Source of Funds vs Source of Wealth: Verification Challenges in International iGaming

iGaming operators are under intensifying pressure to prevent financial crime. A crucial part of anti-money laundering (AML) and customer due diligence (CDD) in this sector is confirming where players’ money comes from. Regulators and law enforcement want iGaming firms to verify both the Source of Funds (SoF) and the Source of Wealth (SoW) for their customers, especially high-rollers and other high-risk profiles. Getting this right is critical: insufficient checks can allow criminal money to flow through betting accounts unchecked, expose operators to massive fines, and damage reputations. Compliance, risk, and financial crime professionals in the gambling industry must understand the distinctions between SoF and SoW and the unique challenges in verifying them across different countries. This article explains those concepts, examines the global regulatory landscape and inconsistencies, and analyzes how operators can adopt risk-based approaches. It also presents real-world case studies where inadequate SoF/SoW controls led to enforcement actions and costly lessons, and it highlights practical tools and strategies – from open-source intelligence to enhanced due diligence – that can help overcome these verification challenges. Finally, we offer recommendations for weaving SoF and SoW checks into the fabric of onboarding, monitoring, and affordability processes to better protect iGaming businesses from financial crime risk.

Defining Source of Funds vs. Source of Wealth in AML

In the context of AML and CDD, Source of Funds (SoF) and Source of Wealth (SoW) are related but distinct concepts. It’s essential to differentiate them clearly:

• Source of Funds (SoF): This refers to the origin of the specific funds a customer uses for a particular transaction or activity. In gambling, SoF means the immediate origin of the money a player deposits or wagers. It answers the question: “Where did the money being spent right now come from?” For example, a player might fund their online casino account with money from a recent salary payment, a bank account, a cryptocurrency wallet, or a loan. Verifying SoF involves tracing that particular deposit back to a legitimate source – such as confirming that a large credit card deposit came from an account in the customer’s name funded by their paycheck, or that a wire transfer originated from a known bank account rather than an untraceable source. Essentially, SoF checks help ensure that the funds used for gambling are not the proceeds of crime (like fraud, theft, or drug trafficking) by examining the transaction-level origin.

• Source of Wealth (SoW): This refers to the origin of the customer’s overall wealth and assets. It looks at the cumulative origin of a person’s total net worth – how they acquired their money and property over time. SoW answers a broader question: “How did this customer get their wealth, and how can they afford their level of spending?” In a gambling context, SoW verification means understanding a player’s financial background – for instance, knowing whether their wealth comes from decades of business profits, a lucrative job, inheritance, property investments, or other sources. It’s not about one deposit, but about whether the customer’s overall financial situation is consistent with their gambling activity. SoW checks might involve gathering information on a person’s occupation and income, ownership of businesses, investments, or any windfalls (like inheritance or asset sales) that explain their ability to gamble large amounts. This helps gauge if their gambling funds could plausibly be legitimate. For example, if a player is betting thousands of dollars weekly, a SoW inquiry might reveal that they are a successful entrepreneur with significant income (a plausible source of wealth), versus someone with no obvious earnings which would be a red flag.

In summary, Source of Funds is about the specific money in play, while Source of Wealth is about the entire financial origin of the person. SoF is narrower and often transaction-focused, and SoW is broader and customer-focused. Both are vital in AML: SoF checks catch tainted money entering the system, and SoW checks provide context about a person’s financial background to judge if their gambling activity makes sense. In practice, these concepts work together. For instance, if a customer deposits $50,000 into an online casino, SoF verification would seek to confirm that this $50,000 came from, say, the sale of a car or a legitimate bank account, while SoW verification would assess whether the customer’s overall wealth (perhaps as a high-earning professional or business owner) supports such a large deposit in the first place.

Both SoF and SoW checks are core components of robust AML due diligence. They help an operator ensure that money circulating through betting accounts is legitimate and that the customer’s gambling expenditure is explainable by lawful means. Under many AML regulations, establishing SoF is a basic requirement for large or suspicious transactions, and establishing SoW is a key part of Enhanced Due Diligence (EDD) on higher-risk customers (for example, when dealing with politically exposed persons or unusually high spenders). Essentially, regulators expect iGaming companies to “follow the money” – not only the money a customer is gambling with (SoF) but also the money they have in general (SoW). By doing so, operators can spot red flags such as funds that might be stolen or a gambler whose spending far exceeds any known legitimate income. This provides a safety net against money laundering and also helps identify problem gambling or affordability concerns. In the next sections, we will explore why verifying SoF and SoW is challenging in the international iGaming arena and how different jurisdictions enforce these expectations.

Challenges in Verifying SoF and SoW Across Jurisdictions

Verifying the source of players’ funds and wealth is easier said than done. iGaming operators face a host of operational, legal, and technological challenges in implementing effective SoF and SoW checks, especially when dealing with customers across multiple countries. Below, we analyze these challenges in detail:

• Operational Challenges: From an operational standpoint, doing SoF/SoW due diligence on gambling customers can be complex and resource-intensive. One challenge is the high volume of transactions and customers – online gambling platforms might handle thousands of deposits daily, so identifying which warrant deeper source verification is like finding needles in a haystack. Setting the right triggers is difficult: too low a threshold and the compliance team is overwhelmed, too high and you might miss risky activity. Once a customer is flagged for review, gathering information can be cumbersome. Unlike a bank account opening (where customers expect to provide financial details), gamblers often sign up within minutes. Asking a player for documents like bank statements, pay slips, or proof of wealth after they have begun playing can meet resistance or confusion. Many customers are hesitant to share personal financial documents with a betting site, fearing privacy issues or simply disliking the intrusion, and high-value customers might take offense or move to a competitor if they feel “grilled” about their finances. Furthermore, analyzing the information provided is an operational challenge: compliance staff need the expertise to interpret bank statements or business records from potentially many different countries. If a customer provides a complex document (say, financial statements of a company they own), staff must determine if it legitimately supports the claimed wealth. Training personnel to spot red flags (like forged documents or inconsistent financial information) and to understand various income sources is a continuous challenge. All this must be balanced with not disrupting the customer experience too much – a strict check might prevent money laundering but also could drive away legitimate VIP customers if handled insensitively. Internally, there’s often a tension between compliance and revenue teams: compliance officers seek comprehensive verification, while VIP managers worry about upsetting valuable players. Achieving the right balance operationally – thorough checks that are also efficient and customer-friendly – is a tricky task.

• Legal and Jurisdictional Challenges: The international nature of iGaming means operators must navigate a patchwork of regulations and privacy laws when verifying SoF and SoW. Different jurisdictions impose different AML requirements. For example, an operator licensed in the UK must adhere to the UK Gambling Commission’s stringent rules on customer due diligence and affordability, whereas a site licensed in Malta follows EU directives and Maltese regulations, and a Curacao-licensed site might have yet another set of expectations. Keeping track of these inconsistent regulatory requirements is challenging. One country’s regulator may require verifying source of funds for any customer who deposits beyond a certain threshold (e.g. €2,000 is a common threshold in EU AML rules for gambling), while another jurisdiction might only mandate basic ID checks unless suspicion arises. There are also differences in what evidence is considered acceptable: some regulators issue detailed guidance on what documents to obtain for SoW (for instance, the UK expects documented proof of income or wealth for VIPs), whereas others are less prescriptive. This inconsistency forces international operators to either apply a highest common denominator approach globally (which can be costly and unpopular with customers in less strict markets) or to tailor their compliance on a per-jurisdiction basis (which is operationally complicated and risks a weakest-link effect). Data privacy laws add another layer of difficulty – in the EU, for instance, the General Data Protection Regulation (GDPR) requires that collecting personal financial data must be necessary and protected, so operators must carefully justify and secure any documents they request. In some cases, sharing information across borders is restricted, which hampers an operator’s ability to get a “complete picture” of a customer who might be active on their platform from multiple countries. Additionally, verifying documents from foreign jurisdictions can be legally tricky: for example, an operator might receive a bank statement from a customer in a country where it’s hard to confirm its authenticity or where banking secrecy laws limit what the operator can independently verify. Cross-border cooperation isn’t always smooth – an operator cannot easily query a foreign bank or tax office to confirm a document. All these legal and jurisdictional variances create a challenging landscape for compliance teams to navigate without inadvertently breaching either AML obligations or privacy laws.

