### Introduction

In recent decades, sanctions have become a standard instrument in international politics and a headache for compliance teams. Sanctions take different forms, from restrictions to additional rules on specific services and trade deals (such as price caps), and can be applied to individuals, entities, or jurisdictions.

Sanctions compliance is easily the most risky regulatory environment. Sanction evaders create complex schemes to access financial instruments and employ new technologies to launder and transfer money. 

Compliance officers should understand how such actors operate to abide by national and international sanctions without over-compliance, establish an effective Regtech stack to analyze transaction patterns and cooperate with national financial intelligence units to secure themselves from potential noncompliance fines.

Here, we review several cases elaborating on old-school and novel sanctions evasion approaches and provide advice on how to react to them.

### Case one: Tracking Cryptocurrencies 

The generous promise of anonymity and privacy made cryptocurrencies widespread among illegal actors. Still, it took stablecoins (pegged to traditional currencies) to make them genuinely convenient for money laundering, illegal trade, and sanctions evasion.

Just like bank accounts, cryptocurrency wallets can store significant wealth. A non-custodial wallet not operated by a platform like Binance or Coindesk requires no KYC checks to create and manage and can’t usually be traced back to its beneficial owner. A single person can control a virtually unlimited number of wallets, which means assets belonging to a single person can be distributed across numerous accounts, making them hard to trace.

However, blockchain is transparent by design, meaning that a high-net-worth sanction evader won’t be able to quietly transfer all his wealth through crypto. The lack of liquidity in the cryptocurrency market means that crypto isn’t reliable as a replacement for traditional financial instruments on a large scale. However, crypto is suitable for smaller-scale transactions, such as payments for smuggled goods between private entities working on procurement for sanctioned organizations. There are many crypto exchanges with lax or lacking AML controls that are specifically suited for such clientele.

### Case Two: Informal Connections

One crucial challenge in sanctions compliance is identifying ties between designated entities and proxies that facilitate sanctions evasion. One year ago, we emphasized this problem in the context of PEP screening in jurisdictions with widespread government corruption. Sanctioned individuals may conceal ownership of assets and actual beneficiaries of transfers behind distant relatives, close associates, and other trusted individuals, such as lawyers or consultants.

### Case Three: Revealing Schemes

Large-scale sanctions evasion, such as international trade with a sanctioned country or corporation, often requires complex schemes, including numerous legal entities in different jurisdictions (including off-shore and mid-shore financial centers), multiple international bank transactions to conceal the beneficiaries, and shady practices related to movement of the goods. 

Compliance-wise, such activities pose a significant risk to financial intermediaries. 
On the one hand, they can’t see the whole picture and may be convinced that the transactions between parties are legit. Even though sometimes the people behind sanction evasion schemes are well-known wealthy individuals with a lobbying potential, often the global sanction evasion and money laundering networks are orchestrated in secrecy and managed by seemingly quiet people living simple lives, which can’t usually be connected to high-risk activities.

On the other hand, once an illegal scheme is revealed, the regulators may consider that a financial intermediary (such as a bank) failed to take sufficient measures to prevent money laundering and sanction evasion, resulting in noncompliance fines. The well-known cases include Standards Chartered, Deutsche Bank, HSBC, Danske Bank, Societe Generale, Commerzbank, Credit Suisse, and BNP Paribas, with cumulative fines totaling 20 billion dollars in the last two decades.

### Conclusions

In 2024, compliance teams should go far beyond standard anti-money laundering frameworks to ensure full enforcement of international sanctions. There are several key recommendations:

* Fintech companies that enable the convenient use of traditional money and cryptocurrencies for everyday payments should employ on-chain analysis and risk assessment for crypto assets to prevent illicit transactions and ensure compliance. Such an approach is essential to avoid over-compliance and enable legitimate money transfers over the blockchain.
* Advanced Regtech solutions automate complex compliance tasks, such as adverse media searches, which allow the identification of informal ties between designated individuals and legal entities and facilitators of sanctions evasion. 
* Financial intermediaries lack instruments to identify complex sanctions evasion schemes, so related noncompliance risks can’t be mitigated. That’s why it’s crucial to cooperate with the national financial intelligence units and independent financial crimes investigators (such as [OCCRP](https://www.occrp.org/en)) and be proactive in reporting potential sanction evasion cases.

