Wash Trading is an unethical practice of artificially manipulating the price by buying or selling assets.
Money laundering is rampant in this field due to the global yet unregulated markets.
KYC and AML have become a need with the malicious activities that go down under the rugs of decentralization.
Cryptocurrency exchanges are centralized hubs where traders meet to trade different digital assets. As such, they act as intermediaries facilitating transactions and storing their users’ funds in a centralized location. However, the characteristics and nature of a blockchain make it difficult for these intermediaries to operate as they do with traditional financial markets.
In decentralized exchanges (DEXs) like IDEX or services like Bisq, users directly transfer tokens from one party to another by sending them to an Ethereum address. When both parties can control their own private keys, there is no need for an intermediary who can be hacked or maliciously take user funds.
However, most centralized exchanges have substandard security practices given the lack of trustless alternatives: KYC checks, hot and cold wallets, Know Your Customer documents, and other anti-money laundering schemes are expensive processes that almost all centralized exchanges implement. Users may ask: Is there a way to combine the convenient experience of trading on centralized exchanges with the trustless benefits of decentralized ones? Solving these challenges will require adopting new technologies beyond blockchain — artificial intelligence and machine learning algorithms that understand natural human language could help detect money laundering activities even if they occur on a decentralized platform.
Money laundering is a process by which criminals disguise the origins of illegally obtained assets. It can occur in any financial setting but is often associated with physical currencies like the US dollar. Criminals like to use US dollars because they are easy to obtain and widespread on a global scale. Once criminals obtain US dollars through several illicit means, they try to disguise them by passing them off as though they were obtained legitimately. Although cryptocurrencies like Bitcoin were designed to be decentralized and trustless, they are still mostly traded on centralized exchanges. These exchanges are a prime target for criminals who want to take illegal funds and disguise them as legitimate ones. By moving the funds from one cryptocurrency to another, criminals can slowly clean their funds by making them appear more legitimate over time. This process is referred to as money laundering.
Wash trading is a form of market manipulation in which a trader buys and sells a contract or commodity for their own account to create a false impression of demand for a commodity. Manipulators create an illusion of significant trading activity to trick others into thinking there are more buyers or sellers of a commodity than actually exist. For example, one person or company can buy and sell to themselves at slightly different prices to create the illusion of an active market when there is none. In an NFT setting, a trader (or set of traders) buys and sells the same underlying asset to themselves on different exchanges to make it appear as if there is significant demand for the asset when there is not. This is done by moving the underlying asset between accounts to create a false impression of demand for the asset. It is easy to detect wash trades when assets are fungible and have single-source creation. However, assets that have non-fungible tokens (NFTs) will be harder to detect.
Cryptocurrencies are a new asset class with a high degree of anonymity that has attracted nefarious actors. Criminals want to obtain cryptocurrencies through illicit means to “wash” them to make them appear legitimate funds. They do this because they want to use this money to buy goods and services or exchange them for government-issued currencies. Most centralized exchanges require KYC information to prevent money launderers from using them to buy and sell cryptocurrencies. Decentralized exchanges and decentralized hybrid exchanges like IDEX, which support NFTs and fungible tokens, will be the next stage of evolution in the crypto trading industry. Given the decentralized nature of these exchanges, they are not subject to regulation like centralized exchanges are. Therefore, they are not required to implement costly KYC and AML processes that can drive up the cost of trading.
There are a few different ways that money laundering can be detected in cryptocurrencies:
Exchanges can implement an internal process to detect suspicious trading activity and report this information to regulators.
Machine learning algorithms can also be used to automatically detect suspicious trading activity. These algorithms are programmed with rules that detect abnormal trading activity that may indicate money laundering.
Machine learning algorithms use data to train themselves to recognize patterns.
There are three phases in the machine learning process: data collection, data preparation, and making predictions. When algorithms are trained with historical data, they can be taught to recognize anomalous trading activity that may indicate money laundering. To build a machine learning model, you will need to collect data, decide on a statistical approach for building and testing your model, and then deploy your model to production.
Fungible tokens can help prevent money laundering in a few different ways:
The implementation of KYC and AML standards on decentralized exchanges will prevent criminals from using these exchanges to launder money.
The implementation of machine learning algorithms can help detect money laundering even if it is done on a decentralized exchange.
In an ideal world, a token with a single supplier will be easy to detect and flag for money laundering activities because it would be impossible for anyone to trade different quantities of the same token.
However, adopting non-fungible tokens (NFTs) like CryptoKitties, which have a single supply but multiple owners, will make it harder to detect money laundering activities.
Decentralized exchanges will help reduce money laundering in the crypto industry, but they cannot wholly stop criminals from using them. Since centralized exchanges also have KYC and AML processes, criminals who want to launder money will also go to these exchanges. However, a few things will help improve the fight against money laundering. First, decentralized exchanges can implement KYC and AML standards to make it harder for criminals to use them. Second, decentralized exchanges should implement machine learning algorithms to help detect money laundering activities. Ultimately, blockchain technology and cryptocurrencies will have a transformative effect on society. These technologies will enable people to transact peer-to-peer in a way that has never been possible.