• Technological Challenges: Technology is both a boon and a bane in SoF/SoW verification for iGaming. On one hand, modern RegTech tools exist that can automate parts of the process, but on the other hand many legacy gambling platforms were not originally designed with granular financial due diligence in mind. One challenge is systems integration: ensuring that the gaming platform, transaction monitoring systems, customer databases, and document management solutions all work together so that a spike in deposits automatically triggers a flag, which then logs any documents the customer submits and records the review outcome. Many operators struggle with fragmented systems and data silos, especially if they operate multiple brands or have grown through acquisitions – customer information might not be centralized, making it hard to get a single view of a player’s activity. Another challenge is the lack of reliable databases for verification. Unlike some bank transactions that can be checked via payment screening, verifying a source of funds often means manually examining uploaded documents (which could be scanned images that defy automated reading, or could even be forgeries). Advanced document verification tech exists (for example, tools to verify if a PDF bank statement has been tampered with), but sophisticated launderers can produce very convincing fake documents. Automation is limited because assessing source of wealth often requires judgment and context – an algorithm can flag that a customer’s deposit patterns are unusual, but determining if their wealth claim (“I sold my company for $5 million”) is credible might require human analysis and external research. Additionally, technology struggles to keep up with emerging payment methods. iGaming increasingly involves e-wallets, cryptocurrencies, and other alternative payment channels. If a player deposits Bitcoin or another cryptocurrency, tracing the source of those funds is technologically challenging – compliance officers may need blockchain analytic tools to see where the crypto came from (was it from an exchange? from a potentially illicit wallet cluster?). Few operators have fully integrated such tools, and even those that have face the complexity of interpreting the results in a meaningful way for SoF purposes. Finally, real-time intervention is a technical challenge: ideally, an operator would identify suspicious funds and intervene before the money is gambled away or withdrawn, but doing this in real time requires very agile systems and risk engines to avoid both false negatives and false positives that could interrupt legitimate play. In summary, while technology can aid SoF/SoW verification (through automation of data collection, open banking APIs, etc.), many operators still grapple with outdated systems, insufficient data analytics, and the need for manual processes, especially when dealing with cross-border data and various document formats.

In combination, these operational, legal, and tech challenges mean that verifying SoF and SoW in the online gambling world is far from straightforward. An operator might, for example, identify a high-spending customer and want to verify their wealth, but encounter issues such as: the customer is in a different country (jurisdictional issue), is reluctant to provide detailed financial info (operational issue), and the documents they eventually send are in a foreign language or format the compliance system can’t automatically read (technological issue). Overcoming these hurdles requires careful planning, adequate resourcing, and clever use of tools – topics we will discuss later in this article.

Global Regulatory Expectations and Cross-Border Inconsistencies

Across the world, regulators recognize that gambling businesses must scrutinize the sources of customer funds and wealth to combat money laundering. However, the expectations and rules differ by jurisdiction, and this inconsistency poses its own challenge in the international iGaming sector. Below is an overview of global standards and some key regional approaches, highlighting differences and commonalities:

• International Standards (FATF): At the highest level, the Financial Action Task Force (FATF) – the international AML standard-setter – provides baseline expectations for all countries. FATF classifies casinos (including online casinos) as “Designated Non-Financial Businesses and Professions” subject to AML requirements. FATF Recommendations call for gambling operators to conduct customer due diligence when transactions exceed certain thresholds (commonly around USD/EUR 3,000 for casinos) and to apply enhanced due diligence (EDD) for higher-risk customers or situations. Notably, FATF Recommendation 12 specifically requires that institutions (which extends to casinos) identify politically exposed persons (PEPs) and take additional measures like obtaining senior management approval to onboard them, and establishing the PEP’s source of wealth and source of funds. Similarly, FATF standards say that if a customer is from a high-risk country or if other risk factors are present, enhanced measures – such as more thorough SoF/SoW verification – should kick in. These international standards don’t have force of law by themselves, but they heavily influence national regulations. In essence, FATF has made it clear globally that checking where money comes from is a cornerstone of a gambling operator’s AML duties. However, how each country implements these standards can vary, leading to differences in practice.

• Europe (European Union and Key Jurisdictions): The European Union’s AML directives have steadily tightened obligations on the gambling sector. Under the 4th and 5th EU Anti-Money Laundering Directives, all providers of gambling services (not just casinos, but online betting, etc.) are “obliged entities” for AML. The EU framework requires customer due diligence for any transaction or series of linked transactions of €2,000 or more in gambling. That means if a player’s deposits reach €2,000, the operator must verify the player’s identity and, as needed, gather additional information like source of funds. Moreover, EU rules require Enhanced Due Diligence in specific cases: when dealing with PEPs, when transactions involve high-risk third countries, and whenever a higher risk of money laundering is identified. Establishing source of wealth is explicitly mandated as part of EDD for PEPs and in other high-risk scenarios. For example, a licensed operator in Malta or another EU state must obtain information sufficient to determine a customer’s SoW and expected activity level, commensurate with their risk profile – and crucially, if the risk is high, the operator should seek independent documentation to verify the SoW/SoF (such as asking for supporting documents and not just taking the customer’s word). While the EU provides this broad framework, there can be differences in enforcement and guidance among member states. For instance, regulators in jurisdictions like Malta, Sweden, or Spain may issue their own guidelines on what evidence of SoF/SoW is acceptable or how quickly checks should occur after the threshold is met. There is also sometimes a gap between law and practice – some markets might have the rules on paper but historically less rigorous enforcement compared to, say, the UK. Nonetheless, the overall trend in Europe is toward greater scrutiny of gambling funds. Notably, European regulators have started cooperating more and sharing information, so an operator weak on SoF/SoW checks in one EU country might not find refuge for long, as the expectation of robust AML compliance is high everywhere in the bloc.

• United Kingdom: The UK, home to one of the world’s largest online gambling markets, has some of the most stringent regulatory expectations regarding SoF and SoW. The UK Gambling Commission (UKGC) requires licensed operators to conduct thorough customer due diligence and ongoing monitoring, and it places a strong emphasis on affordability and source of funds checks, especially for VIP customers or those showing signs of heavy spending. In practice, this means UK operators must proactively verify the income or wealth of customers who reach certain spending thresholds or exhibit risky behavior. The UK has been a pioneer in linking responsible gambling with financial due diligence – the idea that if someone is gambling far more than their apparent means, the operator has a duty to intervene, both to prevent harm and to ensure the money isn’t illicit. The UKGC has published specific guidance on managing “High-Value Customers” (HVCs, often referred to as VIPs). After a series of scandals and compliance failings, new rules were introduced requiring that before giving VIP status or incentives to any player, the operator must vet the player’s source of funds, verify their occupation and income, assess affordability, and ensure a senior manager is accountable for that customer’s compliance. The clear regulatory message is that being wealthy or a big spender does not exempt a player from checks – if anything, it demands more scrutiny. The UK’s regulatory approach also expects an operator to document everything – so if regulators come knocking, the company can produce evidence of what SoF/SoW checks were done for each high-risk customer. The UK has consistently enforced these expectations with hefty penalties. Many UK enforcement cases (some detailed in the case study section below) involve operators fined millions of pounds for failing to obtain adequate evidence of customers’ source of funds or for ignoring obvious red flags about affordability. In summary, any operator in the UK or serving UK customers must treat verifying SoF and SoW as not just a legal obligation but a core part of their risk management, with very clear guidelines to follow (and little sympathy from regulators if they fall short).

