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Responsibly Integrating Artificial Intelligence (AI) and Machine Learning (ML) in Gaming

Michael Calvin
September 28, 2023
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Blog

Responsibly Integrating Artificial Intelligence (AI) and Machine Learning (ML) in Gaming

Michael Calvin
September 28, 2023
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Blog

Responsibly Integrating Artificial Intelligence (AI) and Machine Learning (ML) in Gaming

Michael Calvin
September 28, 2023
Arrow facing leftward to go back
Back to all posts
Blog

Responsibly Integrating Artificial Intelligence (AI) and Machine Learning (ML) in Gaming

Michael Calvin
September 28, 2023
Arrow facing leftward to go back
Back to all posts
Blog

Responsibly Integrating Artificial Intelligence (AI) and Machine Learning (ML) in Gaming

Michael Calvin
September 28, 2023
Arrow facing leftward to go back
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Blog

Responsibly Integrating Artificial Intelligence (AI) and Machine Learning (ML) in Gaming

Episode
Michael Calvin
September 28, 2023

Introduction

At Kinectify, we’ve received many inquiries about AI and Machine Learning (ML) for risk management. These buzzwords have been prevalent for some time and the viral success of ChatGTP earlier this year threw jet fuel on AI/ML’s popularity.

Generative AI (GenAI) and Natural Language Processing (NLP) have become ubiquitous terms among the general populace since the popularity of ChatGTP made these existing technologies more consumable to the public. With the power and ease of use of these tools, it’s reasonable to ask where Kinectify is positioned in the AI landscape.  

Kinectify exists to deploy the most advanced risk management technologies to the gaming industry. AI is an important component of this and we’ve architected Kinectify with this in mind. We also deeply value a range of modern technologies and methodologies that form the basis of our technology stack and feature sets that add dramatic impact to our end-users in addition to AI.  

Many technology companies jump on the bandwagon in an attempt to leverage these open-source technologies in a new market. Kinectify, however, is taking a disciplined and responsible approach to deploying AI/ML to the gaming industry.  

Kinectify Approach to AI

Step 1: Identifying Specific Use-Cases

Our first step to deploying AI for gaming risk management was to target one aspect of gaming risk management: anti-money laundering (AML). Gaming AML is ideal for AI/ML for both quality and productivity improvement. The use of these technologies for AML have been encouraged by the US government (FinCEN) and widely used in banking AML for years.  However, these modern technologies have yet to be introduced in an impactful way in the gaming industry.  

Kinectify is rolling out a range of AI/ML capabilities that will identify risk more immediately and process workflows almost instantaneously. Nearly all areas of AML will be enhanced including risk scoring, conducting investigative research, monitoring transactions, and filing government reports. AI/ML is impactful for pattern recognition, allowing us to be more precise in player risk management, save more player relationships, and protect the gaming ecosystem from true bad actors.  

Step 2: Data, Data, Data  

The challenge in the gaming industry is that all AI/ML technology for AML has been trained against banking industry data, which is not very applicable to gaming. This is one reason banking AML systems that tout AI/ML enter the gaming space and generate an obscene amount of false-positives and miss true risks, infuriating users who get stuck paying for systems that simply do not work.  

Additionally, big data is needed to truly understand player behavior for risk management. A single casino’s data is not sufficient for effective and authoritative AI models. A cloud-based modern AML system that can ingest large data volumes from clients and process it in near real-time was needed first. Once we designed and deployed this system, the next step was winning relationships with top gaming brands with big data. Now that we have achieved this, we are ready to train and deploy impressive AI models designed for the gaming industry.  

Step 3: Partner with Leading AI Technologists

AI/ML tools are widely accessible to software developers through open-source tools and libraries. Allowing almost anyone to integrate some form of AI/ML into their software. You no longer need the top minds from academia to create highly sophisticated AI based solutions. However, having access top data scientists is invaluable if you want to produce exceptional solutions. They can configure and tune models to achieve maximum accuracy and precision, and squeeze every ounce of value possible out of the leading edge tools in the market.

Kinectify has numerous engineers with expertise in deploying AI across a number of industries. In addition, we are partnering with the former head of data science of Netflix who has a specialized team that has worked on the leading AI products in the world including the Google Brain. We are sparing no expense to designing optimal AI capabilities for the gaming industry that will drive incredible value across the spectrum of risk management, starting with AML.  

Step 4: Educate

The success of AI/ML technologies for AML is precision and explainability.  Regulators, gaming commissions, auditors, and gaming organizations all need to understand how the system works and to understand the value it delivers. We have our work cut out for us.  

The foundation of education is a strong user-interface allowing all to understand the product by simply using it. In addition to this, we are partnering with GLI, Vector Solutions, and others to provide training and resources, allowing everyone to understand these advanced technologies being deployed in our industry.  

Considerations for AI in Risk Management

Risk management has unique needs in both transparency and repeatability. Most AI solutions focus on accuracy, but not consistency or transparency. We trust ChatGTP to work, but we have no insight into how it works and if you feed it the exact same information twice the result can be very different. This simply does not work for most risk management use cases, especially AML.  

For AI to be effectively applied to AML, the system must be explainable, transparent, and repeatable (precise/accurate). In technical terms, the solution must be idempotent meaning the system should produce the same explainable result given the same input.  

If the system lacks idempotence and explainability, you have a real problem making decisions off those results and supporting those decisions with auditors. If the system doesn’t behave in a consistent and predictable way, it provides very little value to our industry, even if it was accurate both times.  

The financial services industry succeeded with AI/ML in AML when they designed systems focused on idempotence and explainability and Kinectify is doing the same in the gaming industry with AI models trained on gaming data and a platform purpose-built for gaming AML.

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ABOUT KINECTIFY

Kinectify is an AML risk management technology company serving gaming operators both in the US and Canada. Our modern AML platform seamlessly integrates all of the organization's data into a single view and workflow empowering gaming companies to efficiently manage risk across their enterprise. In addition, Kinectify's advisory services enhance gaming operators' capacity with industry experts who can design and test programs, meet compliance deadlines, and even provide outsource services for the day-to-day administration of compliance programs.

To learn more about Kinectify and book a demo, click here.

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Michael Calvin

Michael Calvin is a technology leader driven to deliver great software through high-performance engineering teams.

Prior to joining Kinectify, Michael led the development of multiple cloud-first SaaS solutions in the construction technology, identity-proofing (KYC), and financial services markets. He has also delivered both on-premise and cloud solutions in the highly regulated healthcare and education spaces. ‍ Michael is a technologist, and enjoys the everyday challenge of solving real-world problems with technology. He is constantly expanding his skillset, learning new languages, and finding new ways to deliver high-quality, high-performance solutions faster. ‍

Michael served in the U.S. Marine Corps from 2004 to 2008. After his enlistment, he completed a BS in Information Technology Web Development and an MS in Management Information Systems while working full-time as a programmer. He has completed the High Performance Leadership course from Cornell University, the AWS Certified DevOps Engineer Professional certification, and is a Certified ScrumMaster. Away from work, Michael enjoys traveling, wine-tasting, cooking, and enjoying the perks of California living.

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