Abstract The article examines the ways private policing is organized with regard to profitability. While the literature on private policing has enhanced our understanding of its growth, scope and normative implications, less is known about how ‘hybrid’ policing is conducted to make profit. Informed by 38 qualitative interviews with the seven largest insurance companies in Sweden, the article details how power relations are organized to ensure that the private policing of insurance claims supports and does not pose a threat to profit. Drawing on evidence from the empirical research, a range of issues are discussed, including the relationship between private policing and state power, and the intertwined governance of both claimants and policing actors. Introduction The aim of this article is to explore and analyse how the private policing of insurance claims is organized to produce profit. Research shows that profit is a distinctive feature of private policing (e.g. Spitzer and Scull 1977; Shearing and Stenning 1987; South 1988). In relation to the private insurance industry, there is ample additional evidence to suggest that priority is given to customer service (profit) over fraud detection (e.g. Clarke 1989; Gill 2001; Ericson et al. 2003). Similar tendencies are also found in other private business sectors (e.g. Shearing and Stenning 1987; Williams 2005). However, as Rigakos (2002) has noted, few studies have detailed how private policing activities are organized to generate profit. I would argue that when private business enforces an instrumental order (Shearing and Stenning 1984), it is not only the relationship with customers that is at stake. We must also examine how structures, relationships and forces within the private organization are organized to produce this order. In so doing, the arrangements outlined here are linked to a regulatory tradition with a long history, which, as Braithwaite (2003) notes, has often been neglected in criminology. As a result, the existing literature on private policing maps and debates the empirical as well as the normative effects of the rise of private security in relation to traditional crime (e.g. Jones and Newburn 1998; Johnston and Shearing 2003; Crawford 2006; Loader and Walker 2007; Diphoorn 2016). It follows that, as has been noted by Button and Brooks (2016), the literature on private policing is largely based on observations of the private security industry, while other modes of private policing are often neglected. The current article adds to this literature by considering a form of ‘hybrid’ policing (Johnston 1992; see Schuilenburg 2015) which targets economic crime. The research into the private policing of insurance claims remains scarce, and existing studies have primarily been located in English-speaking settings. A common thread in this body of work is the private insurance industry’s focus on customer service and its reluctance to bring fraud to the attention of the criminal justice system. For example, Ghezzi’s (1983) investigation of the emergence of in-house fraud investigation units in the United States reveals that these units operate as a private police force and that very few cases are reported to the criminal justice system (see Reichman 1983; Marx 1987). In a similar vein, Clarke’s (1989) research into insurers in the United Kingdom reveals how private insurers are reluctant to police claims fraud, and similar conclusions are supported by the work of Gill and Hart (1997) and Gill (2001). These findings are also confirmed by more recent studies (King 2013; Button and Brooks 2016). However, Button and Brooks (2016) also suggest a change in the response from ‘shallow’ policing tactics to ‘deeper’ modes of policing, in which greater emphasis is placed on the criminal justice system. In Sweden, the few existing studies primarily consider the scope of insurance fraud, public attitudes, legislative issues and the characteristics of fraudsters (Eriksson and Tham 1982; Persson and Svanberg 1998; Stenström et al. 2015). But beyond observing that insurers prefer to manage fraud without state involvement, this body of work does not detail the particulars of how this is accomplished in practice. In a series of publications, Ericson and colleagues (Ericson et al. 2000; 2003; Ericson and Doyle 2003) examine the private insurance industry as the most important institution for governance (next to the state). More specifically, Ericson and colleagues address the issue of order by making an important distinction between two mechanisms: fraud through governing and governing through fraud. The former establishes how fraud is produced by the insurance relationship itself; it is entrenched in a ‘loss ratio security nexus’ and is ‘only policed vigorously if it is seen to have substantial impact on loss ratio security’ (Ericson and Doyle 2003: 326). The latter stresses how insurance fraud is used to legitimate a continuous expansion of surveillance and control (e.g. interviews, credit checks, audits and inspections). In the same vein as other observers (e.g. O’Malley 1991), Ericson et al. (2003: 310) also connect the policing of insurance fraud to profit: External law enforcement remedies are extremely rare because they disrupt the smooth flow of insurance organisation and business relationships. Instead, fraud is handled within the private justice system of the insurance industry and its peculiar focus on loss ratio security. This article contributes to this literature by presenting findings from a non-English speaking context and detailing how private policing practices are linked to power; i.e. in what ways do power relations ensure corporate profitability? Although previous research has noted that private insurers strive to make profit and prioritize customer service over fraud detection, the empirical question of how this is accomplished in practice remains largely unanswered. Indeed, Ericson’s emphasis on governance is clearly illuminating, but the role of power is not completely clear. And although Ericson et al. (2003) outline the important connection between private justice and profit, nobody has as yet described in detail how policing actors in this system are governed in order to govern the insured population. By explicitly addressing the role of power in the governance of claimants and employees, my hope is that the article will bring additional clarity and enhance our understanding of the operations of private policing. Furthermore, existing work on the policing of insurance claims sits comfortably in the important project of moving away from a state-centred analysis of policing (see Johnston and Shearing 2003). But what is lacking is a detailed account of the role of the state and its relationship to private contributions to policing (cf. Loader and Walker 2007). As Crawford (2006) observes, the neo-liberal state—far from being redundant—retains its symbolic and social authority, legitimacy and resources and operates as the last resort with regard to other forms of control (e.g. it insures risks that private insurers cannot cover). The industry’s reluctance to use criminal law does not necessarily mean that fraud is chiefly ‘dealt with largely by the industry without state help’ (Button and Brooks 2016: 211) or ‘beyond the law’ (Ericson and Doyle 2003: 319). Nor does it suggest that civil law does not include repressive dimensions. In fact—since it is becoming increasingly difficult (and unattainable) to define rules that distinguish the customer–business relationship from policing (Gill 2002; Hörnqvist 2014; Engdahl and Larsson 2015)—it is critical to examine how state power intersects with private policing and operates beyond the criminal law. Whether referred to as ‘regulatory capitalism’ (Levi-Faur 2005), ‘the new regulatory state’ (Braithwaite 2000) or ‘the post-regulatory state’ (Black 2001), there has been a general shift away from state-led command-and-control strategies towards other modes of private and hybrid regulation (Ayres and Braithwaite 1992; Parker and Braithwaite 2003). The Selection of Fraudulent Claims As a general premise, this article analyses insurance fraud as ‘an artefact of how the insurance industry organises to deal with it’ (Ericson et al. 2000: 540). That is, the actors