• North America (United States and Canada): In the US and Canada, online gambling is regulated on a regional basis (state/provincial level for the most part), but general AML principles still apply and are often enforced by national authorities. In the United States, land-based casinos have long been subject to the Bank Secrecy Act (BSA) regulations and oversight by the Financial Crimes Enforcement Network (FinCEN). Large casinos are considered a type of financial institution under the BSA, which means they must implement AML programs, report large cash transactions (any cash in or out over $10,000 in a day triggers a Currency Transaction Report), and file Suspicious Activity Reports (SARs) for any transaction that looks suspicious (with a federal reporting threshold of $5,000 for casinos, and in practice even lower if something is clearly off). While these rules historically focused on cash handling in physical casinos, the same principles are expected in the digital realm as states legalize online sports betting and iGaming. Online operators in states like New Jersey or Pennsylvania must have compliance programs that mirror those casino standards. One difference in the US approach is that there is not a standardized requirement to gather source of wealth information on every high roller by law; instead, it is more risk-based and driven by suspicious patterns. For example, a US online sportsbook might not ask every big depositor for proof of income upfront, but if a customer’s activity raises red flags (say extremely large deposits from unknown sources, or a customer who is a foreign VIP), the expectation is the operator will perform due diligence, which could include investigating SoF or SoW and filing a SAR if they can’t get comfortable with the explanation. FinCEN has penalized casinos that failed to dig into obvious high-risk patrons – for instance, cases where VIPs with criminal notoriety gambled millions without the casino asking where the money came from or filing reports. As online gambling grows in the US, there’s an increasing focus on voluntarily adopting best practices like checking source of funds for high-risk customers, even if not explicitly spelled out in every state regulation, because regulators and enforcement agencies view it as part of an effective AML program. In Canada, casinos and online gambling (where permitted, such as Ontario’s regulated iGaming market) are overseen by provincial authorities and FINTRAC (the federal financial intelligence unit). Canadian regulations similarly require identifying customers over certain thresholds and performing EDD for high risks. Recent Canadian casino scandals (particularly in British Columbia earlier, and the general awareness from global cases) have put pressure on operators to verify large cash buy-ins or online deposits. They must document efforts to determine if funds are legitimate (for example, some casinos in Canada now ask for source of funds declarations when a patron brings in beyond a certain amount of cash). For online play, an operator in a regulated province would be expected to flag and investigate if a player’s spending seems disproportionate. Overall, in North America the trend is that while explicit SoW checks might not be as codified as in the UK, regulators are increasingly expecting operators to “know their customer” at a deeper level and not turn a blind eye to implausible transactions. The patchwork of state/provincial rules can create some inconsistency, but any major operator aiming for a strong compliance posture will implement SoF/SoW verification for high-risk cases as a standard part of their program.

• Other Regions (Asia-Pacific and Beyond): In other parts of the world, standards are also tightening, though practices vary. Australia has faced high-profile casino inquiries (e.g. Crown Resorts was hit with unprecedented fines and licensing repercussions for AML failures, which included not properly vetting VIP junket clients’ funds). Australian regulators now mandate rigorous due diligence on big players and junket partners – effectively requiring casinos to establish source of funds for anyone bringing in large money, especially from overseas. Many Asia-Pacific jurisdictions (like Singapore, Macau for land-based, the Philippines for licensed online operations targeting abroad, etc.) have been under pressure from the APG (Asia/Pacific Group on Money Laundering) to strengthen casino AML controls. This includes ensuring that casinos verify the source of large deposits and the background of high rollers, given the region’s issues with capital flight and corruption proceeds. For online gambling hubs like the Philippines, where numerous “POGO” online casinos operate, regulations have been evolving to require more stringent checks (in part because of some scandals involving Chinese high-rollers and illicit funds). Some smaller or emerging markets historically had weaker oversight – for instance, offshore online casinos in certain Caribbean or Pacific island jurisdictions might not have been closely monitored on SoF/SoW – but international pressure and the risk of being grey-listed by FATF is pushing these places to improve their laws. Global inconsistency remains, however, in how aggressively rules are enforced. A player gambling on a Curacao-licensed site might not face the same level of questioning about their funds as one on a UK-licensed site, for example. This unevenness can tempt “regulatory arbitrage,” where high-risk individuals might gravitate to sites in lenient jurisdictions. Nonetheless, there is a clear movement toward harmonization of expectations: through international cooperation, information sharing, and high-profile enforcement actions, regulators worldwide are signaling that operators anywhere should err on the side of doing more due diligence, not less. Many multinational gambling companies therefore choose to implement relatively consistent standards group-wide, often following the strictest regime they operate under (like UK or EU rules), to ensure they are not caught out in any one country. For compliance officers, the key is staying abreast of each jurisdiction’s specific requirements (which can change with little notice) while maintaining a robust global baseline that meets core principles: identify your customer, monitor their transactions, and take reasonable measures to verify any funds or wealth that seem significant or suspicious.

In summary, global regulatory expectations emphasize a risk-based but proactive approach to SoF and SoW verification. All reputable jurisdictions expect that an iGaming operator knows where a customer’s money comes from, especially for higher-risk customers, even if the exact triggers and documentation requirements differ. The inconsistencies in rules (thresholds, definitions, documentation standards) require operators to be agile and knowledgeable. In cross-border scenarios – say a company licensed in Country A serving a player in Country B – operators often choose to comply with the stricter of the two regimes or whichever applicable law is stricter, because failing to meet a major regulator’s expectations (like the UKGC or an EU regulator) can have serious consequences. We’ve also seen regulators collaborate: for instance, if a UK-licensed operator has a compliance issue with a foreign VIP, the UK regulator may communicate with that VIP’s home country regulator. The direction of travel is clear: no matter where an online gambling company operates, the expectation is that it actively checks and evidences the legitimacy of customer funds, particularly when large sums or red flags are in play. Those who don’t will likely face enforcement action sooner or later.

Risk-Based Approaches for Different Customer Profiles

Effective SoF and SoW verification in iGaming hinges on a risk-based approach – focusing resources on the customers and scenarios that pose the greatest potential risk. Not all players are equal from a risk perspective. Here we examine how operators tailor their due diligence for certain high-risk customer profiles and situations, such as high-net-worth VIPs, politically exposed persons, and customers from high-risk jurisdictions:

• High-Net-Worth Individuals and VIP Gamblers: These are customers who gamble large amounts, often designated by operators as VIPs or “high value customers.” By virtue of the sums of money they can bring to (or withdraw from) a gambling platform, they present a higher inherent risk of money laundering or illicit funds being in play. A risk-based approach means that the bigger the customer’s transactions, the deeper the investigation into their financial background should go. For a high-net-worth (HNW) player, an operator will typically conduct enhanced due diligence to establish that the person’s wealth is real and legitimate. This could involve verifying their occupation or business via independent sources (company registries, news articles, etc.), checking their income (for example, requesting proof of earnings or net worth statements), and ensuring that their gambling activity is proportionate to known wealth. One common strategy is setting tiered thresholds: e.g., if a customer deposits or loses more than £X in a short period, they are escalated for a SoF/SoW review. VIP players are often assigned personal account managers – a best practice is to involve those managers in gathering information (in a tactful way) about the VIP’s wealth and source of funds. For instance, a VIP manager might know that a particular big spender sold a tech company for millions (thus explaining their wealth) – that information should be documented and, if high risk, corroborated (say, by seeing a news report of the business sale or by obtaining some evidence from the client). Regulators expect that being wealthy does not get one a free pass; in fact, it’s well-documented that some VIP programs historically turned a blind eye to sources of money in pursuit of revenue, which has led to sanctions. A risk-based approach now requires that for HNW customers, affordability checks are performed – meaning the operator assesses whether the losses or bets are sustainable compared to the customer’s known or declared wealth/income. If a supposed millionaire is betting like a millionaire and provides proof of wealth, that might be acceptable, but if someone claiming a modest background is betting huge amounts, it’s a glaring warning sign. In short, for high-value customers the operator should seek clear evidence of wealth (or a legitimate income stream) commensurate with their gambling and keep monitoring continuously. High rollers often receive continuous monitoring and periodic review of their status – for example, an annual review to update their source of wealth information, since wealth can change over time. The risk-based mindset is: the greater the value and frequency of transactions, the more detailed and frequent the checks.

