The use of intelligence in the gaming industry is growing rapidly, both in terms of artificial intelligence and the use of the intelligence profession. Casinos and gambling establishments have collected more intricate customer data for a longer time and on a greater scale than most other industries. Their predictive analytics systems anticipate behavior while at the same time, intelligence-led security teams ensure the protection of casino assets and the reduction of risks (money laundering, fraud, problem gambling, data breaches etc.), as well as provide a liaison point to government. However, while intelligence in the gaming industry is progressive and contemporary, investment in intelligence in organizations that regulate the gaming industry appears more limited. This article will endeavor to explain three things:
The intelligence profession found its feet in the military sphere before taking on a considerable role within national security. Since then, it has trickled down into law enforcement agencies before making its way to the private sector (with particular emphasis on financial institutions and consulting firms). While, in many instances, the regulatory world has come late to the intelligence game, the potential is extraordinary. A cornerstone of any regulator is the reduction and prevention of harm. Intelligence plays a critical role in the effectiveness of a regulator through developing greater understanding of the at-risk behaviors manifesting in the targeted population/area/entity. In gaming this role is intrinsically linked to licensing providers and involves understanding good behaviors, identifying and monitoring bad behaviors, and advising on the best ways to change behaviors. This is a conceptual step well beyond the traditional, simple compliance-checklist assessments of codes. Core analytical intelligence tools relate to trust, harm, association, systems analysis, statistical analysis, profiling, and broader risk paradigms. The intent of regulatory intelligence is to inform targeting decisions related to these at-risk behaviors.[i] The absolute requirement for any intelligence system is to ensure that the key decision-makers are not surprised. In regulation, surprises often relate to being unaware of certain types of unwanted behaviors manifesting within the regulator’s jurisdiction. Surprise arises from not being connected with other agencies who had relevant information, or results from trusting an entity because they regularly conformed to compliance checks but did not actually deserve that trust.
For example, a gaming establishment may be audited by the regulator and found to be compliant. At the same time, the same establishment may be under investigation by a law enforcement body. Worse still, it may be under investigation from another section of the regulator itself; however, due to information silos, the two sections may not be communication. This would mean that there are problems in sharing information and intelligence across the regulator as well as externally. These types of surprise often lead to increased public perception of regulatory failure and influence much of the negative reporting on regulators in recent years.
In regulation, you may commonly hear the term ‘intelligence’ used in relation to something received, for example, “we received intelligence that an incident has occurred.” What this actually is, is ‘information received’ which needs to be processed. What national security, law enforcement and regulators have in common is that, when assessing ‘threats’, much of what you are looking for is hidden from view. The idea of intelligence encompasses collecting and processing information not readily at hand, and assessing external risk factors that can impact decisions. In short, regulatory intelligence acts in the same way that it does in other sectors: know as much as you can, understand as much as you can, all in an environment filled with data and information but where there will always be gaps. Regulatory intelligence becomes even more significant if the regulator can harness the industry’s intelligence system to augment its own; thereby maximizing its collection coverage.1
But if intelligence is so useful, why isn’t it more prevalent in regulation? There are multiple barriers that create problems for the implementation of a successful regulatory intelligence program. The first is language and understanding. Intelligence started out in regulation due to the need to make sense of the vast amounts of data collected by regulatory bodies. Overtime, this has resulted in the role of the intelligence analyst being conflated with the role of ‘data analyst’. However, as the regulator modernizes, they soon realize they need an ‘intelligence officer’ to pursue and collect information from various sources beyond that held in their own databases. This requires individuals with skills in deductive and inductive reasoning, stakeholder engagement, open source collection etc; job aspects that transcend the role of data analytics.
The second barrier to regulatory intelligence success is culture. There are three overarching types of regulator: functionally orientated, process orientated and problem-solving; each with their own pitfalls. In the functionally orientated regulator, the presence of intelligence teams are uncommon and their mandate is often narrow. This usually results in the team being disconnected from the wider organization and unable to develop broader lines of inquiry. They often play a supporting role ‘as required’ to compliance officers, auditors and investigators resulting in a marginalized, reactive and reduced function. In process orientated regulators (the majority), the heavy emphasis on process and structures undermines the creativity necessary in the intelligence practice. These agencies will often focus on the process of the assessment rather than the implications and maintain a heavy focus on information already held internally. The result is the ‘intelligence’ function is usually absorbed into data analytics, policy or corporate risk areas. A problem-solving regulator is the best fit for an intelligence function and allows the flexibility and access intelligence requires to be successful. However, intelligence in this type of regulator is particularly vulnerable to organizational change (e.g. after a public regulatory failure) which may shift the regulator back to process or functional driven models.
So how can intelligence best benefit regulators? As an example, Intelligence in Regulation by Neil Quarmby highlights the following four types of intelligence which are useful across all types of regulators:
Outputs of the above include everything from strategic assessments and trend and pattern operational reports to tactical entity profiles.
Overall, intelligence is critical for any regulator that wishes to be proactive, future focused and have an emphasis on the prevention of harm and the cultivation of trust (both publicly and for regulated entities). A regulator using intelligence effectively would have good decision makers in place with clear authority at all levels of decision making; and have an intelligence capability which satisfies their decision needs.
As a final note, COVID-19 has had a dramatic effect of the gaming industry world-wide. While presenting numerous challenges, it is in times of uncertainty that the intelligence profession shines. Gaming regulators should look to their intelligence teams re-orientate their operational and strategic decision making, for example:
Anne-Maree Quarmby, COO
1 For example, Benson writes on those operating in the Maritime sphere seeking to harness human source connections to improve their awareness of compliance in the sector. J Benson, Human Intelligence: the missing piece to comprehensive maritime domain awareness, 28 April 2020 http://cimsec.org/human-intelligence-the-missing-piece-to-comprehensive-maritime-domain-awareness/43507
i Intelligence Rising, ‘Intelligence in Regulation: Professional’, 2019 https://intelligencerisingcourses.thinkific.com/courses/intelligence-in-regulation
ii Quarmby N, ‘Intelligence in Regulation’, Federation Press, Nov 2018