involved in the policing of insurance fraud are not passive participants who simply react to fraud. Instead, they are active contributors in the social construction and enactment of fraud (cf. Manning 2004). Accordingly, there is no such a thing as the true characteristics of fraudulent claims or fraudsters. This notion is incommensurate with research (e.g. Ormerod et al. 2003; Morley et al. 2006; Dionne et al. 2009) that accepts realist assumptions about fraud and that tends to reduce the policing of fraud to a matter of developing more efficient detection practices. Figure 1 outlines the study’s empirical data on insurance fraud and also illustrates the theoretical approach employed in the article. Fig. 1 View largeDownload slide The detection of insurance fraud. Thick arrows highlight the power relations examined in this article. The figures are from 2014 and were provided by Insurance Sweden Fig. 1 View largeDownload slide The detection of insurance fraud. Thick arrows highlight the power relations examined in this article. The figures are from 2014 and were provided by Insurance Sweden Figure 1 reveals how the collective efforts of claims adjustors, Special Investigations Unit (SIU) and legal departments occupy centre stage in the ‘making’ (Ericson 1993: 7) of fraud. In short, the figure illustrates that the production of fraud depends upon the ability and inclination of claims adjustors to provide special investigators with information and with suspect claimants to investigate. In this regard, the discretionary decisions made by adjustors are a critical factor in determining which claimants will be at risk of eventually becoming ‘criminals’. The figure shows that, as a result of this process, only 7,000 of the 2,000,000 claims made in 2014 were referred to special investigation. And among these, 350 claimants were reported to the police, which yielded 90 prosecutions and 35 convictions. Thus, apparently, there are many claims which could be made the subject of investigation but which are not, since claims adjustors instead choose to reimburse, reject or negotiate the claim. And there are many investigation cases that could be reported to the police, but which investigators instead choose either to re-refer to claims adjustors, or to manage themselves and where the investigations are thus not passed on to the police. Productive and repressive power: a framework for understanding private policing The empirical outcome in Figure 1 is situated in a theoretical framework of power. At one level, then, private insurers exercise power through the definition and (co) production of reality. Because private insurers are in the position to detect, select and report suspicious cases, the police are dependent upon the insurers’ definition of a claim. The claims that private insurers choose to report to the police are therefore an important source in relation to the image of fraud that is conveyed in official crime statistics. As Figure 1 also illustrates, this production of reality is chiefly carried out in the everyday practices of claims handling. Theoretically, then, the role of claims adjustors constitutes a problem for corporate management because adjustors’ collective decisions will determine customer satisfaction, profitability and premium levels. The article specifies how these strategies are incorporated into private policing practices by drawing on Foucault’s (1977) distinction between productive and repressive power. The article considers how productive forces are supported by repressive means (e.g. control technologies and negative sanctions) to ensure compliance with norms (cf. Hörnqvist 2010). Both O’Malley (1991; 2003) and Baker (2000) have presented illuminating examples of these mechanisms in relation to the field of insurance. Discipline, for example, has a long history (i.e. the use of collectors in 18th century England, see O’Malley 2003). Further, the insurance contract is centre stage in this disciplinary system, since it ‘establishes the coercive conditions for the operation of an enforcement network aimed at disciplining householders’ (O’Malley 1991: 177). Hence, the insurance contract constitutes a form of regulation that contains the insurer’s norms of conduct, is as mandatory as the law and is (ultimately) enforced by the state (Baker and Simon 2002). But the insurance relationship is also organized around moral and normative (and thus productive) beliefs about the nature of the subject engaged in the insurance relationship (Baker 2000; O’Malley 2006; cf. Rose et al. 2006). Specifically, the insurance relationship produces different notions of the liberal subject, which are then exacerbated by this relationship’s pivotal position in liberal governance. Whereas risk management technologies that are used to calculate insurance premiums envision an actor who is capable of rational and probabilistic calculations, profitability in liberal governance is also linked to an uncertain subjectivity that is expected to exhibit reasonable foresight with regard to the future (O’Malley 2000). Actors in the insurance relationship are thus exposed to productive forces which include norms that organize practices and produce notions of normality and deviance. In other words, the empirical data on the measures used by insurers to manage claimants and employees are not neutral because they are organized around particular norms that categorize and sanction subjects in the insurance relationship. One major advantage associated with Foucault’s concepts is that they situate power in an organizational setting. Rather than considering power as something that the CEO or the management team possess, the emphasis here is focused on how relations, knowledge, technologies and the circulation of power operate to promote corporate profitability. Of course, Foucault’s conceptual schema has been criticized for failing to account for individual freedom. With regard to this issue, however, Foucault has clarified his position by stating that power is only power when it operates on individuals who are free to choose their course of action (Foucault 1982). It follows, then, that claims adjustors are not absolutely repressed or disciplined by their employer. Rather, they are free to decide whether or not to reimburse a claim, but these acts are conducted in a context in which the organization attempts to intervene in the flow of events and to steer their attention and behaviours. And it is these attempts that constitute the central focus of the current article. However, the article’s focus on how power is practised, empirically, constitutes a departure from Foucault’s (1977) analysis in Discipline and Punish, which primarily draws on sources that describe how power ideally ought to be organized. A further consideration is that private insurance companies are embedded in the larger structures of the insurance industry and of state regulation (see Ericson et al. 2003). Specifically, the article argues that the role of the state and its interaction with corporate governance in the private policing of insurance fraud has been neglected in previous research. Rather than a withering away of state power—an implicit assumption in the regulation literature (see Crawford 2006)—we should consider a regulatory plurality, with the state regulating certain areas while others are partially delegated to self-regulation. For instance, the state stipulates rules that define the operations of private insurance companies and the insurance relationship. This aspect includes insurers’ legal powers to store and use data about their customers; e.g. private insurers cannot use claims history in the sales process. To ensure compliance with state law and regulation, governmental authorities (e.g. the Swedish Data Protection Authority, and the Swedish Financial Supervisory Authority) monitor the operations of the insurance industry, and the police assess whether cases of conflicts between insurers and the insured are the property of the criminal justice system or should be treated as a contractual dispute (thus falling under civil law). Moreover, it is important to understand how private power operates within and beyond criminal law. Private regulation, for example, is found across business sectors (nursing