• Politically Exposed Persons (PEPs): Customers who are PEPs pose distinct risks because they are individuals in positions of political or public influence, and therefore are at higher risk of corruption or bribery. Examples include government officials, politicians, high-ranking military officers, state enterprise executives, as well as their immediate family members and close associates. The presence of a PEP in one’s customer base elevates risk as their wealth could potentially include illegal kickbacks or misappropriated public funds. A risk-based approach mandates automatic enhanced due diligence for any PEP customer. As soon as a player is identified as a PEP (often via routine PEP and sanctions screening of the customer database), the operator should require Source of Wealth information at onboarding or as early as possible. In fact, regulations worldwide (as discussed, FATF and EU rules) explicitly require establishing SoW for PEPs. Practically, this means asking the PEP to declare how they accumulated their wealth (for example, years of salary and investments, or inheritance, etc.) and crucially, requesting documentation to support that. Because PEPs might be tempted to disguise illicit wealth through gambling, an operator must be skeptical and seek external validation. For instance, if a customer is a known PEP – say a mayor of a city or a general in a foreign military – the compliance team might collect their financial disclosure statements (if they are public officials required to file those), look for news about their business dealings, and require evidence for any large funds (perhaps bank statements or proof of sale of an asset). Additionally, any transactions by the PEP should be under tighter monitoring: unusual patterns (like funds coming from third parties or sudden spikes in betting volume) should prompt immediate scrutiny. Another aspect is that PEPs might react negatively to being asked for personal financial documents (some feel it’s an affront to their status). Compliance staff need to manage such interactions carefully, but still firmly – the rule is that no exceptions can be made for PEPs if the law says SoW must be obtained. Many casinos and betting firms have learned that failing to question a powerful client is a huge mistake; there are cases where casinos accepted money from relatives of dictators or politicians under sanction, leading to enforcement action when discovered. Therefore, the risk-based approach for PEPs is essentially a zero-tolerance stance: treat them as high risk from the start, demand robust SoF/SoW proof, involve senior management in approving the relationship, and keep an eagle eye on their play. If a PEP can’t adequately explain or document their source of wealth, the safest course is often to refuse or sever the relationship to avoid laundering potentially corrupt funds.

• Customers from High-Risk Jurisdictions: Geography plays a major role in risk assessment. Customers who are residents or nationals of countries with high levels of corruption, weak AML controls, sanctions, or significant organized crime presence will typically be classified as higher risk. Examples might include jurisdictions on the FATF “high-risk” or “grey” lists, or countries under international sanctions. For such customers, a risk-based approach again means enhanced checks. An operator should be asking: “Given this customer’s country of origin, do we need extra assurance about their money?” In practice, enhanced due diligence for high-risk jurisdictions involves requiring more documentation and verification of funds. If a player from a country known for financial crime risks starts gambling large amounts, the operator should request detailed SoF – e.g., “provide a bank statement showing the origin of the $10,000 you deposited” or “we need documents showing how you obtained this money (did you earn it, inherit it, etc?).” There is also often a need for independent verification because documents from certain countries might be easier to forge or less reliable. For instance, if a document is supplied in a foreign language, it should be translated and perhaps certified. Operators often rely on databases or intelligence reports about country risks to decide what extra steps to take. Funds coming from a bank in a secrecy haven or via a payment processor in a loosely regulated region could be a red flag needing additional corroboration. Moreover, customers in high-risk jurisdictions might not have as much digital footprint or easy ways to verify their wealth (for example, fewer public company records or media reports), so using specialized due diligence firms or forensic accountants to verify wealth is sometimes warranted for very high-risk cases. Another scenario is if the payment itself comes from a high-risk country (even if the customer is elsewhere) – for example, a player in the UK depositing from a bank account in a Caribbean island known for shell companies. That too should raise questions and likely prompt a SoF inquiry. Essentially, the risk-based approach dictates that the higher the country risk, the more an operator should do to confidently establish that the funds are clean. This might include obtaining references or financial statements, verifying identities more stringently, and keeping such accounts under frequent review. It’s worth noting that regulators will expect operators to be aware of current geopolitical risks; for example, with sanctions on certain countries, any customer with ties to those places should undergo sanctions screening and additional source-of-funds checks to ensure no sanctioned individual or entity’s money is involved. Ignorance of a customer’s background is not a defense if that customer launders money through the site.

In addition to these profiles, a truly risk-based approach also looks at behavioral red flags that can occur in any profile. For example, a customer (even not high-value or not from a risky country) who suddenly changes their deposit pattern dramatically, or who structures deposits just under reporting thresholds, or who requests unusual payment methods – these situations might also prompt SoF/SoW checks under a risk-based system. The overarching principle is proportionality: low-risk customers (small-stakes, well-known, local residents with stable profiles) get standard monitoring, whereas higher-risk customers (by virtue of wealth, position, or geography) get increasing levels of scrutiny. This tiered approach allows operators to allocate their compliance resources where they matter most, and it aligns with regulatory expectations that companies must be able to demonstrate they know more about the riskiest customers.

Implementing such differential treatment requires clear internal policies. Many operators establish risk-rating models for players (considering factors like deposit levels, loss levels, country, PEP status, etc.) and tie specific due diligence actions to each risk level. For example, for a medium-risk new customer perhaps verify employment and source of funds for first large deposit; for a high-risk customer (like a PEP or very high spender) demand a full source of wealth review and senior management sign-off. This structured approach helps ensure consistency and that nothing falls through the cracks.

In summary, whether it’s a millionaire entrepreneur, a government official, or a player from a far-flung jurisdiction with weak oversight, different customer profiles call for tailored verification measures. By focusing on these high-risk categories, gambling operators can better prevent illicit money from mingling with gambling revenues and avoid regulatory trouble. As we’ll see next, failures to apply such risk-based verification have led to notable enforcement cases that underline why these practices are so vital.

Case Studies: When SoF/SoW Lapses Led to Trouble in iGaming

Real-world cases vividly illustrate what can go wrong when online gambling companies fail to properly verify customers’ source of funds or wealth. Below are several international iGaming case studies that highlight the consequences – from enforcement actions to unwanted exposure – and in some instances how these incidents spurred process improvements:

• VIP with Stolen Funds at Betway (UK): In a high-profile UK case, online betting firm Betway was penalized £11.6 million after investigators found it had allowed a “VIP” customer to deposit and lose huge sums (£8 million deposited, £4 million lost over several years) without sufficient source of funds checks. It later emerged that significant portions of this VIP’s money were stolen from their employer. Betway’s staff had often just taken the customer’s word about his wealth or source of money (at one point accepting a vague claim that funds were inherited or business proceeds, without verification). This lack of verification meant the operator was effectively unwittingly enjoying revenue from stolen money, which is both an AML breach and a public relations disaster. The UK Gambling Commission’s investigation noted that simply asking for documentation or doing open-source research could have revealed discrepancies – but those steps weren’t taken until far too late. The record fine served as a clear warning to the whole industry that VIP programs must not prioritize profits over compliance. Following this case, many UK operators reviewed their VIP procedures, and the regulator introduced stricter rules as mentioned, mandating upfront SoF and SoW checks for high-value customers before they receive VIP perks. Betway itself reportedly overhauled its onboarding for big spenders, incorporating third-party wealth checks and more rigorous ongoing monitoring, to prevent a repeat of such lapses.