Dataspike platform leverages compliance teams’ ability to identify high-risk individuals and entities and prevent sanctions evasion, money laundering, and other illicit activities. It aggregates information from various sources, assesses risks, and helps compliance officers make informed, evidence-based decisions.


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Lessons on sanctions evasion

### Introduction

In summary, money laundering is the obfuscation of sources of funds obtained through illicit means. According to the Oxford English Dictionary, the first well-documented use of this term dates back to the 1970s and was widely adopted in the 1980s. However, money laundering has likely existed since the emergence of money and laws that prohibited certain activities.

Money laundering follows the predicate offense from which the funds are acquired. This legal concept also originates from the late 20th century; however, it’s essential for understanding the history of money laundering. While crimes such as piracy or robbery have been common throughout human history, there are more opportunities to explore the history of money laundering following white-collar offenses, such as bribery, financial fraud, or tax evasion.

This publication will review how money laundering has changed over time. This article will use modern concepts and terms to discuss events that took place years and centuries ago. 

### Three stages of money laundering

Money laundering consists of three steps: placement, layering, and integration. Placement is where questionable funds are reintroduced to the financial system. For that purpose, money can be deposited into accounts at financial intermediaries. To circumvent the reporting threshold, criminals split money and employ so-called “money mules” to open accounts and make transfers. Sometimes, money is sent abroad via remittance services or physically smuggled to jurisdictions with lax financial controls.

At the Layering stage, the funds are transferred through shell companies, often established in different jurisdictions, to hide the origin of the deposited cash. A professional facilitator usually orchestrates the process. Money launderers use fictitious contracts for trade or lending to provide plausible supporting documentation. Investigations based on massive leaks of documents related to offshore companies, such as Panama Papers or Pandora Papers, can illustrate the complexity of such schemes.

Finally, money Integration is performed through ostensibly legal economic transactions, such as acquiring various assets, purchasing goods, investments, etc. At this point, the criminals re-acquire control over the funds.

### Money laundering cases over the history

#### China

In the publication “Lords of the Rim,” American historian Sterling Seagrave provided details on tax evasion and money laundering practices employed by Imperial China-era merchants. One notable example is Fei-Chien, or Flying Money, an informal value transfer system based on exchange notes. This system enabled traders to avoid taxation when transferring funds abroad and leave a minimal money trail record. It also enabled trade in goods forbidden in particular parts of the ancient world, as sales and acquisitions usually remained invisible to authorities. 

Fei-Chien was highly formalized and regulated because it was the backbone of Chinese expatriate economics. In modern terms, it’s one of the early documented examples of placement and layering in the context of money laundering. The system is still widely used in South Asia and remains part of money laundering schemes for Chinese crime syndicates.

#### Ancient Greece

The polises of Ancient Greece introduced two components of the modern financial system: an agora, which served as a centralized location for financial activities overseen by the authorities, and a strong institute of reputation in economic relations (which remotely resembles modern KYC). Lenders operating across Greek cities separated by the Aegean Sea established networks for sharing information about maritime merchants to exclude fraudulent and dishonest ones from future transactions.

The tax system of ancient Greece, specifically classic Athens that ditched indirect taxes) provided many opportunities for tax evasion. Direct taxes were mainly applied to wealthy individuals. For instance, liturgies obliged rich citizens to fund specific public activities or maintenance of state property, such as triremes, during the war. 

Wealthy Athenians often concealed their wealth by assigning their assets to nominal owners or putting money in the bank. There was little or no bank regulation, and private financial intermediaries could ensure the complete confidentiality of their clients and even provide the latter with secret returns with no tax obligations. The same could be done with other illegal proceeds (such as bribes), making banks a one-step, one-stop laundromat for Greek citizens.

#### Modern times Switzerland

As money laundering requires secrecy, criminals benefit from corporate and bank secrecy practices. For centuries, Switzerland established its reputation for extreme financial secrecy and became a European hub for high-profile money launderers. Even in the 2020s, it was blamed for a passive stance towards money laundering, sanction evasion, and other illegal practices.

Swiss bank secrecy regulations date back to the 1713 Council of Geneva decision that forbade bankers from disclosing information about their clients to safeguard the interests of the Catholic French monarchy, which wanted to obscure its dealings with banks in a Protestant Switzerland during the European wars of religion. Financial secrecy became a tradition and was later supported by legislation, making obtaining information about accounts and their owners borderline impossible for authorities.