industry, banking sector, food industry) and concerns areas such as labour standards, environmental performance, information privacy and human rights policies (see Haufler 2001; Shamir 2004; Vogel 2010). The Swedish insurance industry, for its part, issues standards, recommendations and guidelines concerning (for example) the ethical and legal standards for claims investigation practices, proper customer relations, routines for archiving documents and insurance conditions. Compliance with these standards is, however, neither monitored nor sanctioned in a systematic fashion. The processes detailed in this article are largely focused on governance at the company level; i.e. the article details the strategies and technologies insurance companies use to shape the behaviours of claimants and employees in ways that promote profit, which in turn affects the image of crime. Method This article draws on 38 qualitative interviews with representatives from the insurance industry. The seven largest insurance companies in Sweden (which together represent roughly 80 per cent of the Swedish insurance market) were included in the study. The interviews were conducted in 2014/15 as a part of a project at the Swedish National Council for Crime Prevention, and lasted between 45 minutes and 2 hours. All but five of the interviews were recorded and transcribed. Participants were recruited through snowball sampling (two snowball lines were used), which helped us to discover a range of insurer characteristics as our understanding of the field evolved. For instance, I had not planned to interview staff from marketing departments, but the importance of these roles became clear as the fieldwork progressed. However, since the insurance companies refused to allow me to interview sales agents, the conclusions presented in this article only apply to the claims and investigations process. Table 1 presents the organizational positions of the participants. These interviews were accompanied by ‘Go-alongs’ (Kusenbach 2003) where I observed adjustors work in situ, asked questions and listened to their conversations with claimants. This methodology was very useful for understanding the routine tasks of claims handling, and the observations were also very important for making sense of the qualitative interviews. Table 1 Persons interviewed Interviewee type Interviews conducted Claims adjustors 11 Special investigators 9 Public relations, legal experts, industry association officials, loss prevention 8 Claims executives 4 Chief executive officers 3 Risk managers 3 Total 38 Interviewee type Interviews conducted Claims adjustors 11 Special investigators 9 Public relations, legal experts, industry association officials, loss prevention 8 Claims executives 4 Chief executive officers 3 Risk managers 3 Total 38 View Large All the roles represented among the interview participants are involved in various ways in the policing of insurance fraud and the governance of claimants. Claims adjustors are clearly the most important gatekeeper (see Figure 1), but their work is also affected by their relationship to the other roles. For example, risk managers make decisions about the terms and conditions of the insurance contracts that claims adjustors use as a basis for their decisions on whether to reimburse a loss. But the opposite is also true in that the decisions of claims adjustors provide an input that is used by risk managers to make decisions about the construction of insurance contracts. The aim of these interviews was to understand the participants’ socially constructed reality (cf. Berger and Luckmann 1991). Informed by an abductive approach (Glaser and Strauss 1967), the analysis was guided by a concern to understand the selection process and the content of the interviews. Thus, the focus on power and profit emanated from my processing of the empirical data and my reading of the existing literature on private policing. The qualitative interviews were based on several themes, but the interviewees were also free to elaborate on other themes that they felt to be relevant. The following themes were discussed in interviews: ‘Methods for detecting fraud’, ‘co-ordination/interaction’, ‘knowledge about fraud’, ‘evaluation of work performance’ and ‘fraud prevention’. The analysis was conducted in several steps. First, all the interviews were read and then subsequently coded line-by-line. In the following step, initial codes were structured into broader themes, e.g. ‘tacit knowledge’, ‘surveillance technology’, ‘indications of fraud’, ‘control’, ‘risk assessments’ and ‘coordination’. In the next step, these themes were structured into two broad themes: governing the insured and governing employees. Although there were minor idiosyncrasies between the participating insurance companies, the conclusions presented here apply to all of them. Interview data are, of course, also associated with certain limitations. Some participants were reluctant to disclose what they probably believed to be sensitive (and thus harmful) information about the claims process and investigative processes. And as has been mentioned, it would probably have been fruitful to have interviewed insurance sales agents. Another issue relates to the impact of the interviewees’ rationalizations on their presentation of reality. However, I would argue that the effect of this is rather small given the nature of the questions asked (primarily about work processes) and the total number of participants included in the study. Findings We use colours to classify customers. A multi-loss claimant is marked as yellow in our system. They had too many losses in the past year to slip through the system unnoticed. Claimants previously under investigation or with unpaid premiums are marked as red. This allows us to immediately recognize if we are talking to a customer whom we should look at more carefully. (Claims Adjustor 10) The quotation includes many of the features that will be examined and analysed in the following. For instance, it reveals how computer software is used to visualize deviancy using colour coding, and it highlights the emphasis that insurance companies place on claims history (and thus profitability). This section sets out to examine the techniques insurers use to detect insurance fraud and manage suspicious claimants. These strategic uses of technologies to guarantee profit are analysed in relation to productive and repressive power. Next, the article moves on to examine the configuration of productive and repressive forces directed at claims adjustors and special investigators. Although these findings are presented in two separate sections, these processes are in fact intertwined and the measures used to ensure that claimants are profitable cannot fully be understood without considering the managerial tactics used to make sure that private policing actors do not pose a threat to profit. The Policing of Insurance Claims and Claimants for Profit It is important to bear in mind that policyholders are referred to as different objects (of knowledge) depending on the specific organizational process in question. The claims process is the point at which policyholders activate their policy and receive value for their insurance premiums. As will be elaborated in the following, this transformation of policyholders into claimants is conducted via the application of criteria that are not spelled out in the insurance contract (i.e. in the sales process). Moreover, I will argue that the data reveal that the claims process would be accurately characterized as a sorting mechanism whereby policyholders are defined and managed as being either ‘profitable’ or ‘unprofitable’. Interviews reveal that this is accomplished using four techniques: Formal risk criteria, informal risk criteria, surveillance and civil law. In terms of power, the formal risk criteria are closely tied to productive power (profit), and the informal criteria to the authority of adjustors, whereas surveillance and the civil law are tied to discipline and repression. Formal risk criteria: claims history, value of losses, customer status Even though the detection of abnormalities is carried out manually by claims adjustors, this work relies heavily on computer software that flags risks. As