• Affordability Neglected for a “Nanny” at Caesars (UK): In another UK enforcement example, Caesars Entertainment’s UK division (which ran both online and land-based betting at the time) was fined (£13 million) for multiple AML and social responsibility failures. One striking case in the regulator’s report was a self-identified self-employed nanny who was allowed to lose £18,000 in a year without the company verifying her income or affordability. Common sense would question how a nanny (a typically modest-paying job) could afford that level of loss. Additionally, a retired postman lost £15,000 in under two months and a politically exposed person lost £795,000 over a year, all with inadequate source of funds or wealth checks by the operator. These cases showed an overall failure to implement risk-based checks: even when customers had jobs or profiles that seemed inconsistent with their gambling spend, the operator did not follow up sufficiently. The PEP, in particular, should have undergone enhanced due diligence, but the company had not obtained proper evidence of his wealth or the origin of the nearly £800k he gambled, which could have been a serious red flag. The enforcement action not only penalized Caesars but also led to several personal management license holders (individual executives) being formally warned or penalized, underlining that management must enforce these checks. This case reinforced that affordability is a key component of AML in gambling – if someone’s spending appears to outstrip their legitimate means, it demands an intervention to either verify funds or stop further play. Post-incident, the UK industry widely increased training for staff to spot such discrepancies (“does this customer’s job title or known profile make sense for their spending?”) and to escalate those cases to compliance for review.

• White Hat Gaming and Unverified “Winnings” (Multi-Jurisdiction): White Hat Gaming, an operator with international online casino brands (licensed in places like Malta and the UK), was fined £1.3 million by the UKGC after failing to conduct adequate source of wealth checks on two high-spending customers. In one case, a customer had lost around £70,000. When asked for a source of funds, they provided a bank statement that showed a single £30,000 deposit, claiming it was winnings from another gambling operator. White Hat’s team accepted this explanation at face value and did not verify it – for example, they did not confirm with the other operator or seek evidence of those supposed winnings. This was deemed a failure because simply seeing money in a bank statement isn’t enough; one must also ask “Where did that money itself come from?”. It could have easily been a circular movement of illicit funds or an incomplete story. The regulator’s stance was that the company should have corroborated claims of funds coming from gambling wins (which might involve obtaining proof of that win or considering it with skepticism since using one gambling win to fund more gambling can still be problematic if the initial money was illicit or if it indicates problem gambling). The enforcement pointed out that frontline staff often didn’t make good use of the information customers provided – either not spotting red flags in bank statements or not following up on obvious anomalies. White Hat Gaming, after this fine, reportedly invested in better training and brought in additional verification tools to examine documents more closely (for instance, tools that can flag if a bank statement is inconsistent or if an account doesn’t show the expected salary credits that match a customer’s claimed occupation). The case serves as an example to all operators that verification means going beyond the surface – if something looks odd in a customer’s finances, you must investigate until you’re satisfied or else refuse further business.

• Matchbook (Triplebet) – High Roller Anomaly: In 2020, Triplebet (trading as the betting exchange Matchbook) had its UK license suspended and was fined (approximately £740,000) for AML and social responsibility failures. A notable issue cited was the failure to establish source of funds for a customer who gambled extraordinarily high amounts (reportedly one customer was able to gamble £2 million in a single day) without proper checks. This kind of outlier activity should have immediately triggered an in-depth look at how and why that customer had such funds. The fact that it didn’t happen indicated serious gaps in the company’s risk monitoring. The consequence was severe: beyond the financial penalty, Matchbook was forced to suspend operations in the UK for a time while it overhauled its processes. This case underscores that regulators will not hesitate to halt a business entirely if they think the AML control failures are serious enough. It was a wake-up call that even one or two very large unverified transactions can bring an entire platform under scrutiny. The aftermath saw Matchbook implementing what the UKGC called an “extensive remediation plan,” including appointing new leadership, integrating new KYC and transaction monitoring systems, and tightening thresholds for review so that such a huge bet would set off immediate alarms in the future.

• Cross-Border High-Risk Gambler – Olympic Casino (Lithuania): To illustrate that these issues are global, not just UK-centric, consider a case from Lithuania in 2025: Olympic Casino Group (a large Eastern European gaming operator) was fined a record €8.4 million by Lithuanian authorities. The case involved a high-rolling patron who was later accused of embezzling tens of millions in public funds, gambling large sums at the casino. The regulator found that the casino had turned a blind eye to obvious red flags, performing only perfunctory source of funds checks despite the patron’s transactions being enormous. According to the investigation, the casino’s monitoring of this VIP’s play was essentially just ticking boxes and not genuinely questioning how a person could afford to gamble at such scale. The patron was a public official involved in a corruption scheme, exactly the type of individual one would hope stringent SoF/SoW checks would catch. The enforcement included scathing remarks that the measures to check the origin of funds were inadequate. This case is particularly interesting because it shows how an issue in one realm (government corruption) directly intersected with gambling due diligence: if Olympic Casino had diligently sought proof of the patron’s wealth and legitimate income, the disparity might have come to light earlier or suspicious transactions could have been reported. The fallout in this case led to the operator enhancing its internal controls and likely applying much stricter vetting for any politically connected clients. It also signaled to the international community that even smaller markets are ramping up enforcement and that no major operator anywhere can afford to be complacent about SoF/SoW.

• Process Innovation After Failures: Not all outcomes are punitive; some cases lead to industry innovation in compliance processes. For instance, after a series of UK fines around 2018–2020, several online bookmakers and casinos collaboratively explored new technologies for affordability and source of funds verification. One concrete development was the growing use of open banking in the UK – a technology that allows customers to securely share their banking data with third parties. Gambling operators began piloting open banking-based affordability checks, wherein a customer who hit a certain spending threshold could consent to the operator reviewing a read-only snapshot of their bank transactions. This would quickly show an operator the customer’s income and outgoings, giving a far clearer picture of affordability than static documents. Early adopters of this approach found that it streamlined the process – rather than asking a customer for three months of bank statements via email (which could be slow and incomplete), open banking could provide a verified, real-time transaction feed to assess disposable income. Another innovation has been the creation of centralized “single customer view” systems (championed in the UK) that aim to allow different gambling companies to share data on high-risk customers while respecting privacy. The idea arose after cases where a problem gambler or money launderer, when cut off by one company, would simply move to another; regulators and industry groups have pushed for a solution where, if one operator has flagged a customer for potential illicit funds or unaffordable gambling, other operators could be alerted. This is still developing, but it represents a forward-thinking response to the limitations revealed by past incidents. In terms of internal process, a number of operators also invested in dedicated Financial Crime teams specifically for VIP and high-risk accounts after seeing the fallout of not paying close attention. For example, companies set up special units that review every new VIP nomination to ensure SoW checks are done before the person gets perks like higher deposit limits. These teams often use third-party intelligence tools to supplement what the customer provides – such as databases that estimate a person’s net worth or alert to any negative news about them. All these changes show the industry’s learning curve: high-profile failures and fines have led to more sophisticated, tech-enabled, and collaborative approaches to verifying source of funds and wealth.