In the early 20th century, Swiss banks promoted the country as a tax haven and a safe place to store assets, which resulted in an unprecedented influx of money during the turbulent times of the Word War and the following succession of political, financial, and monetary crises in Europe and ashore. 

Money launderers, such as the renowned “Banker for the American Mafia” Meyer Lenski, took advantage of the protection provided by the Swiss banking system. He purchased an actual Swiss bank and built a network of shell companies and offshore accounts to launder proceedings from illegal activities in the United States. He employed nearly anonymous numbered bank accounts that provided an additional layer of privacy to deposit questionable money that passed through his international laundromat and used them to secure legal loans in the bank. Despite all the efforts of the U.S. authorities, he was never convicted. Lenski died in 1983, aged 81, free.

#### The Prohibition in the USA

In the early 20th century, money laundering wasn’t even considered a separate activity but a component of other crimes. No legislation obliged banks to identify their clients or question the source of funds thoughtfully. However, tax evasion was already a thing, and criminals needed a way to convert illegal proceedings into legal profits.

There’s a widespread belief that the term “money laundering” originates from the activities of a renowned Prohibition-era gangster, Al Capone, who allegedly used laundrettes with cash-only laundromats as cover firms to launder revenues from prostitution or bootlegged liquor sales, and other illegal businesses. The amount of cash flowing into laundromat operations was hard for law enforcement authorities to monitor, generating vast amounts of seemingly legitimate funds.

#### Watergate Scandal

The first well-documented use of the term “money laundering” in the general media was in the Guardian’s 1972 coverage of the Watergate scandal. It was the first time the U.S. authorities emphasized the need to interpret money laundering as a separate offense. 

The Watergate scandal is commonly associated with a break-in at the Democratic National Committee headquarters in the Watergate Office Building in Washington, D.C. Still, the most essential part was a scheme that concealed funding sources for Richard Nixon’s 1972 election campaign. After being elected President of the United States in 1968, Nixon established a “Committee to Re-elect the President” to aggregate donations for his next campaign. However, the contributions didn’t go directly to the fund; they were rerouted to Mexico and then back to a Miami-based front company, allowing the concealment of the origin of money and donors’ identities.

The Department of Justice of the United States linked the cash found on the Watergate burglars to the “Committee to Re-elect the President” funding, and the connections were later confirmed during the burglars’ trials. The finding convinced the House of Representatives to grant its judiciary committee more authority to investigate money laundering matters. Despite winning the 1972 elections, Nixon resigned in 1974 due to the threat of impeachment for this and other misdemeanors.

#### War on Drugs

During the global war on drugs in the 1980s, law enforcement authorities required more instruments to chase money and freeze and seize assets belonging to organized crime. The United States pioneered the development of anti-money laundering legislation, which finally led to the formalization and globalization of control over money laundering.

During Ronald Reagan’s presidency, the U.S. authorities escalated their control over illegal drugs. The 1985 Money Laundering Control Act declared money laundering a separate federal crime for the first time. It enabled law enforcement and intelligence services to impose restrictive measures on proceedings from the drug trade. This strategy proved effective and was soon followed by similar laws in other countries.

In 1988, the United Nations implemented the Vienna Convention Against Illicit Traffic in Narcotic Drugs and Psychotropic Substances, which declared money laundering illegal, specifically in regard to the drug trade. In 1989, the G7 established the Financial Action Task Force (FATF) to analyze money laundering trends and develop standards and best practices to prevent it nationally and globally.

#### War on Terror

The 9/11 terrorist attack on the World Trade Center in New York had a profound effect on the development of anti-money laundering regulations in the U.S. and the world. For instance, the Patriot Act of 2001 directed financial institutions to expand anti-money laundering programs and improve due diligence reporting on foreign bank transactions. It also introduced new communication standards between law enforcement authorities and financial intermediaries. The stricter anti-money laundering regime implemented by the U.S. to fight the threat of international terrorism soon became the benchmark for the rest of the world.

### Conclusions

We made a short glimpse into the evolution of money laundering and financial regulation from the ancient times to the beginning of the 21st century. Get ready for our next historical review on the modern ways of money laundering and contemporary AML tactics.



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The brief history of money laundering (from ancient times to the early 21th century)

### Trust, but Verify: GenAI in AML Compliance
Generative artificial intelligence (GenAI) is the most significant tech hype nowadays. Large language models became standard productivity tools, and new startups promise to revolutionize industries with GenAI. However, most existing GenAI-based products help in simple everyday tasks rather than redefining how people work. Can GenAI become a life-changer instead of a time-saver in a complex workflow, such as anti-money laundering (AML) compliance? Let us explore further. 