reported by interviewees, the following indicators are automatically visualized on their computer screens: claims exceeding 10,000 Euros, house fires, previous investigations, the number of unpaid premiums and ‘multiple losses’ (see also Gill 2001). These indicators are all organized around profitability, in the sense that they are deviations from the conditions used to calculate premiums. That is, the statistics on losses are critical for the calculation of premiums and for assigning a policyholder to the right risk pool: We’re continuously monitoring the statistics on losses. It is the foundation for how we calculate premiums. Are we charging the right premium in relation to the risk we’re taking? […] so when a loss occurs, can we in fact afford to reimburse the customer? (Risk Manager 1) Now, while the terms and conditions of insurance contracts do not stipulate that policyholders are expected to suffer an appropriate level of losses, the practices of insurers reveal that an abnormal loss ratio is defined as having made more than five claims during the past two to three years. The data include a large number of accounts describing the pivotal role of claims history in the management of insurance fraud. In one interview, a claims adjustor stresses how the claims history is used to justify increased control: An abnormal claims history is a clear indication for us that it is time to slow down the process and take a closer look. So, the customer knows that “I’ve had a few claims now and it is only natural that my insurer wants to take a closer look at my case”. And I tell the customer that their claims history justifies closer inspection, especially if they question my decisions. When they ask “Why do I have to give you receipts, you’ve never asked for it before” I’ll tell them, “Your claims history the last year stands out and we want to take a closer look”. (Claims Adjustor 10) Formal criteria are also a productive force because they underpin a moral distinction between ‘good’ and ‘bad’ customers. At interview, claims adjustors described the morally ‘good’ customer as a claimant who pays the premium on time, has multiple insurance policies with the company, has been a client for a substantial period of time and has made only a few or no previous claims: A customer who has been a policyholder and paid the premium for many years and who’s had few claims. You don’t have to do much control, it’s their first claim, and the customer has filed the claims form correctly. It makes our work so much easier and the claim is usually reimbursed swiftly too. The customer is easy to access and answers all my questions. That’s a good policyholder. Everything is in order and we receive everything we need without delay. (Claims Adjustor 8) Another special investigator reported that although their task is to consider the interests of all policyholders, they are likely to take extra care of ‘special customers’ who have ‘been with us for several years, paid their premiums and have no previous losses […] You want to take care of them…you try to please the customer as far as possible’ (Special Investigator 5). On the other side of this dichotomy, the ‘bad’ customer is represented in the opposite terms, as being unprofitable and thus more likely to commit fraud. This representation includes features such as having a recently purchased policy, few policies, a policyholder who does not pay the premium on time, and who has multiple losses (i.e. the features that are visible to the adjustor). With regard to claims involving jewellery, for example, one claims adjustor noted that it is suspicious if the claimant knows the exact weight of the jewellery and ‘has reported similar claims and hasn’t been a customer for a long time, the policy is recently purchased’ (Claims Adjustor 32). Interviewees also reported that these customers constitute a problem for ‘the honest customer’, because insurance fraud will have an impact on premium levels. A manager, for example, reported that: ‘I think that we have a huge responsibility for the insured collective. Of course, the customers expect their insurers to take action against those who are dishonest and who cause problems for the collective’ (Risk Manager 1). But this notion of caring for the profitable segments of the insured population also exposes a tension between adjustors/investigators and those roles who are responsible for the particular insurance product. At interview, one risk manager observed that investigators often claim that fraud and misrepresentations ‘must’ make the insurance product unprofitable (hence justifying increased policing on the part of the insurers), the risk manager’s view was: ‘Yes, that might be the case, but all in all it’s still profitable (Risk Manager 1).’ An actuarial expert described this as a ‘balancing act’ between preventing fraud and taking care of the population in order to promote profitability, even though investigators argue that insurance conditions need to be rewritten in order to prevent fraud: ‘I can’t go to our executives and argue that we have to make these changes [simply] because investigators report that this is very common. I have to provide evidence: I want to make this change because… I have to present facts’ (Actuarial Expert 1). The emphasis that is placed on claims history (multiple losses), and the technology that is employed to identify deviance, institutionalizes a tolerance towards fraud in the claims process (see Ericson and Doyle 2003). Consequently, the formal criteria are geared towards identifying and managing claimants when they start to pose a threat to corporate profit. Furthermore, these indicators are not a reflection of the ‘true’ characteristics of fraud and fraudsters. Instead, their use produces a situation where loss rates, house fires, losses of expensive items, claims histories, the presence of previous investigations and diligence become knowledge criteria and indicators of fraud. Informal risk criteria: gut feeling, aggressiveness, incongruities You just get this feeling when you speak to the customer…it just doesn’t sound right… they don’t know where they parked the car before it burned up or even why they were there. They say they were there to visit a friend and they barely know the name of this person…this gives you small hints that something isn’t right. (Claims Adjustor 5) The above quotation is illustrative because it stresses the role claims adjustors ascribe to their feelings in revealing fraud. This is also consistent with previous research, which indicates that fraud detection in the claims handling process is to a large degree reliant on adjustors’ tacit knowledge, their gut feeling (Reichman 1983; Gill 2001; Morley et al. 2006). This knowledge is shaped through daily interaction with ‘normal’ claimants and by perceptions of ‘normal’ behaviour. Thus, claims adjustors’ ability to detect ‘deviance’ is acquired and shaped through training and by their experience of the constant flow of ‘normal’ claims. One adjustor observed that: ‘It’s impossible to teach someone to detect fraud. It’s your gut feeling... each call you take… it’s that call that stands out completely from all your other calls that day’ (Claims Adjustor 32). When asked to specify their gut feeling, interviewees had great difficulty making their tacit knowledge explicit. However, many mentioned incongruities in claimants’ narratives and behavioural characteristics as being indicative of fraud. Narratives that are defined as being ‘too good to be true’ constitute one example of this kind of incongruity: A car crash and the persons involved live at the same address. They crash in some remote area in the middle of the night… and just happened to be at the same place at the same time. This is a clear indication that something isn’t right. (Claims Executive 1) Besides assessing narratives, claims adjustors reported that they study a claimant’s conduct during interactions (usually telephone calls) for signs of deception. Specifically, this includes norms about proper conduct in the claimant-claims adjustor interaction. Interviewees reported that signs of a lack of self-governance such as stress, aggressiveness and persistence are interpreted as indicative of fraud (see also Ormerod et al. 2003; Morley et al. 2006). A claims adjustor described that suspicions ‘depend to a large degree on how the customers express themselves […] are they keen to assist us, what type of information do they give us, can they explain the item they lost and when they bought it?’ (Claims Adjustor 10) Control and surveillance The primary repressive methods that claims adjustors use to impose negative sanctions on claimants are surveillance technologies that can be gradually imposed and escalated. Increased control on the adjustors’ part is based on the formal and informal indicators mentioned above. A claims adjustor observed at interview that the level of control tends to increase as the value of the loss increases or deviates from definitions of ‘normalcy’: We often choose to trust the customer. By experience you know what’s normal for a loss, what type of values we’re normally talking about. When the values start to go up, we step in and conduct a more thorough control. (Claims Adjustor 10) Besides the implicit control and surveillance that takes place when adjustors use information that is available in the organization’s internal systems or that comes from interactions with claimants for administrative purposes (cf. Dandeker 1990), interviewees described several additional techniques. Deviant claimants can be required to send in receipts to prove their ownership of an item. Adjustors and special investigators also report that they run financial checks by accessing websites that contain publicly available tax information, and that they conduct social network analysis using Google, Facebook and Instagram: We use public information from the Tax Agency to establish relations between claimants. We can also use Google to see if there is information that link them together. Are they friends on Facebook, for example... and have they reported that they do not know each other…? (Special Investigator 2) Furthermore, the insurance contract gives insurers powers to test and govern claimants by forcing them to divulge private information that is held by a range of governmental authorities. This information is accessed through the forced ‘voluntary participation’ of the insured; claimants must approve requests for confidential information from governmental authorities (e.g. the Tax Office, the Social Insurance Agency, the Police or the Enforcement Agency) if this is required by the insurance company, or claims are automatically rejected. In this sense, conditions in the insurance contract have the same status as law. Insurers also contract third party specialists to investigate and analyse crashed or burned cars, home fires, a claimant’s health status and burglaries. In addition, they maintain an in-house capacity to analyse documents, passports, car keys, websites, identification cards and receipts. If needed, insurers contract private security firms to conduct covert surveillance of claimants suspected of misrepresenting their claims (see King 2013). Civil law and private justice We [special investigators] are all former police officers and have been employed as detectives. So we know when a claim should lead to a prosecution. Of course, we can’t do criminal investigations, we never go that, far because it rests on the customer to prove that there in fact has been a loss… so we assess the case from a business perspective. (Special Investigator 2) This quotation highlights how private insurers’ investigations are guided by civil law rather than criminal law. Another investigator observed: ‘We don’t conduct criminal investigations, we do civil investigations and decide whether or not it will hold up in the civil litigation process’ (Chief Investigator 2). In Sweden, there is also evidence to suggest that insurers’ reliance on civil law has increased over time. According to industry figures, insurance claims have soared over the past decade, increasing by 75 per cent since the year 2000 (Insurance Sweden 2015). Meanwhile, the number of insurance frauds reported to the police has decreased by 50 per cent since the 1990s. As was stated in the introductory section of the article, previous research suggests that the policing of insurance claims is conducted by private insurers with little support from the state (e.g. Ghezzi 1983; Reichman 1983; Clarke 1989; Ericson et al. 2003; Button and Brooks 2016). However, as previously noted, the empirical data presented here suggest that we need to look beyond the criminal law to understand the role of the state in the private policing of insurance claims. There is a private justice system (cf. Ericson et al. 2003) in which civil law defines the ‘truth’ (standards of proof, burden of proof) about a claim, and is then used to mete out justice and impose a punitive load on claimants (see also Zedner 2009). Thus, this system is repressive despite being organized around civil law. For example, interviewees reported that the law allows private insurers to increase premiums (which was also said to be a way to get rid of unwanted customers), and in some cases to cancel policies (see also Ericson et al. 2003). In cases where insurers are prohibited by law from terminating a policy (e.g. home insurance) for unwanted customers, investigators reported in informal discussions that the premiums can be significantly increased to make the cancellation a ‘voluntary’ decision on the part of the policyholder. Profit and the Policing of Claims Adjustors and Special Investigators This part of the article situates the empirical findings from the previous section in an organizational setting and, considers the role of the strategies adopted to govern claims adjustors and special investigators. It is argued that these two processes are intertwined and reinforce one another. While insurers use technologies to detect unprofitable customers, there is also a gamut of technologies for detecting employees who fail to comply with corporate norms (of profitability). Or stated differently, the policing of insurance claims cannot be fully understood without considering the policing of private policing actors themselves. As stated at the beginning of this article, the claims process is one of the most important and potentially risky organizational processes for corporate management (cf. Gill 2001). Thus, it is no surprise to find that the interviews reveal that claims adjustors are rigidly controlled to promote profitability. The primary means to ensure profit, and by the same token to reduce discretionary power, is the setting and gauging of individual goals. Interviews show that claims adjustors are measured on the following variables: (1) customer satisfaction and (2) efficiency. A ‘normal’ claims adjustor in full-time employment is expected to receive 3,000–4,000 calls per year, and in 75 per cent of these cases, the customer should rate their satisfaction as a five on a five-point scale. At interview, adjustors reported that deviant ratings (customers who rated their work performance at one or two) are monitored and referred to team managers for investigation. Claims adjustors also reported that managers often revise their decisions to in order satisfy discontented claimants: My impression is that the team leader and the claimant reach an agreement in these cases. And I know from my own experience that the team leaders sometimes want us to disregard inconsistencies and try to satisfy the customer anyway. (Claims Adjustor) A normal rate of efficiency is defined by interviewees as the individual adjustor’s ability to complete the work on at least 45 per cent of all claims within 24 hours of the loss being reported. Being able to meet these norms, ‘being normal and no risk’, is described as very important for a claims adjustor and for his or her status and future career with an employer. This means that the interaction between claims adjustors and claimants is not only important for producing knowledge about ‘deviant’ claims, but also for producing knowledge about and assessing adjustors’ work performance. In part, the emphasis placed by management on customer satisfaction and efficiency produces a situation in which adjustors who take the time that is necessary to investigate and control claims perform poorly. These techniques steer the attention of claims adjustors by supplying few