Each of these case studies carries lessons. Patterns emerge: operators got into trouble when they either ignored obvious signs (e.g., someone of modest means gambling big money) or relied solely on customer assertions without independent verification. The enforcement outcomes also consistently highlight that “know your customer” in gambling must go beyond just knowing their name and age – it means knowing how they are funding their play and being alert to any mismatch between a customer’s financial profile and their gambling behavior. They also show that regulators worldwide are increasingly intolerant of lax practices; whether it’s the UK, another European country, or elsewhere, authorities are willing to levy steep fines and even suspend businesses to drive the message home.

For compliance and risk professionals, these stories underscore the importance of robust SoF and SoW checks. They also provide practical insight: for example, if a customer claims their money comes from another gambling win (as in the White Hat case), a best practice would be to verify that win; if a VIP is spending millions, ensure multiple layers of approval and documentation are in place, and if a customer’s profile doesn’t add up, do not hesitate to dig deeper or even refuse service. In the next section, we will discuss the tools and techniques that can help achieve these goals, many of which have been sharpened or newly developed in response to the challenges highlighted by cases like these.

Tools and Techniques: Using Third-Party Solutions, OSINT, and EDD to Verify SoF/SoW

Overcoming the challenges of source of funds and wealth verification in iGaming requires leveraging a combination of third-party tools, open-source intelligence (OSINT), enhanced due diligence practices, and direct customer interaction. A multi-faceted approach can greatly enhance an operator’s ability to detect and verify the true origins of customer funds. Here are key tools and techniques and how they play a role:

• Advanced Verification and Data Analytics Tools: The RegTech market offers various tools that can aid compliance teams in verifying SoF and SoW more efficiently. For example, identity verification platforms often include modules for document verification – an operator can ask a customer to upload bank statements or payslips through a secure portal, and the software will analyze these documents for authenticity (checking for signs of tampering, confirming logos and fonts match official templates, etc.). Some providers maintain databases of known fraudulent document templates to compare against. Additionally, there are income and employment verification services in certain countries that operators can use (with customer consent). For instance, in some jurisdictions, APIs can connect to credit bureaus or tax records to retrieve verified income information. Similarly, gaming companies now utilize transaction monitoring systems configured for gambling patterns – these systems automatically scan all customer deposits, bets, withdrawals, etc., to flag unusual activity (like rapid cycling of funds, multiple accounts using the same payment method, or depositing just below certain thresholds repeatedly). When a flag triggers, it can automatically prompt a SoF check workflow. One notable technological aid is the aforementioned open banking integration: by using open banking, operators can get a real-time look at a customer’s finances (with permission) – seeing recent salary credits, average balance, other gambling transactions, etc. – which is immensely useful to gauge whether current gambling spend is affordable and what the direct source of the funds is (for example, seeing a large transfer from another account or a cash deposit in the bank statement that might need explanation). Open banking basically turns what could be weeks of back-and-forth paperwork into a swift digital check. It can not only verify income but also catch if the customer is funding gambling via debt (e.g., if their bank account shows frequent credit card cash advances – a sign of problem gambling or potential fraud). Automation and machine learning are also being introduced: some operators employ machine learning models to predict a customer’s likely income band from various inputs (address, occupation, spending habits) and then compare it to their gambling spend – if gambling spend far exceeds the predicted income, the system flags for manual review. While these tools are powerful, they are not foolproof alone; they augment human decision-making by sifting through data at scale and highlighting where attention is needed.

• Open-Source Intelligence (OSINT): OSINT refers to gathering information from publicly available sources, and it is a cornerstone of modern EDD in financial crime compliance. For verifying source of wealth, OSINT can be invaluable. Compliance analysts will often perform web searches on a customer’s name combined with keywords (like “fraud,” “investigation,” “award,” “net worth,” etc.) to see if anything noteworthy appears. News articles might reveal that a player is involved in a court case, or conversely, that they were featured in a magazine for selling their startup company – either can drastically change the risk understanding. Social media and professional networking sites may provide clues: a customer’s LinkedIn profile could confirm their employment (and level of seniority, which correlates to income), while their lifestyle visible on social media might either support or call into question their claims about wealth. For example, if someone claims to be a wealthy investor but OSINT finds they have multiple bankruptcies or no online footprint at all, that’s a flag. Corporate registries and land registries are another rich OSINT source: many countries have online databases where one can see if the person is a director or shareholder of companies, or owns real estate. If a customer says they own a business, checking the corporate registry can confirm if that business exists, how long it’s been around, and sometimes even its financial filings. Owning significant real estate or multiple companies might justify wealth; not owning any assets might contradict a claim of high wealth. In the case of PEPs or high-risk individuals, OSINT is used to uncover any adverse media – for instance, a simple search could show if the person has been implicated in corruption or is related to someone who is. There are also specialized databases (often subscription-based, which blurs the line between OSINT and third-party tools) that compile such media and profile information on high-risk persons. Compliance teams in gambling firms increasingly have staff trained in OSINT techniques, essentially acting like investigators piecing together a customer’s wealth puzzle from the internet and databases. A well-executed OSINT investigation can sometimes discover exactly what you need – say an interview in a local newspaper where the customer discussed his successful business, explaining his wealth; or on the negative side, a press release from law enforcement about a fraud ring that lists your customer as an associate. These pieces of intelligence greatly inform whether to trust a customer or to probe further.

• Enhanced Due Diligence (EDD) Procedures: Enhanced due diligence means going deeper than standard checks, and many of the points above (tools and OSINT) feed into an EDD process. But EDD also involves direct actions by the compliance team to validate and document SoF/SoW. This can include requesting specific documentation: for example, asking a customer for a copy of the contract of sale if they claim they sold a property to get the money, or asking for a letter from their lawyer or accountant attesting to an inheritance if that’s the source of wealth. EDD often means verifying one piece of evidence against another – if a customer provides a payslip, the team might also ask for a tax document or a bank statement showing the salary deposit to ensure consistency. In high-risk situations, some operators even hire independent investigators or due diligence firms to conduct background checks on a customer. This might be done for very high net worth VIPs or suspicious cases: the firm might verify education credentials, look into litigation records, check the dark web for any mention of the person, or even discreetly gather intelligence from local sources. Another aspect of EDD is internal collaboration: modern gambling compliance overlaps with responsible gambling, fraud prevention, and security departments. If a player is high-risk for AML, they might also exhibit problem gambling behaviors or fraud patterns. Having a cross-functional approach – say, a committee that reviews any high-risk client with members from AML, responsible gambling, and finance – can ensure a 360-degree view (for instance, responsible gambling staff might know the customer mentioned stress over finances in a chat, which is useful for AML to know too). Documentation and record-keeping is a key part of EDD: everything learned and decided about a customer should be logged in a case file, so if regulators ask, the operator can show a clear narrative of what was checked and why the decisions (to retain or terminate the client, to allow further play or not) were made. In summary, EDD is the practice of leaving no stone unturned for risky customers – it’s labor-intensive, but it’s how you catch the details that basic checks would miss.

