The type of online casino you are registered with determines the quality of support options you get. Many top online casinos tend to go all out in their support section, offering a variety of options, some of which are available 24/7. For this reason, you have to take your choice of online casino very important. If registered at a poor-quality bookmaker, you would not be able to resolve your issues in sufficient time because of the poor support method available.
Every player has their preferred support method. It could be appealing to you because of the speed or quality of help provided. Most players prefer a fast and readily available support method. The most common support methods you can find in an online casino are discussed below.
Live Chat
Live chat support is the most sought-after support method in an online casino. It ticks all the boxes for a quality support method as it is available 24/7 with a trained representative on the other end to offer help. Live chat is a relatively fast support method, and it allows players to get to the root of their issue without any unnecessary delay.
The response time attached to the live chat support method varies among online platforms. In some casinos, players get a reply within seconds, while others could take minutes. Players who use 20Bet casino live chat support method usually get a reply from an agent in under a minute.
ChatBot
This is a relatively new support method, so it is not quite common among online casinos. The chatbot feature is quite similar to that of live chat, only difference is that you are communicating with a virtual bot rather than a human agent. This support method is limited, as only preset issues can solutions be offered. The chatbot feature contains the most common problems bettors might run into while in the casino.
Email Support
Contact via email is very common as many online casinos provide their email address. It is a pretty straight forward means of contact, as it gets you in direct contact with a support agent. The response time for this support method varies. Some might reply quickly, while others might take days before you get any response.
Telephone Support
This support method is slowly ageing away, less bookmakers tend to offer help via calls. Through the contact number provided, players can ring up the casino and lay their complaints. However, with online casinos offering their services to a global audience, operating this support type becomes more difficult.
Social Media
We are currently in a time where human interactions take place via a variety of social media platforms. Many online casinos have an active social media presence. Using their social media handles, players can contact the bookmaker and get easy fixes to their problems.
Artificial intelligence is increasingly presented as a solution to one of the most persistent problems in regulated gambling: accurately measuring the black market. Supporters argue that AI can process vast data sets, detect hidden patterns, and deliver insights traditional methods cannot. Critics warn that AI may amplify existing biases and create a false sense of precision. The debate is no longer theoretical—it is shaping regulatory strategies across iGaming and sports betting.
Why Measuring the Black Market Remains So Difficult
Illegal gambling activity is designed to be invisible. Unlicensed operators avoid regulation, shift domains frequently, and operate across borders. Traditional measurement tools rely on incomplete proxies such as surveys, payment data, or enforcement reports.
Each method captures only part of the picture, making overall estimates unreliable. This is the gap AI is expected to close—but whether it can do so accurately is the core question.
How AI Is Being Applied to Black Market Analysis
AI systems are currently used to analyze large-scale datasets that would be impossible to process manually. These include web traffic patterns, payment flows, app usage data, and behavioral signals.
Common AI Use Cases in iGaming
Machine learning models can identify clusters of suspicious activity, track player migration between licensed and unlicensed platforms, and estimate market share based on probabilistic modeling. In theory, this provides a more dynamic and real-time view of the black market than static reports.
However, AI does not create data—it interprets what it is given.
The Promise: Speed, Scale, and Pattern Recognition
The strongest argument in favor of AI is its ability to scale. Unlike surveys or audits, AI models can continuously update estimates as new data arrives.
Key advantages often cited include:
ability to process millions of data points simultaneously
detection of non-obvious correlations across markets
For regulators dealing with fast-moving online gambling ecosystems, this responsiveness is highly attractive.
The Core Problem: Garbage In, Garbage Out
AI systems are only as good as their inputs. If the underlying data is incomplete, biased, or poorly defined, AI-generated outputs can be misleading.
Data Bias and Assumption Risk
Many AI models rely heavily on web traffic and payment data. This can skew results toward more visible illegal operators while missing private networks, crypto-based platforms, or local betting channels.
Without standardized definitions of what constitutes “black market activity,” AI may simply automate inconsistent assumptions rather than correct them.
Transparency and Explainability Concerns
One of the biggest regulatory challenges with AI is explainability. Policymakers need to understand how conclusions are reached, especially when those conclusions influence tax policy or enforcement priorities.
Black-box models that produce percentages without clear methodological explanations undermine trust. This is particularly risky in politically sensitive debates around gambling harm and market size.
Can AI Replace a Gold Standard—or Does It Need One?
AI is often framed as a replacement for traditional measurement frameworks. In reality, it may require an agreed-upon standard even more than human-led methods.
AI as a Tool, Not an Authority
Without a shared baseline—definitions, validation rules, and confidence intervals—AI outputs remain estimates, not facts. Used responsibly, AI can support decision-making. Used carelessly, it can create overconfidence in flawed numbers.
This is why many experts argue that AI should complement, not replace, structured methodologies.
Regulatory Implications of AI-Based Estimates
When regulators adopt AI-generated black market estimates, those numbers quickly influence licensing conditions, tax rates, and advertising restrictions. If the estimates are wrong, the consequences are systemic.
Overestimating the black market can justify excessive restrictions that weaken legal operators. Underestimating it can delay enforcement and expose players to unregulated risks.
The margin for error matters.
Industry and Operator Perspectives
Operators generally support data-driven approaches but remain cautious about AI-led conclusions being treated as definitive. Inconsistent or opaque models increase regulatory uncertainty and investment risk.
