How criminals use real estate to launder money and what can be done to stop it


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Matt Long, Head of Anti-Money Laundering Solutions, Quantexa

Real estate is especially attractive to criminals, as it is to any legitimate investor. It is a common component of a balanced investment and / or business strategy and is likely to grow over time.

In fact, according to recent report The European Parliament has estimated the share of real estate in confiscated criminal assets, which can be used as an indicator of how much money is laundered through real estate, at 30 percent between 2011 and 2013. Europol report Looking at the trends in organized crime in the European Union, the majority of criminal groups and networks (68 percent) use money laundering methods such as investing in property to try to legitimize or hide their illicit proceeds.

For criminals, real estate investments provide a cover for respectability and legitimacy, which implies “explainable” large lump sums and is often subject to limited scrutiny in many global jurisdictions.

Actually, number of technicians are used by criminals to hide the identity of both themselves and illegal sources of funds used to buy property – cash, shell companies, trusts. As can be seen from various reports of leaks, such as the Panama Papers, the use of shell companies to buy property was of immense value to those who wanted to hide or hide their identity.

The money laundering risk associated with the property is further increased when the buyer does not need lender financing and regulated financial institutions are not involved. Other parties are used, such as settlement / transaction attorneys, solicitors and / or agents, appraisers, property traders and insurance companies, and therefore no anti-money laundering (AML) obligations apply in some jurisdictions.

Likewise, in the sale of property, “legitimate” proceeds from crime or corruption can be further integrated into the financial system and separated from their original illicit source through similar opaque structures such as trusts and shell companies. The proceeds can also be reinvested in other real estate, luxury goods and securities and ultimately cashed out as net cash.

This image tracks the estimated movement of laundered funds from real estate transactions in different countries and across different platforms (source: Quantexa).

Fighting anonymity

Money laundering through real estate has many high profile case studies. For example, in a recent announcement from U.S. Department of Justicethe suspect, charged with money laundering, allegedly “channeled the proceeds (millions of fraudulent) schemes through at least six properties on the island of Hawaii.”

Recognizing the ongoing global risk of money laundering from real estate and the associated anonymity, countries are trying to enforce the identification and disclosure of beneficial ownership through the US Corporate Transparency Act and the Anti-Money Laundering Directive in Europe.

However, while both of these initiatives are widely recognized and endorsed as key tools in the fight against economic crime, including the use of real estate purchased through companies, the registries themselves are not without problems.

Reducing risk, detecting suspicious activity

To apply a risk-based approach to detecting and reporting suspicious activity, an institution must ask a series of questions before a real estate transaction, activity or customer relationship can be deemed suspicious and regulatory reporting obligations can be triggered.

For example, in determining a customer’s risk, the ability to confidently identify the “real” customer and the involvement of third parties or corporations in deliberately concealing or disguising the identity of the beneficial owner without a legitimate business justification is critical.

The institution should also consider not only identifying and assessing the risk associated with the buyer, but the cumulative or cumulative money laundering risks associated with the entire purchasing network, including the seller and everyone involved in the transaction.

When buying real estate involving high-ranking officials or their family members who require increased attention, or because of certain international regulations, such as sanctions, it is necessary to be able to identify and assess the risks associated with relationships and business interests.

In terms of transaction risk and geographic location, risk indicators such as source of funds, type of property involved, perceived undervaluation or overvaluation, mismatch between buyer and seller and property, large amounts of cash, complex loans or other financing need to consider the presence of fictitious companies. This is especially true for real estate transactions in high-risk locations that are known for weak anti-money laundering regimes.

Given the evolving regulations and the general complexity associated with the real estate money laundering risk, many regulated institutions are challenged to identify and respond to real risk, while ensuring an efficient and effective compliance process and customer service expectations.

Context is everything

Traditionally, consolidating internal and external data sources and taking action against attackers was done manually and was very difficult for investigators and due diligence teams. This problem is exacerbated by traditional rule-based transaction monitoring systems, which often focus on the institution’s customers and the movement of purchase money in isolation, which can both generate a large number of false positives and miss broader indicators of risk.

To help overcome this inefficient process and reduce exposure to risks in real estate transactions, a growing number of regulated institutions are using technologies that analyze data from internal and external sources. This allows them to automatically gain a deep understanding of all parties involved in a real estate transaction and provide context as to why a real estate transaction may or may not be suspicious. The approach to combining risk data is a process called entity resolution that combines disparate data points from multiple systems into a single, accurate view.

By making a problem-solving decision, researchers and analysts can spend less time collecting data and performing time-consuming manual research, and instead focus on real risk. This process allows financial institutions to automatically combine internal Know Your Customer (KYC) data with external data sources to identify, verify, and evaluate all parties involved in a transaction.

Graphical analytics is critical

Once the data has been processed, you can use linked graph analysis to find hidden relationships, which can then reveal hidden risks in real estate transactions. When an institution can see the alleged interrelated relationships and transactional activity in general, it can then assess the holistic risk and present the results to the researcher as a contextual alert to improve the efficiency and effectiveness of both AML investigations and KYC processes.

Most financial institutions have a wealth of customer, counterparty, and transactional data that they can use in conjunction with external data sources to create powerful contextual insights and transform compliance programs regarding the complexity and risk of real estate purchases.

To be truly effective, financial institutions must strive to create an intelligent data management system. By deploying innovative technologies such as entity resolution and graphical analytics, banks can create a unified view of their customers and confidently automate their business decisions. These practices help them remain accountable to regulators while reducing the risks and compliance costs associated with the vulnerable real estate sector.

Quantexa is a London-based data analysis and software development firm that serves banking and insurance, among others.

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