incentives for detecting fraud, and in this way they reduce the discretionary space of employees (see also Gill 2001). The quantitative performance indicators described above are not only productive in the sense that they aim to generate customer satisfaction and pacify discontented claimants; they also create an opportunity for insurers to detect and manage ‘deviant’ employees who fail to comply with norms regarding the instrumental order that insurers wish to maintain. This organization around the norm of profitability is supported by a set of disciplinary methods. At interview, the most salient examples of repressive power were found in descriptions of: detailed time schedules, placement in physical space, random controls and the setting of claims limits. During the study’s observations of claims handling, it was also striking that discipline is ingrained in the adjustors’ work environment. For example, claims adjustors are placed in open plan offices, and management regulates the claims adjustors’ schedules by assigning times for each work task, i.e. when to receive new claims, when to manage pending claims, meetings and lunch. This micromanagement is represented in colour schemes that are used to divide, categorize and visualize each claims adjustor’s work day. In their interviews, for example, claims adjustors referred to their time as being ‘blue’ (receiving calls) or ‘red’ (managing pending claims). The numbers of calls they receive and cases they complete are judged, examined and compared with those of others, and every month a random sample of rejected claims are reviewed by team managers. Besides the discipline that is suggested by the spatial distribution of claims adjustors in open plan offices, repression is directed at those who do not comply with the norm of producing satisfied customers (or following the procedures that are believed to produce profit). A failure to produce satisfied customers is reported as a ground for being given less work freedom. In addition to being given less discretion in their work, adjustors who perform poorly on Key Performance Indicators (KPIs) are also reported (in informal discussions with the author) to face the additional negative consequences of having slower wage growth. Nonetheless, it is important to note that all adjustors are subjected to random controls by management: When you start, all your payments are controlled by two persons. Your level will increase as you become more experienced... I can pay out 5,000 without control. But then they will make random controls of all payments, so a payment of 50 could be examined. (Claims Adjustor 32) Protecting ‘the profitable’ from special investigators This system of productive and repressive forces must not only be analysed as a way of governing claims adjustors. Indirectly, it is also geared towards controlling the actions of special investigators. Here, I think, it is important to stress that in-house investigation units are, per se, a reputational risk; interviewees stated that no insurance company wants to be associated with policing. Instead they want to be perceived as a reliable actor when a loss occurs. Thus, as special investigators pointed out, the policing of insurance claims must be organized to avoid the risk of over-policing: We are not supposed to be like the public police […] we could have a hundred more investigators and still be busy, but we do not want to be too controlling; we must find the proper balance between control and customer satisfaction. (Chief Executive Investigator 3) Data show that this balance—what Ericson and Doyle (2003: 358) refer to as a tolerance towards fraud—is achieved by the following means: (1) making special investigators dependent on a role that is rigidly governed towards customer satisfaction and expediency (claims adjustors), (2) keeping the number of special investigators at a comparably low level, (3) the design of KPIs and (4) making special investigators dependent on legal experts. First, the organizational position of claims adjustor allows them to control the flow of information. Claims adjustors’ decisions to reject, negotiate or compensate a claim may remain concealed from special investigators, whose work is dependent on information from adjustors. At interview, for example, one special investigator referred to claims adjustors as their ‘eyes’. By imposing this structural constraint on special investigators, private insurers reduce the risk of having special investigators scrutinizing ‘good’/’profitable’ segments of the insured population. One claims adjustor also reported that they have a dialog with the investigator to make sure that they have time to investigate a case: We’ll ask them if they have time. If they feel that they are busy, well, we won’t give them new cases. In those cases, you try to pick the cases that are 100 percent certain. But sometimes they tell us that they have more time and that we can give them the cases are less certain too. (Claims Adjustor 32) Second, it goes without saying that 140 special investigators only have a limited ability to check the 2,000,000 claims that are made each year in Sweden. A third point to be made relates to the use of KPIs. Special investigators report that they, as a unit, are organized around the norm of rejection; i.e. they are expected to reject 70 per cent of the claims they choose to investigate. According to one interviewee: Our goal is to reject about 70 percent of the cases we select for investigation. We meet this target, so 30 percent of the cases we select are either wrong or we cannot prove our suspicions. We would never decide to refuse a claim if we’re not certain. If the claimant goes to court and we lose… that would be bad PR for the company. (Special Investigator 7) This quotation also indicates the fourth strategy insurers use to control special investigators; namely making them dependent on the legal department. Regardless of what a fraud investigation results in—a rejected claim, a civil litigation process or a criminal process—insurers are represented by legal experts in any judicial process. In other words, legal experts play a role that matches that of the public prosecutor. Moreover, the course of action in a fraud investigation is determined in a dialogue between legal experts and investigators: I frequently receive inquiries from special investigators. They want my opinion on legal issues such as: How should we proceed in this case? Is the evidence sufficient? Can we tell them to dispute the claim or do we need to investigate further? Is the evidence sufficient to reject the claim? (Legal Expert 1) Discussion and Conclusions The aim of this article has been to detail and examine how the private policing of insurance claims is organized with regard to profit. Informed by 38 qualitative interviews, the article has been concerned with how the overarching profit motive of private insurers affects private policing practise through the organization of both repressive and productive power. Its distinct contributions to the limited literature on the policing of insurance claims will be described and discussed in the following. The article has presented a systematic analysis of the operations of private insurers outside an English-speaking context, and reveals a high degree of consistency in the ways in which the private insurance institution polices insurance claims across Western countries. It confirms Ericson et al.’s (2003) observation that claimants are sorted into ‘good’ and ‘bad’ categories (cf. Baker 2000) using various risk indicators, and are policed largely through the denial of claims, with very few actual fraud prosecutions (see also Ghezzi 1983; Reichman 1983; Clarke 1989; Gill and Hart 1997; Button and Brooks 2016). However, in addition to confirming these previous observations, the article has presented empirical data on how this outcome is accomplished through the incorporation of productive and repressive power. Referring to this configuration of power relations, the article has shown that the policing of claimants is not analytically separate from the governance of the actors responsible for carrying out the policing of this population. The article shows that the norm of profitability is a productive force which