back as chargebacks or all chargeback claims result from fraud. As it was outlined, customers can also make a chargeback claim when they ask for a refund for other reasons.

Furthermore, a common understanding in the team is also developed through making each fraud decision transparent to others by writing comments on customers’ accounts after the examination of each order. The comments usually contain a reference to the relevant data, including a long order history of the customer, consistency of the data such as matching customer and cardholder names, email addresses or any inconsistencies through varying order details such as different names, addresses and credit cards and so on. The comments are written so that co- workers can see why their colleagues accepted or declined certain transactions:

If we don’t write down this whole bunch of information, the next person

will accept it. That isn’t acceptable. The next person who opens this case

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explanation why the orders should not be accepted, I spent like 15 minutes on that and the next person who has never done Mexico, oh two positive orders I accept that, even with another email, credit card and other details (Agent, 26 Female).

As the quote underlines, the aim is also to pass on one’s own understandings to others, to encourage them think along similar lines and make similar decisions. However, as this example shows, such information can also be missed by other team members, particularly due to limited time available for fraud examinations. As will be discussed in Chapter Six, quick decisions are required to deal with large quantities of data which contribute to whether other colleagues’ assessments are taken into account.

This section discussed how manual reviewers make fraud decisions by including other team members in the process, and how fraud results from the collective evaluation. Furthermore, it was explored how certain practices are performed in the team, to develop a common understanding of fraud. The next section will discuss the final internal method of experimenting with order cancellations as a way of confirming the genuineness of customers.