### Old-School Machine Learning vs. GenAI

Machine learning, the application of artificial intelligence (AI) that allows machines to learn and improve, gained traction in the 1990s and became mainstream in the 2010s. Machine learning instruments work under the hood of popular websites, operating systems, business applications, etc. These applications are valuable due to their ability to make accountable predictions (predictive analytics).

GenAI is a particular implementation of machine learning that aims to generate new content (text, images, video and so on) based on its training dataset. The GenAI boom of the recent decade was manifested by the launch of numerous consumer AI applications, as opposed to industrial, such as chatbots or image generators, which facilitated the adoption of AI tools as part of daily routines and workflows. 

### The GenAI Hype
The hype surrounding GenAI exploded in the late 2010s, bringing substantial investor interest to the industry and fueling the growth of numerous startups, creating their own AI or building specialized solutions on top of existing ones. 
Financial institutions (FIs) have long employed various AI/machine learning instruments to offer digital-first onboarding, run adverse media screening of their customers, improve false positive detection in transaction monitoring and identify unusual patterns in user activity. Does GenAI have unique potential for changing a current regulatory technology stack, or can it make things worse by empowering cybercriminals and fraudsters?

### The Challenges
The ability to create plausible-looking content makes GenAI shine in the hands of cybercriminals, who use it to bypass know your customer (KYC) procedures in banks, financial technology and crypto apps with fake identities. GenAI applications create fake IDs, proofs of address and other documents, generate photos and even pass the liveness check with deepfakes.

A recent example of a potentially mean GenAI was the network behind the currently inoperative OnlyFake website, which was supposedly able to create realistic-looking IDs. People claimed to be able to pass through document verification at PayPal and cryptocurrency exchanges. 

Later, GenAI applications could also be tasked to create realistic-looking invoices and records for money laundering purposes. Technologies enabled malevolent actors to single-handedly manage multiple synthetic users’ identities and accounts. Over recent years, numerous tech enthusiasts and security experts have pointed out vulnerabilities in existing KYC procedures; however, no large-scale industry research has been published.

### The Opportunities

AML compliance is standardized and directed by legal requirements. A properly trained conversational assistant can help compliance officers with everyday duties and provide a fast search across legal documents and cases. There is little space for AI “creativity,” but GenAI can solve one of the long-standing issues associated with machine learning, the 

### AI bias.

Bias is the fundamental problem of machine learning. Bias may originate from the training data that overrepresents or underrepresents specific groups based on race, gender or other characteristics. Bias can be rooted in the very design of a machine learning model, reproduced through self-training and amplified over time. In this case, GenAI can be tasked to generate vast amounts of synthetic data, such as customer profiles with certain qualities, which will be further used to train other machine learning models, tweak their performance and reach better results. 

### The Considerations for GenAI

There are several matters to consider when discussing the implementation of AI in financial compliance. 
The matter of AI accountability became important with the adoption of machine learning models in business. A quote attributed to a 1970s IBM presentation states: “A computer can never be held accountable; therefore, a computer must never make a management decision.” However, when it comes to GenAI applications, such as chatbots, people use and overuse them in decision-making and even brag about it on X and other social media platforms. In compliance, AI-induced mistakes may come with a high price for both the company and the customer, which means using AI recommendations should be limited.

FIs must be able to explain their decisions to internal and external parties, including regulatory bodies. However, the complexity of modern AI models results in a situation when the input signals might not be easily identifiable or even known. This problem is even worse for generative AIs, which often trade explainability for flexibility and are even more prone to AI hallucination.

Another matter is data privacy, which is even more crucial for companies in the regulated financial market. Machine learning models are prone to data leakages from the training datasets, the capacity to unmask anonymized data through interferences, and “remembering” information about individuals in the training datasets even after the data is discarded. That is a known issue, and some generative AI developers explicitly state that they cannot ensure the security and confidentiality of the information that users provide.

### Conclusion

For decades, machine learning revolutionized business in the financial services and regulatory technology markets. One should not be mistaken by the hype surrounding GenAI: Machine learning models already optimize dozens of crucial processes in AML compliance workflow. 

GenAI became a massive problem for AML compliance, as cybercriminals employed the technology to create synthetic identities of nonexistent people with forged documents and deepfake-powered faces. GenAI has the potential for a positive change in the industry; however, it is not as apparent as its ability to cause chaos for compliance officers.