generates conceptions of normal and deviant behaviours among both claimants and claims adjustors. It is in relation to this norm that technologies and tactics are used to monitor, assess and modify the behaviours of claims adjustors and claimants. This norm also affects the selection of potential fraud cases, since the formal risk indicators visualize deviance in terms of unprofitability (e.g. an unusual claims history, high-value losses, unpaid premiums, previous fraud investigations). Consequently, the forces of governance directed at claims adjustors produce a system that detects fraud and misrepresentations among the unprofitable customer segment. This governance involves a circumscription of the discretionary power of adjustors, which in combination with a dependency on the legal department, also serves as a strategy for exercising governance over in-house fraud units and avoiding the risk of over-policing profitable customers. These mechanisms for sorting and producing ‘profitable’ and ‘unprofitable’ claimants and for managing employees are in turn enforced via the use of repressive power. This confirms Ericson et al.’s (2003) observation that private insurers have developed a private justice system organized around loss ratio (profit and customer service). However, this article also reveals that this system is organized around civil law, which is used as a productive force to determine the truth in a claim (standard of proof, burden of proof) and is linked to repression and negative sanctions (increased premiums, rejected losses and the cancellation of policies). Civil law, then, is applied in ways that mirror the state’s use of criminal law. It is important to stress, however, that this use of civil law to mete out justice also serves to circumvent the protections that the penal code provides to the weaker party as a result of the reversal of the burden of proof and the lower standards of proof associated with civil litigation. This highlights the difficulties associated with disentangling private governance in the insurance industry from the power of the state. Ericson and Doyle (2003: 317) have argued that ‘the law is usually not even taken into consideration in deciding what to do about the conduct that could be considered illegal’. This study shows, however, that civil law remains largely in the background and is applied by private insurers in ways that resemble the use of criminal law by the public police. Thus, the fact that private insurers do not utilize the criminal justice system as their primary punitive practice, but prefer to view criminal justice as a complement to the civil litigation process, does not simply mean that private policing activities are dislocated from the state (Reichman 1983; Clarke 1989; Gill and Hart 1997; Ericson and Doyle 2003; Button and Brooks 2016). This application of civil law—which traditionally regulates relations between a business operator and customer—to impose a punitive sanction and to police insurance claims provides an empirical illustration of how the boundaries between regulation and policing are blurred (cf. Gill 2002; Hörnqvist 2014; Engdahl and Larsson 2015). In particular, it shows how our image of crime (as it is conveyed by official crime statistics) is bound up with different regulatory strategies. As was noted in the Introduction section, the article describes the importance of considering and discussing the roles of private governance and state power in private policing. The article has stressed that the state defines the ways in which customer information can be stored and disseminated and outlines the contours of the ways in which private insurers can legitimately police insurance claims. For instance, the Data Protection Act prohibits private insurers from using information from the claims process and from special investigations in the sales process. This, in combination with the role of civil law, suggests that private insurers do not govern ‘beyond the law’ (Ericson and Doyle 2003: 317). Instead, this private justice system governs via a mixture of private rules and state regulations. While this article remains sympathetic to the need to step away from a state-centred analysis of policing (Johnston and Shearing 2003), the empirical data reveal that the state (beyond the criminal law) has an important role in private policing (Crawford 2006; Loader and Walker 2007). In fact, when special investigators conduct ‘civil investigations’, they exercise both state power (by relying on civil law) and private power (by targeting unwanted and unprofitable customers). The ways in which the private policing of insurance claims is organized to ensure corporate profit (e.g. to punish beyond the criminal justice system) are to a large degree ‘anchored’ (Crawford 2006:459) in and supported by state power. However, the article also suggests that the most common scenario is that private insurers enforce their own regulation by denying a claim. But when a claimant appeals their decision, or when a claimant is reported to the police, the state—at least to a certain degree—contributes to enforcing private regulation or the rules determined by the insurer and codified in the insurance contract (cf. O’Malley 1991; Baker and Simon 2002). In addition to the fact that the empirical evidence shows that this private justice system is organized to detect, sort out and process unprofitable customers (who require ‘too much’ security in relation to their premiums), it is also disadvantages the claimant. The criminal justice system’s protection of the accused (the burden of proof lying with the state, and guilt having to be proved beyond reasonable doubt) are circumvented. The practices described here also represent different configurations of risk and uncertainty. That is, the ways in which claimants and employees are governed indicate that private insurers are managing a future that does not lend itself to precise calculations (cf. O’Malley 2000; 2006)—fraud, for example, is linked to uncertainty since it is virtually impossible to predict when a misrepresented claim will be filed. And as this article suggests, it is not primarily the fraudulent act per se that is managed; rather, it is suspicious acts among unprofitable customers. However, this way of governing an uncertain future also intersects with risk management. Besides the obvious example that risky claimants have their premiums raised or are excluded from the insured population, the techniques outlined in this article also promote risk-awareness and responsibility. ‘The multi-loss claimant’ and ‘the over-controlling employee’ emerge as persons who are in need of information about the risk they pose to the insured and the insurance company. As is the case with other subject positions, then, this information can help them to govern themselves as ostensibly free and more responsible actors by making better-informed decisions in the future (O’Malley 2006). That is, the technologies private insurers use to produce profit hinge upon the notion that claimants and employees are free subjects with a responsibility to promote corporate profitability. Acknowledgements I would like to thank Helene Oppen Ingebrigtsen Gundhus, Felipe Estrada, Janne Flyghed and two anonymous reviewers for their comments on earlier drafts of this article. References Ayres I. Braithwaite J. (1992), Responsive Regulation: Transcending the Deregulation Debate . Oxford University Press. Baker T. (2000), ‘ Insuring Morality’, Economy and Society , 29: 559– 77. Google Scholar CrossRef Search ADS Baker T. Simon J. (2002), ‘ Embracing Risk: The Changing Culture of Insurance and Responsibility’, in T. Baker J. Simon, eds, Embracing Risk , 1– 25. University of Chicago Press. Google Scholar CrossRef Search ADS Berger P. L. Luckmann T. (1991), The Social Construction of Reality: A Treatise in the Sociology of Knowledge . Penguin. Black J. (2001), ‘ Decentring Regulation: Understanding the Role of Regulation and Self-Regulation in a ‘Post-Regulatory’ World’, Current Legal Problems , 54: 103– 46. Google Scholar CrossRef Search ADS Braithwaite J. (2000), ‘ The New Regulatory State and the Transformation of Criminology’, British Journal of Criminology , 40: 222– 38. Google Scholar CrossRef Search ADS Braithwaite