How Criminals Use Real Estate to Launder Money, and What Can Be Done to Stop It
By Matt Long, head of anti-money-laundering solutions, Quantexa
Real estate is particularly attractive to criminals in the same way it is to any legitimate investor. It is a common component of a measured investment and/or business strategy and is highly likely to appreciate over time.
In fact, according to a recent report by the European Parliament, the share of real estate in criminal assets confiscated, which can be used as an indicator as to how much money is laundered through real estate, was estimated at 30 percent between 2011 and 2013. It was also noted in the latest Europol report looking at organized crime trends in the European Union that most 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 of respectability and legitimacy that involves “explainable” high-value single amounts and are frequently subject to reduced scrutiny in many global jurisdictions.
In fact, a number of techniques are used by criminals to cover the identities of both themselves and the illicit sources of funds used to purchase property — cash, shell companies, trusts. As seen in various “leak” reports, such as the Panama Papers, the use of shell companies to purchase property has been of immense value to those wishing to obscure or hide their identities.
The money laundering risk associated with property is further enhanced when the purchaser does not need lender financing and regulated financial institutions are not involved. Other parties such as settlement/closing attorneys, solicitors and/or agents, appraisers and title search and insurance companies are used, and therefore no anti-money-laundering (AML) compliance obligations are applied in certain jurisdictions.
Similarly, when property is sold, the “legitimate” proceeds of crime or corruption can be further integrated into the financial system and distanced from their original illicit source through similar opaque structures, such as trusts and shell companies. Proceeds may also be reinvested in other properties, luxury goods and securities and eventually cashed out as clean funds.
Money laundering through real estate has many high-profile case studies. For example, in a recent announcement from the U.S. Department of Justice, a suspect indicted for money laundering was alleged to have “routed the proceeds of (millions of fraudulent) schemes through at least six pieces of real estate on the island of Hawaii.”
Having recognized the ongoing global risk of real estate money laundering and associated anonymity, countries are attempting to force the capture and disclosure of ultimate beneficial ownership through the likes of the Corporate Transparency Act in the United States and the Money Laundering Directives in Europe.
However, even though both of these initiatives are widely recognized and endorsed as being key tools in the fight against economic crime, including the usage of real estate purchased through companies, the registries themselves are not without challenge.
Mitigating Risk, Detection Suspicious Activity
In order to apply a risk-based approach to detecting and reporting suspicious activity, a number of questions need to be asked by the institution before the real estate transaction, activity or customer relationship can be considered suspicious and regulatory reporting obligations can be activated.
For example, when determining the customer’s risk, the ability to confidently identify the “real” purchaser and the involvement of third parties or a corporation to intentionally hide or mask the beneficial owner’s identity, without a legitimate business rationale, is critical.
The institution should also consider not only identifying and assessing the risk associated with the buyer, but the collective or aggregated money laundering risks associated with the entire purchasing network, including the seller and anyone else involved in the transaction.
For property purchases involving high-ranking officials or their families who require enhanced attention, or because of specific international provisions like sanctions are in order, being able to identify and risk assess relationships and business interests is essential.
From a transaction and geography risk perspective, risk indicators such as the source of funds, the type of property involved, suspected under- or overvaluation, a mismatch between buyer and seller and the property, the extensive presence of cash, complex loans or other financing and the presence of shell companies need to be considered. This holds particularly true with regard to deals for properties in high-risk locations that are known for having weak anti-money-laundering regimes.
Given the evolving regulations and general complexity surrounding real estate money laundering risk, the challenge for many regulated institutions is to identify and act on the genuine risk, while still ensuring an efficient and effective compliance process and meeting customer service expectations.
Context Is Everything
Traditionally, consolidating and acting on both internal and external data sources to take action against bad actors has been highly manual and very challenging for AML investigators and due diligence teams. This challenge is perpetuated by traditional rules-based transaction monitoring systems that frequently focus on the institution’s customer and the purchasing money movement in isolation, which can both generate high volumes of false positives or miss broader risk indicators.
To help overcome this inefficient process and mitigate risk exposure in real estate transactions, an increasing number of regulated institutions are using technology that looks at data across internal and external sources. This allows them to automatically obtain deep insight into all parties connected with the property transaction and provide context about why the real estate transaction may or may not be suspicious. The approach to connecting risk data is a process called entity resolution, which aggregates disparate data points from multiple systems into an accurate single view.
By implementing entity resolution, investigators and analysts are able to spend less time gathering data and carrying out time-intensive manual research and instead focus on real risk. This process allows financial institutions to automatically piece together internal know your customer (KYC) data with external data sources to identify, verify and assess all connected parties to the transaction.
Graph Analytics Are Critical
Once the data is resolved, connected graph analysis can be used to find hidden relationships, which can then uncover hidden risks within real estate transactions. When an institution is able to see suspected connected relationships and transactions activity in their entirety, it can then assess the holistic risk and present the findings to an investigator as a contextualized alert to increase the efficiency and effectiveness of both AML investigations and KYC processes.
Most financial institutions have a wealth of customer, counterparty and transaction data, which they can leverage alongside external data sources to create a powerful contextual view and transform compliance programs surrounding the complexity and risk of real estate purchases.
To be truly effective, financial institutions must look to build an intelligent, data-driven capability. By deploying innovative technologies, such as entity resolution and graph analytics, banks can build single views of their customer and confidently enable the automation of decisions surrounding their activity. These practices help them remain accountable to regulators while simultaneously reducing risks and compliance costs associated with the vulnerable real estate sector.
— Quantexa is a London-based data analytics and software development firm that serves the banking and insurance industries, among others.