• Direct Customer Interaction and Interviews: Sometimes, the simplest way to get information is to ask the customer. While many customers balk at intrusive questioning, a skillfully handled customer interview or questionnaire can yield crucial details. For significant customers, especially VIPs or those under review, compliance officers might arrange a polite conversation – this could be a phone call or face-to-face meeting (in the case of very high-end clients, even a meeting at the casino or a video call) – to discuss the need for information. The tone is important: operators usually frame it as wanting to “update their records” or comply with regulations, and that these questions are standard for high-level accounts. In these interactions, the officer may ask open-ended questions like “Could you tell us a bit about how you were able to fund the account at that level? For instance, what are the main sources of your income or wealth that make this play comfortable for you?” Customers might reveal more in conversation than on forms – perhaps mentioning a recent company sale, or that they’re a beneficiary of a family trust. These conversations can also gauge the customer’s reaction: if someone becomes unusually defensive or evasive about their finances, that itself is a red flag. Some might refuse outright to provide information – and if it’s a requirement, the operator then has justification (and indeed an obligation) to cut off the relationship if minimum due diligence can’t be completed. Another form of customer interaction is sending structured questionnaires (source of wealth forms) where customers fill in details about employment, salary range, other income, net worth, etc. While people could lie on forms, having them sign a declaration adds a layer of accountability, and inconsistencies between their declaration and what evidence later shows can be telling. Additionally, by engaging with the customer, operators sometimes discover helpful context – e.g., the customer might volunteer that they have multiple properties earning rental income, which then the compliance team can verify. A collaborative but firm approach often works best: make it clear that this process is required for continued service and is meant to protect both the business and the player from fraud or illegal activity, and many customers (especially legitimate ones) will understand and cooperate. It’s often the malicious actors who will either disappear or give nonsensical answers when pressed, effectively exposing themselves.

• Third-Party Databases and Intelligence Services: Aside from OSINT and customer-provided info, operators frequently rely on subscription-based databases (offered by companies like Refinitiv World-Check, Dow Jones, ComplyAdvantage, etc.) which compile profiles on high-risk individuals and entities. These databases can be queried to see if a customer is listed as a PEP, if they have adverse media, or if they appear on any watchlists or sanctions lists. For example, if a new high-stakes registrant shares a name with someone in a database who was convicted of financial crime, that’s a prompt to investigate if it’s the same person. There are also wealth-estimation services that aggregate data like property ownership, company ownership, and so forth to give an approximate net worth or wealth score for individuals in certain countries – while not definitive, these can be used as a check (does the external estimate roughly align with what the customer claims?). Another modern tool is device and behavioral analytics: if someone is using the site in a pattern suggestive of mule accounts or multiple identities (say the same device is used by accounts under different names), it might indicate a professional money launderer rather than a genuine individual – at which point SoF/Sow verification might be futile and the better response is closing accounts and filing a suspicious report.

By combining these tools and techniques, an iGaming operator can build a much more complete picture of a customer’s financial background and the legitimacy of their play. For instance, imagine a scenario: A new customer deposits $20,000, triggering a review. The operator’s automated systems flag the deposit as unusually high for a new account and also note the customer’s address is in a country known for high corruption. A compliance analyst uses a third-party database and finds the customer is a director of two companies. They perform an OSINT search and discover a news article about one company being awarded a large government contract (which could explain wealth, or could raise questions about political connections). They request source of funds documentation; the customer, after some hesitation, shares a bank statement showing the $20k came from the recent sale of a luxury car. The analyst verifies the car ownership via a public vehicle registry (OSINT) and perhaps even finds social media posts of the customer with that car – things line up. They document all this, and because the customer is from a high-risk country, they also set a rule for ongoing monitoring that if the customer deposits beyond, say, $50k or shows any unusual transactions, it will be escalated for another review. In this way, using multiple sources of information and verification gives confidence in the assessment.

It’s worth emphasizing that technology and tools don’t replace human judgment but rather enhance it. A comprehensive SoF/SoW verification process in iGaming is like assembling a puzzle: pieces come from the customer, from databases, from OSINT, from transaction patterns, and sometimes from law enforcement alerts. The compliance team’s role is to put these pieces together to see the full picture – is it a picture of legitimate wealth being spent recreationally, or does something not fit (indicating possible money laundering or unaffordable gambling)? By deploying the right tools and approaches, operators can more reliably answer that question.

Integrating SoF and SoW Checks into Onboarding, Monitoring, and Affordability Processes

To manage these requirements effectively, iGaming operators should integrate source of funds and source of wealth checks seamlessly into every stage of the customer lifecycle – from the moment of onboarding, through continuous account monitoring, to periodic affordability assessments. Below are practical recommendations for embedding SoF and SoW verification into key processes:

• Robust Onboarding KYC with Early SoF Indicators: The foundation is laid at customer registration. During onboarding, beyond just collecting identity documents, operators should gather some basic financial profile information to inform risk rating. This could include asking new customers about their occupation and perhaps an approximate income range or source of wealth in a polite, optional way (some operators include a field like “Occupation/Industry” in the sign-up form, or even a short questionnaire for high deposit limits requests). While not every customer will provide extensive info upfront, having any initial data helps contextualize later activity. Importantly, risk-based customer segmentation should start at onboarding – for example, if a new customer is identified as a PEP through screening, or is from a high-risk country, they should automatically be classified as higher risk and tagged for EDD from the get-go. Similarly, if during signup a customer opts for very high deposit limits or indicates being a professional gambler, that might warrant early SoF checks (some sites, for instance, won’t allow a very high first deposit without at least asking some questions or doing an initial check). Onboarding is also the stage to obtain necessary consents for future checks – for example, including in the terms that the company may request source of funds documentation or use credit reference agencies to verify information. This way customers are on notice that such checks are part of the business relationship. Some leading operators perform a kind of “soft” affordability check at account creation using open data – for instance, deriving an estimate of average income by postal code or other demographic factors, which can be used as a loose benchmark until real data comes in. The key is that the onboarding KYC process should not be treated as a one-off formality; it’s the first step in a continuous due diligence journey. A well-designed onboarding will flag potentially higher-risk customers for closer attention right away, ensuring that big issues are caught early rather than after significant suspicious gambling has already occurred.

• Automated Monitoring and Trigger-Based Reviews: Once the customer is active, the operator’s monitoring systems should be continuously scanning for thresholds or patterns that trigger SoF/SoW checks. This means defining clear rules such as: “If cumulative deposits exceed £X within Y days, then initiate a source of funds review,” or “If a player’s net loss reaches Z, trigger an affordability check.” Many operators set multiple tiers of triggers. For example, a first-tier review might be a relatively low threshold that prompts a basic check – perhaps a simple email to the customer asking if they can confirm their source of funds or provide a payslip, or an internal analyst doing an open-source search based on info already on file. If that first-tier check doesn’t raise concerns, the player can continue until the next threshold. A second-tier trigger at a higher amount might require more formal documentation and analysis (like bank statements, proof of wealth, etc.). And a critical threshold might be defined where the account is paused pending full verification because the activity is now very high risk. Real-time monitoring is essential; for instance, if someone suddenly deposits a very large amount in the middle of the night far above their usual pattern, an automated alert can notify a compliance officer to review immediately (possibly even halting withdrawal of any winnings until the review is done). Another important aspect is ongoing PEP and sanctions screening – databases should be periodically refreshed because someone not a PEP today could become one if they take political office, or a person could newly appear on a sanctions list. If that happens, a SoW check should be launched immediately because the risk profile has changed. Integrating these triggers into the gaming platform ensures that checks are not left to memory or manual ad-hoc decisions; they happen as a matter of workflow. Some operators integrate compliance checkpoints into the customer relationship management (CRM) system: for example, the system might prevent a VIP team from increasing a player’s betting limits until the compliance team has given approval post-SoF check. By coding such business rules into the software, it enforces that no one bypasses the process due to oversight or undue commercial pressure.