For the iGaming industry, predictability is as important as accuracy. AI that produces fluctuating estimates without clear explanations can destabilize markets rather than strengthen them.
What a Balanced AI Approach Looks Like
A credible approach integrates AI within a transparent framework. Models should be validated against multiple data sources, regularly audited, and openly documented.
This allows AI to enhance insight while remaining accountable—a critical requirement in regulated gambling environments.
The Bottom Line
AI has the potential to significantly improve how the iGaming industry understands the black market, but it is not a silver bullet. Without standardized definitions, transparent methodologies, and human oversight, AI risks amplifying uncertainty rather than reducing it.
The real debate is not whether AI can measure the black market, but whether the industry is ready to use it responsibly. In a sector where policy decisions carry high economic and social stakes, precision without accountability is not progress.
In regulated gambling and sports betting, policymakers constantly talk about channelisation, player protection, and tax efficiency. Yet all of these goals rely on one basic requirement: understanding how large the black market actually is. Without a shared, credible “gold standard” for measuring illegal gambling activity, decision-making becomes fragmented, politicised, and often ineffective. The damage caused by this lack of standardisation reaches far beyond statistics—it shapes laws, markets, and player outcomes.
What Is Meant by a “Gold Standard” in Measurement
A gold standard is a widely accepted methodology that produces comparable, repeatable, and transparent results across markets. In gambling, this would mean a consistent way to estimate illegal betting volume, player participation, and revenue leakage.
Today, black market estimates are produced using wildly different assumptions, data sources, and definitions. As a result, figures from different studies are often impossible to compare, even within the same country.
Fragmented Data Leads to Conflicting Narratives
One of the most damaging effects of lacking a gold standard is narrative distortion. Regulators, operators, and advocacy groups often cite different numbers to support opposing arguments.
How Methodology Shapes the Outcome
Depending on whether a study relies on self-reported surveys, payment data, traffic analysis, or enforcement reports, the estimated size of the black market can vary by several hundred percent. This creates room for selective interpretation rather than evidence-based policy.
When no methodology is universally trusted, the debate shifts from “what is happening” to “which numbers we prefer.”
Impact on Regulatory Decision-Making
Regulation depends on proportionality. Tax rates, licensing fees, and compliance requirements are supposed to balance consumer protection with market competitiveness. Without accurate black market measurement, that balance breaks down.
Regulators may underestimate illegal activity and assume the market is healthy when it is not. Alternatively, they may overestimate it and introduce overly aggressive measures that push legal operators out.
Both scenarios weaken regulated markets rather than strengthening them.
Consequences for Channelisation Goals
Channelisation—the migration of players from illegal to licensed operators—is a core objective in gambling regulation. Measuring progress requires a reliable baseline.
Why Channelisation Cannot Be Proven Without Standards
If the size of the black market is unknown or inconsistently defined, regulators cannot confidently say whether reforms are working. A reported increase in legal revenue does not necessarily mean illegal activity is shrinking; it may simply reflect market growth.
This uncertainty makes it difficult to justify policy changes, defend regulatory frameworks, or correct failing strategies.
Economic and Fiscal Implications
The black market directly affects tax revenue, employment, and investment. Governments use black market estimates to forecast fiscal impact and justify enforcement budgets.
Inconsistent measurement leads to unreliable forecasts, which can result in:
misallocated enforcement resources
unrealistic tax expectations
This undermines public trust and weakens long-term planning for regulated gambling sectors.
Challenges for Operators and Investors
Licensed operators depend on stable, predictable regulation. When black market size is unclear, operators face uncertainty about competitive pressure from illegal platforms.
This affects decisions on market entry, marketing spend, and product development. Investors, meanwhile, struggle to assess regulatory risk when official data lacks consistency or credibility.
Over time, this discourages capital investment in regulated markets, indirectly strengthening unlicensed alternatives.
Player Protection Suffers from Poor Measurement
Black market operators are not bound by responsible gambling rules, AML standards, or consumer safeguards. Understanding how many players use illegal platforms is essential for evaluating harm exposure.
The Risk of False Security
If regulators underestimate black market usage, they may believe player protection is improving when in reality a significant portion of activity occurs outside the regulated system. This creates a false sense of progress while vulnerable players remain unprotected.
Why Creating a Gold Standard Is So Difficult
Measuring illegal activity is inherently complex. Black markets adapt quickly, operate across borders, and deliberately avoid transparency. However, difficulty does not justify fragmentation.
The main obstacles include inconsistent definitions of what counts as “black market,” limited access to payment and ISP data, and political incentives to frame numbers strategically.
Without collaboration between regulators, academics, and industry experts, these barriers persist.
What a Standardised Approach Could Improve
A widely accepted measurement framework would not eliminate uncertainty, but it would narrow the margin of error and improve comparability across jurisdictions.
It would allow regulators to benchmark performance, identify trends, and adjust policy based on evidence rather than assumptions.
For the iGaming and sports betting sectors, this would mean more stable regulation, better player outcomes, and stronger legal markets.
The Bottom Line
The lack of a gold standard to measure the black market is not a technical inconvenience—it is a structural weakness. It distorts policy debates, undermines regulation, and weakens the legal gambling ecosystem.
Until measurement becomes consistent, transparent, and comparable, efforts to fight illegal gambling will remain reactive and inefficient. In a data-driven industry, the absence of reliable data is one of the most damaging risks of all.