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Generative AI and Compliance

Money laundering takes different forms and varies by scale. The bigger the reward, the more creative money launderers should be to stay under the radar of the financial compliance system. While some schemes seem obvious, others remain secret until they are accidentally revealed. Here, we review some unusual or creative ways to launder money, which are hard to identify and prevent.

### Art 

Artworks are an attractive vehicle for money laundering because of the highly private nature of the art market, the high value of assets, and the lack of regulations. According to the Art Basel report, the global art trades, including primary and secondary deals, amounted to USD 65 billion in 2023. It’s impossible to assess the share of purchases made to launder dirty money, but there’s a benchmark. After the AML regulations were introduced to the art market in Mexico in 2013, art sales dropped 70% within a year.

Even the legitimate parties in the art market seek discretion, which makes this course of action normal. Deals are often conducted via intermediaries, meaning sellers and buyers don’t know much about each other. Artworks may be sold several times without leaving the exhibition space or a free port (a special economic zone in which such deals are naturally free from customs clearance or taxation). The subjective nature of art valuation creates the potential for price manipulation. 

Finally, the international nature of the art market makes moving money across borders easy. This makes art (along with other easily moved luxury goods) a money laundering instrument of choice for sanctioned oligarchs, corrupt politicians, and other people who don’t want to resort to less “noble” methods.

### NFT

NFTs, or Non-fungible tokens, were introduced in 2014 as a concept of ownership certificates stored on a blockchain, linking to physical or digital assets. In 2021, NFTs skyrocketed, promising to revolutionize digital art and provide artists a new opportunity to earn both from the sale and resale of their works. However, only a few digital artists benefited from the technology that has enriched speculators, fraudsters, and created a tremendous amount of room for money laundering.

Due to blockchain's anonymized nature, NFTs became extremely sensitive to price manipulations that required nothing but several crypto-wallets. So-called wash trading (numerous deals between wallets controlled by a single person or a group to create an illusion of interest and pump the price) totaled 98% of deals on some NFT marketplaces. Unsurprisingly, the NFT market became a haven for criminals who used NFTs to launder money, with little or no oversight from the platforms that made money from each trade.

The market peaked in 2021, with primitive computer-generated CryptoPunk #9998 sold for USD 532 million (which was highly likely an attempt to launder money). By then, the industry was under increased scrutiny from anti-money laundering authorities. In 2022, the market collapsed, leading to a complete devaluation of assets owned by “bigger fools.”

### Gaming economies

Most online games monetize through in-game currencies and digital assets, such as lootboxes, rare items, cosmetics, in-game objects, and more. In many games, digital goods can be traded between accounts or sold on official marketplaces, third-party platforms, or through the resale of redeemable codes or accounts for cryptocurrencies or fiat money (which is usually against Terms of Service). The deals with in-game assets ain’t subject to strict governance (if subject to any), and money laundering there can go unnoticed.

In 2019, Valve, the developer of a well-known cooperative shooter Counter-Strike: Global Offensive, discovered that lootboxes and keys for them, which could be traded between users on the Steam Community Market, became a money laundering vehicle. Nearly all transactions with CS:GO lootboxes and keys were made using stolen credit cards to launder money. 

### Fake bookings

(Nearly) everything can become a money laundering vehicle for a creative criminal. In 2017, the Daily Beast revealed a scheme by a group of Russian hackers. The criminals used legitimate or stolen Airbnb accounts to request bookings and make payments from stolen credit cards to hosts who later returned the money while retaining their share. Despite high commissions for hosts and guests on booking websites, this scheme allowed them to launder money without revealing themselves.

### Staged gambling

The taxes on income from gambling are surprisingly low in many countries, while most casinos have a lazy approach to compliance, even in the EU or the US. The games that ain’t played against the house, such as poker, open an opportunity to effectively launder money and even transfer it between parties.

### Alternative finance

Alternative financial systems, such as Islamic finance, are trust-based and highly ethical but can be easily exploited for money laundering. Islamic finance exists alongside the traditional financial system but embodies the principles of Sharia. Some Islamic financial instruments, such as the informal value transfer system Hawala, essentially work below the radar of the anti-money laundering system and can be abused. The lack of a centralized and standardized regulatory framework in Islamic finance is another problem that allows criminals to breach trust and move illicit funds.

### Laundromats

Large-scale money laundering schemes may include numerous financial institutions, dozens of companies in different jurisdictions, and sophisticated schemes with hundreds of fake contracts. The most prominent example is the Troika Laundromat, which was revealed by the Organized Crime and Corruption Reporting Project (OCCRP) and other journalists in 2019. The scheme was orchestrated by the Troika Dialog investment bank and worked for ten years.

The Laundromat allowed oligarchs, corrupt politicians, and organized crime groups to secretly acquire assets and funnel money to the European Union and the United States. For that purpose, Troika Dialog created at least 75 firms in tax haven jurisdictions that were incorporated within shell companies in other tax haven jurisdictions to conceal ownership. The bank accounts were opened via proxies, such as seasonal workers. 

The shell companies issued, canceled, and paid for contracts, invoices, and loans, supplemented by fake paperwork. The amount of questionable money flown from the EU and the US through Troika Laundromat totaled USD 4.8 billion between 2003 and 2013, and the European banks exploited within the scheme failed to identify suspicious activities and execute proper compliance measures.

### There is much more to come

Money laundering is a lucrative business that develops and adapts to new regulatory measures, changes in policies, and efforts of anti-money laundering bodies. Anytime soon, we will see new (or modernized old) approaches to money laundering that emerge in response to more strict rules and stronger compliance measures imposed by national and supernational authorities.


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Creative ways to launder money

Know Your Customer (KYC) is essential to the modern anti-money laundering framework. KYC guidelines are designed to prevent banks and other regulated companies from being used for illicit activities and serve as a starting point for other anti-money laundering measures. Yet, even though most people understand the underlying rationale behind KYC, it often becomes the worst customer experience in finance.

A poorly automated KYC can take several days, including office appointments and additional paperwork. Compliance officers' decisions are subject to individual racial, gender, or other biases. Some customers consider KYC a violation of privacy, while others are reasonably concerned about data safety. Finally, there are conspiracy theorists and crypto-anarchists afraid of mass surveillance. People also disapprove of implementing KYC over emerging financial instruments like cryptocurrencies (however, this is not the case).

Modern KYC isn’t that bad, but it’s not great either. Here, we will consider what can be done to make KYC faster, less error-prone, and more comfortable for users in the future.

### One-step KYC solution with eID.

Electronic identification cards store basic personal identification information, sometimes biometric data (such as photos for automated visual identification or fingerprint data), and special credentials that allow for reliable corporate or state services authentication. An eID card with an integrated NFC chip can be read using a smartphone or specialized reader, allowing in-person or remote identification.

National legislation for eID evolves, allowing for streamlined KYC. For instance, the comprehensive legal basis for the remote use of digital identities for KYC in Europe is included in the eIDAS 2.0 standards, the European Banking Authority’s (EBA) guidelines, and the 5th AML Directive. Soon, the KYC process in the EU and other parts of the world will become much easier, less annoying, and generally better (just like the identity check in the airport).

### Risk score aggregation and sharing.

Discomfort caused by KYC is partially rooted in its repetitive nature. An individual has to pass KYC checks again and again in different banks, fintech platforms, crypto exchanges, luxury goods points of sale, and so on. Even worse, the decisions vary due to different compliance policies and compliance officers' interpretations of such policies. That leads to stress, dissatisfaction with negative responses, and general customer dissatisfaction.

The industry can overcome this problem by introducing aggregated risk scores that reflect the results of many KYC checks and AML screenings. Such a score should not include full information about the client but rather a tokenized piece of data. A compliance officer will still be able to request additional documents or explanations. Still, for most people, a KYC will become a fast, easy, and error-prone procedure relevant to their previous experience.

### The true potential of AI is still unknown.

Machine learning already serves as a backbone of many compliance procedures. Computer vision models recognize ID data and run liveness checks. Sophisticate algorithms analyze thousands of transactions in real time to identify unusual patterns potentially related to illicit activities. AI also enables perpetual KYC, an approach that constantly improves KYC profiles based on new knowledge about a customer. 

Some people in the industry research the potential of generative AI in compliance; however, it’s limited by the very nature of such ML models. We commented on the matter in our blog: [Trust, but Verify, GenAI in AML Compliance](https://dataspike.io/blog/generative-ai-and-compliance?lang=en). We believe that generative AI can help identify existing software's drawbacks and tweak their behavior by creating digital identities with specified properties to train and improve ML algorithms.

The accelerated development of AI technologies brings both potential and risks. We still need to overcome various problems, including privacy and security threats, the lack of transparency and explainability of AI actions, and align the potential implementation of novel technologies with laws and regulations designed to protect humans.


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Improving KYC

This publication is dedicated to the basic concepts of financial compliance, such as KYC, AML, and others. We are going to start from the basics: compliance itself and Know Your Customer procedures.

### Compliance

Compliance means conforming to rules, regulations, standards, or laws. In finance, compliance includes various procedures designed to prevent money laundering and financing of illegal activities, which include but ain’t limited to terrorism, proliferation, or human trafficking. The respective area of regulation is often referred to by the abbreviation **AML/CTF**, or **Anti-Money Laundering and Counter-Terrorist Financing.**

### KYC

The first essential step in the AML/CTF framework is the **KYC**, or **Know Your Customer**, procedure. To identify new customers, financial companies (such as banks, fintech firms, payment providers, and so on) request an identity document (such as a passport) and other papers that provide basic information about the person. The KYC procedure may include filling out a form, proof of address check, and so on. 
The information acquired during KYC enables companies to run customer due diligence and establish a risk profile. Some additional checks may be complete: the identity of a potential customer may be checked against the lists of Politically Engaged Persons, sanctioned individuals, or open legal databases. 

### eKYC

**eKYC** or **electronic KYC** refers to different forms of KYC automation. For instance, many fintech apps and neobanks provide a mobile-first onboarding experience: a customer is required to take a photo of an ID, a selfie with an ID, and complete a Liveness test (perform several actions on camera, such as turning head or smiling). The information is captured from an ID using optical character recognition (OCR), the selfie allows verifying the ownership of an ID, and the Liveness test validates that no photomontage or deepfake was used.
More sophisticated examples of eKYC include extracting digital data from the government-issued smart ID. For instance, Estonians can use their eIDs for over 600 government services and any legal interaction within the country, including opening accounts in financial institutions. India’s Aadhaar eID system is one of the most prevalent in the world, registering more than 1.29 billion people. Aadhaar-based eKYC allows financial or telecommunication service providers to verify the identity of Indian customers online and offline.
Electronic KYC has significant benefits over the paper-based approach. It’s faster, more convenient, and less prone to human bias and mistakes. 

### KYB

**Know Your Business**, or **KYB**, is an equivalent of the KYC procedure for sole proprietorships and legal entities. The company may be required to provide its constitutional documents, information on beneficial owners and their identification documents, business licenses, etc. The KYB procedure aims to verify that the company is legitimate (and isn’t a shell company) and its owners ain’t included in the sanction and PEP lists.

### KYCC

**Know Your Customer’s Customer**, or **KYCC**, is an additional compliance measure beyond regular KYB. As a part of KYCC, the companies may be required to provide information about their own customers and partners. KYCC may help to identify fraudulent activities proactively but greatly increases the compliance burden for financial institutions. 

### KYC and compliance

Any company can implement KYC procedures for good. However, some industries are subject to specific regulations and must enforce strict AML policies, including KYC, transaction monitoring, and so on. KYC is obligatory for financial companies (banks, fintech, payment providers), marketplaces, luxury services and goods, gambling, cryptocurrencies, and more.
KYC works as a robust protection against many kinds of financial crime. Basic steps, such as ID check and proof of address check, drive away potential fraudsters while continuous monitoring helps identify suspicious activities and prevent them. KYC isn’t a magic pill but a measure that enables companies to implement strong AML policies.

### KYC beyond compliance

Even though KYC is a legal requirement for some companies, its benefits go far beyond mere compliance. Detailed customer onboarding, continuous monitoring, and the smart use of information collected give the companies the upper hand in the competition.
In the context of **customer relations management**, the information collected via customer onboarding (including KYC) allows for building comprehensive customer profiles and offering products and services tailored to customer needs. A better understanding of customers opens **cross-selling opportunities** and helps to improve sales and marketing processes. 

KYC is also an invaluable source of information for **data analysis** that can provide many insights into the customer behavior, market trends, and potential risks.

Follow #DataSpike for insightful updates in KYC and financial compliance!

Lessons on sanctions evasion

Try DataSpike Now

Lessons on sanctions evasion

The brief history of money laundering (from ancient times to the early 21th century)

Generative AI and Compliance

Creative ways to launder money

Improving KYC

Financial Compliance 101: Glossary