• Affordability and Source of Wealth Assessments as Routine Checks: In jurisdictions like the UK, affordability assessments are becoming a norm – essentially evaluating if a customer’s gambling spend is proportionate to their income/wealth to prevent gambling harm. Even outside responsible gambling regulations, these assessments double as financial due diligence. Operators should incorporate periodic affordability checks for players who sustain high levels of spending. For example, if over a 3-month period a player consistently loses large sums, an affordability review might be scheduled. This could involve reaching out to the customer with a standardized request: “As part of our routine checks, please provide recent proof of income or funds (such as a payslip, income tax statement, or bank statement) to ensure your level of play is sustainable.” Internally, the team would compare the provided info against the customer’s net deposits or losses. If a customer provides evidence of an annual income of $100,000, and they have gambled $80,000 in the past year, that’s a potential problem – either from a responsible gambling perspective or indicating possible undisclosed funds. On the other hand, if they provide evidence of millions in assets, that gambling spend might be acceptable. It’s important that these affordability/Sow reviews aren’t just one-time at a threshold, but ongoing at intervals for active high spenders. Many companies adopt a schedule (say, annual review for all VIPs, or more frequent if they hit new higher tiers of spending). Integrating such reviews into the player’s lifecycle ensures that even if someone initially passed a SoW check, the operator will catch if their situation changes or if initially provided information becomes stale. Affordability checks, when done proactively, can also help preempt regulatory issues – it shows the operator is actively making sure customers aren’t gambling beyond their means or with illicit funds. Documentation from these reviews can be used to justify to regulators that, for instance, “Customer X has lost Y amount, but we have on file evidence that they earn 5Y per year legally, thus we judged it acceptable.”

• Collaboration Between Compliance and Customer-Facing Teams: Integration of these checks works best when the compliance function and the teams that interact with customers (like VIP managers, customer support, etc.) work hand-in-hand. Customer-facing staff should be trained to understand why SoF/SoW checks are needed and how to communicate with customers about them. For example, a VIP manager can play a vital role by giving a heads-up to a VIP that the compliance team will be reaching out for some information and framing it positively. Also, such staff often gather soft information in the course of their relationship – e.g., a VIP might casually mention they just got a bonus at work or sold a property; the VIP manager can pass that along to compliance to assist in verification. Having clear internal protocols – say, whenever compliance requests documents, the customer support team must pause any withdrawal requests and note the account – is key so that the process is consistent and doesn’t lead to mixed messages to the customer. Integration also means that responsible gambling interventions and AML interventions are coordinated. If a customer is asked for SoF due to high spending, it may also be an appropriate time to perform a responsible gambling check (ensuring they’re not showing signs of addiction, offering support resources if needed, etc.). Combining these interactions can reduce friction (rather than contacting the customer separately for financial info and then for responsible gambling, a holistic review can cover both aspects at once). The outcome of any check – whether the customer complied, whether the information was satisfactory – should be logged and, if concerning, shared with relevant departments (for example, if SoF check fails and account is closed, the fraud team should be alerted to see if any chargebacks or suspicious payment patterns exist, and a SAR should be filed by the MLRO).

• Policy, Training, and Culture: From a governance perspective, integration requires having clear written policies and procedures around SoF and SoW checks. These policies should define triggers, responsible personnel, documentation standards, and escalation paths (e.g., at what point do we involve the Money Laundering Reporting Officer or report to regulators?). Staff training should include scenario-based learning – showing employees examples of good vs. bad SoF documents, red flags in customer behavior, and how to handle sensitive discussions. Fostering a compliance culture is crucial: everyone from the support rep to the CEO should understand that verifying customer funds is non-negotiable and is done to protect the business and the players. When leadership emphasizes that long-term business sustainability comes from being compliant and ethical, not just from chasing short-term revenue, staff are more likely to take these processes seriously rather than view them as a hindrance.

• Feedback Loop and Continuous Improvement: Once SoF/SoW checks are part of the operational workflow, it’s important to periodically assess their effectiveness. Operators should track metrics like: How many checks are we doing? What percentage of customers comply? How many accounts do we shut or restrict due to unsatisfactory answers? Are there cases where problematic customers slipped through without checks, and why? By reviewing these, the compliance program can be adjusted. Perhaps thresholds need lowering or additional triggers need adding. Regulators often update guidance or raise expectations (like the UK did with affordability); a nimble program will incorporate those changes quickly. It’s wise for operators to also stay plugged into industry forums or working groups on these topics – sometimes regulators informally share where they see industry weaknesses (for example, “we’ve noticed many operators not sufficiently verifying sources of crypto funds”) which operators can proactively address. In effect, integrating SoF and SoW checks is not a one-time project but an evolving part of operations that should refine itself as new risks emerge (such as new payment methods) or as new best practices become available (such as improved technological solutions).

By weaving source of funds and wealth verification into onboarding, ongoing monitoring, and affordability processes, an iGaming operator creates multiple checkpoints to catch and manage risk. This layered defense means even if a risky individual somehow clears one hurdle, they will likely be caught by another down the line. It also sends a strong message to both regulators and criminals: this platform is actively watching and will question unusual money. In the best case, serious illicit actors will be deterred from targeting a well-protected operator at all, and those that do try will be identified and dealt with promptly. Meanwhile, legitimate players who can demonstrate their funds will experience perhaps minor friction but ultimately can continue playing in a safer, more transparent environment.

Conclusion

In the international online gambling sector, verifying the source of customers’ funds and wealth is no longer just a bureaucratic checkbox – it is a fundamental part of running a safe, compliant, and reputable operation. Source of Funds (SoF) and Source of Wealth (SoW) checks serve as critical tools to prevent money laundering, terrorist financing, and the infiltration of criminal money into gaming platforms, as well as to ensure gamblers are not spending beyond their means to the point of personal harm. This article has outlined how SoF focuses on the origins of specific transactions, while SoW looks at the bigger picture of a person’s financial background. Both angles are necessary to truly “know your customer” in a meaningful way.

We explored the multifaceted challenges that iGaming firms face – from handling vast amounts of data across different countries, to dealing with privacy and legal constraints, to upgrading technology and processes to keep pace with cunning criminals. The global regulatory review highlighted that while the exact rules may differ in London, Malta, Las Vegas, or Sydney, the direction is converging: regulators everywhere expect gambling operators to be as diligent as banks in checking where money comes from, especially for high-risk clients. Inconsistencies in standards require operators to be nimble and often abide by the toughest standard applicable to them to avoid any weak links.

A risk-based approach is essential, tuning the depth of verification to the profile of the customer – whether it’s a wealthy VIP, a politically exposed person, or someone from a high-risk region. The stakes are high with these profiles, as shown by the real-world case studies. Those examples – from the UK VIP who wagered stolen money, to the international casino that missed a corrupt official’s embezzled funds – underline the serious consequences of getting it wrong. They also offer real lessons, prompting industry-wide improvements like stronger VIP due diligence rules and the advent of open banking affordability solutions.

We have discussed how iGaming compliance teams now have an array of tools at their disposal: sophisticated ID verification systems, data analytics, OSINT techniques, third-party intelligence databases, and more – all to piece together the puzzle of a customer’s source of funds. But tools alone are not enough; success lies in integrating these checks into the daily workflow of the business. That means asking the right questions at signup, monitoring transactions continually and intelligently, engaging players for information when needed, and working across departments to ensure potential issues are caught early and handled correctly.

For compliance and financial crime professionals in the online gambling sector, the mandate is clear. It is possible to meet the verification challenges by adopting a proactive, structured, and customer-sensitive approach. This involves building robust internal systems and teams that can perform timely SoF and SoW checks without unduly disrupting the player experience for legitimate customers. It also means fostering a culture where compliance is everyone’s responsibility – from front-line support staff who might notice odd behavior, to executives who allocate budget for better tools and approve stepping away from high-risk revenue when necessary.

The practical recommendations laid out – such as tiered triggers for reviews, leveraging open banking, thorough documentation, and ensuring senior oversight of high-risk accounts – are all pieces of a strong compliance program. When effectively implemented, they not only keep regulators satisfied but actually benefit the business by preventing costly scandals, fines, or even the loss of operating licenses. They also protect the industry’s credibility by reducing the chance that gambling platforms become havens for dirty money or stories of ruined lives due to unchecked gambling losses.