J. (2003), ‘ What’s Wrong with the Sociology of Punishment’, Theoretical Criminology , 7: 5– 28. Google Scholar CrossRef Search ADS Button M. Brooks G. (2016), ‘ From ‘Shallow’ to ‘Deep’ Policing: ‘Crash-for-Cash’ Insurance Fraud Investigation in England and Wales and the Need for Greater Regulation’, Policing & Society , 26: 210– 29. Google Scholar CrossRef Search ADS Clarke M. (1989), ‘ Insurance Fraud’, British Journal of Criminology , 29: 1– 20. Google Scholar CrossRef Search ADS Crawford A. (2006), ‘ Networked Governance and the Post-Regulatory State?: Steering, Rowing and Anchoring the Provision of Policing and Security’, Theoretical Criminology , 10: 449– 79. Google Scholar CrossRef Search ADS Dandeker C. (1990), Surveillance, Power and Modernity: Bureaucracy and Discipline from 1700 to the Present Day . Polity. Dionne G. Giuliano F. Picard P. (2009), ‘ Optimal Auditing with Scoring: Theory and Application to Insurance Fraud’, Management Science , 55: 58– 70. Google Scholar CrossRef Search ADS Diphoorn T. G. (2016), ‘ Twilight Policing: Private Security Practices in South Africa’, British Journal of Criminology , 56: 313– 31. Google Scholar CrossRef Search ADS Engdahl O. Larsson B. (2015), ‘ Duties to Distrust: The Decentring of Economic and White-Collar Crime Policing in Sweden’, British Journal of Criminology , 56: 515– 36. Google Scholar CrossRef Search ADS Ericson R. V. (1993), Making Crime: A Study of Detective Work . University of Toronto Press. Ericson R. V. Barry D. Doyle A. (2000), ‘ The Moral Hazards of Neo-liberalism: Lessons from the Private Insurance Industry’, Economy and Society , 29: 532– 58. Google Scholar CrossRef Search ADS Ericson R. V. Doyle A. (2003), ‘ The Moral Risks of Private Justice: The Case of Insurance Fraud’, in R. V. Ericson A. Doyle, eds, Risk and Morality , 317– 63. University of Toronto Press. Ericson R. V. Doyle A. Barry D. (2003), Insurance as Governance . University of Toronto Press. Google Scholar CrossRef Search ADS Eriksson U. Tham H. (1982), Försäkringsbedrägeri: omfattning och orsaker . Liber/Allmänna förlag. Foucault M. (1977), Discipline and Punish: The Birth of the Prison . Allen Lane. —— (1982), ‘ The Subject and Power’, in H. L. Dreyfus P. Rabinow, eds, Michel Foucault, Beyond Structuralism and Hermeneutics , 208– 26. Harvester P. Ghezzi S. G. (1983), ‘ A Private Network of Social Control: Insurance Investigation Units’, Social Problems , 30: 521– 31. Google Scholar CrossRef Search ADS Gill K. (2001), Insurance Fraud: Causes, Characteristics and Prevention . University of Leicester. Gill M. Hart J. (1997), ‘ Exploring Investigative Policing: A Study of Private Detectives in Britain’, British Journal of Criminology , 37: 549– 67. Google Scholar CrossRef Search ADS Gill P. (2002), ‘ Policing and Regulation: What is the Difference?’, Social & Legal Studies , 11: 523– 46. Google Scholar CrossRef Search ADS Glaser B. G. Strauss A. L. (1967), The Discovery of Grounded Theory: Strategies for Qualitative Research . Aldine de Gruyter. Haufler V. (2001), A Public Role for the Private Sector: Industry Self-Regulation in a Global Economy . Carnegie Endowment for International Peace. Hörnqvist M. (2010), Risk, Power and the State: After Foucault . Routledge. —— (2014), ‘ Repositioning Sovereignty? Sovereign Encounters with Organized Crime and Money Laundering in the Realm of Accountants’, Theoretical Criminology , 18: 528– 45. Google Scholar CrossRef Search ADS Insurance Sweden. (2015), Insurance in Sweden. Statistics 2014 . Insurance Sweden. Johnston L. (1992), The Rebirth of Private Policing . Routledge. Johnston L. Shearing C. (2003), Governing Security: Explorations in Policing and Justice . Routledge. Jones T. Newburn T. (1998), Private Security and Public Policing . Clarendon Press. King M. (2013), ‘ Private Policing of Insurance Claims Using Covert Surveillance’, Journal of Applied Security Research , 8: 343– 73. Google Scholar CrossRef Search ADS Kusenbach M. (2003), ‘ Street Phenomenology: The Go-Along as Ethnographic Research Tool’, Ethnography , 4: 455– 85. Google Scholar CrossRef Search ADS Levi-Faur D. (2005), ‘ The Global Diffusion of Regulatory Capitalism’, Annals of the American Academy of Political and Social Sciences , 598: 12– 32. Google Scholar CrossRef Search ADS Loader I. Walker N. (2007), Civilizing Security . Cambridge University Press. Google Scholar CrossRef Search ADS Manning P. K. (2004), The Narcs’ Game: Organizational and Informational Limits on Drug Law Enforcement , 2nd edn. Waveland Press. Marx G. (1987), ‘ The Interweaving of Public and Private Police Undercover Work’, in C. D. Shearing P. Stenning, eds, Private Policing , 172– 93. Sage Publications. Morley N. J. Linden B. J. Ormerod T. C. (2006), ‘ How the Detection of Insurance Fraud Succeeds and Fails’, Psychology, Crime & Law , 12: 163– 80. Google Scholar CrossRef Search ADS O’Malley P. (1991), ‘ Legal Networks and Domestic Security’, Studies in Law, Policy and Society , 11: 171– 90. —— (2000), ‘ Uncertain Subjects: Risks, Liberalism and Contract’, Economy and Society , 29: 460– 84. Google Scholar CrossRef Search ADS —— (2003), ‘ Moral Uncertainties: Contract Law and Distinctions between Speculation, Gambling, and Insurance’, in R. V. Ericson A. Doyle, eds, Risk and Morality , 231– 57. University of Toronto Press. —— (2006), Risk, Uncertainty and Government . Routledge-Cavendish. Ormerod T. Morley N. J. Ball L. J. Spenser C. (2003), ‘ Using Ethnography to Design a Mass Detection Tool (MDT) or the Early Discovery of Insurance Fraud’, Conference Paper: Extended Abstracts of the 2003 Conference on Human Factors in Computing Systems, 5–10 April, 650– 65. Parker C. Braithwaite J. (2003), ‘ Regulation’, in P. Cane M. V. Tushnet, eds, The Oxford Handbook of Legal Studies , 119– 45. Oxford University Press. Google Scholar CrossRef Search ADS Persson L. G. W. Svanberg K. (1998), Försäkringsbedrägerier: en kriminologisk kartläggning . Sveriges försäkringsförbund. Reichman N. (1983), Ferreting Out Fraud: The Manufacture and Control of Fraudulent Insurance Claims . Massachusetts Institute of Technology. Rigakos G. (2002), The New Parapolice: Risk Markets and Commodified Social Control . University of Toronto Press. Google Scholar CrossRef Search ADS Rose N. O’Malley P. Valverde M. (2006), ‘ Governmentality’, Annual Review of Law and Social Science , 2: 83– 104. Google Scholar CrossRef Search ADS Schuilenburg M. (2015), The Securitization of Society: Crime, Risk, and Social Order . New York University Press. Google Scholar CrossRef Search ADS Shamir R. (2004), ‘ Between Self-Regulation and the Alien Tort Claims Act: On the Contested Concept of Corporate Social Responsibility’, Law & Society Review , 38: 635– 64. Google Scholar CrossRef Search ADS Shearing C. D. Stenning P. C. (1987), ‘ “Say Cheese!”: The Disney Order that is not so Mickey Mouse’, in C. D. Shearing P. C. Stenning, eds, Private Policing , 317– 23. Sage. Shearing C. Stenning P. (1984), ‘ From the Panopticon to Disney World: The Development of Discipline’, in A. N. Doob E. L. Greenspan, eds, Perspectives in Criminal Law , 335– 48. Canada Law Book. South N. (1988), Policing for Profit: The Private Security Sector . Sage. Spitzer S. Scull A. T. (1977), ‘ Privatization and Capitalist Development: The Case of the Private Police’, Social Problems , 25: 18– 29. Google Scholar CrossRef Search ADS Stenström A. Jonsson A. Korsell L. (2015), Försäkringsbedrägerier: en selektionsstudie . Brottsförebyggande rådet. Williams J. W. (2005), ‘ Reflections on the Private versus Public Policing of Economic Crime’, British Journal of Criminology , 45: 316– 39. Google Scholar CrossRef Search ADS Vogel D. (2010), ‘ The Private Regulation of Global Corporate Conduct’, Business & Society , 49: 68– 87. Google Scholar CrossRef Search ADS Zedner L. (2009), Security . Routledge. © The Author(s) 2017. Published by Oxford University Press on behalf of the Centre for Crime and Justice Studies (ISTD). All rights reserved. For permissions, please e-mail: email@example.com
The British Journal of Criminology – Oxford University Press
Published: Mar 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
All the latest content is available, no embargo periods.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud