Money laundering in Canadian real estate is a widely accepted fact of life these days, but the impact isn’t. Government and academics are still debating how much money is needed to distort a market. The truth is, not a whole lot is required to distort any asset market. This is a problem the stock market has been dealing with since the 1920s, and the reason it’s so highly regulated.
The key to understanding how laundering impacts prices, is understanding the marginal buyer. If you understand how prices are set, it doesn’t take long to see it’s not the amount of money that’s the issue. Price distortions can be the result of capital velocity, and the intention of the marginal buyer.
Squad Goal: Money Laundering
First, let’s clarify laundering. Money laundering is the process of making illegally-gained proceeds appear legit. Those proceeds can be from monstrous activity, like fentanyl trafficking. Sometimes it’s less nefarious, like earned income evading a country’s arbitrary capital controls. All of it is illegal however, and is people are trying to hide it. There’s a few ways to do it – but the all follow the same basic process.
Money laundering is usually done in three phases – placement, layering, and integration. Placement is the introduction of cash into a legitimate system. Layering is conducting multiple transactions through multiple accounts, to obfuscate a trail. Integration is working the money back into the legit system. Properly laundered money should be extremely difficult to tell from legitimate business.
One last time, the goal is clean money. Parking cash long term in assets is not typical – these aren’t investors. That said, the layering process usually involves moving cash around very quickly. Fast moving cash often leaves a wake, especially if it’s moving through real estate. To understand why, you need to understand a few concepts – marginal buyers, money laundering, and sales comps.
Marginal Buyers Be Cray, Cray
The marginal buyer is an important part of any asset market, especially fast moving ones. This is the person(s) or company that’s willing to pay the most for an asset. They are a small percent of the potential buyer pool, but the ones that actually buy the assets. The competition between marginal buyers is key to asset price escalation. Every market has one on the way up, but skill and motive determine how healthy the outcome is.
If the marginal buyer is a rational investor, they’re thinking about liquidity. They’re restrained in their bidding price, because they need to be able to make a profit. Rational consideration helps to keep a market sane. If the buyer isn’t bound by rationale or logic, things start to get sloppy.
A cannabis company making $20 million a year in revenue fetching close to the valuation of GM? An investment condo that produces negative cash flow? The buyers of these things aren’t making rational decisions. It doesn’t mean they can’t make money, but they are playing a game of greater fool. You’re hoping that the next buyer is more irrational than you – whether you know that’s the plan or not. When you have an influx of irrational money, it’s hard to figure out what’s real.
The Objective Of Money Laundering
When you buy an asset, whether a home or an oz of pink kush, you try to get the best value for your time and money. You want a deal. The seller is trying to extract the maximum price they can get from you, without driving you away. They don’t want you to get a great deal. The balance of interests go back and forth, and is a fundamental part of a functioning market. Opposing interests help balance things, plus or minus a dash of exuberance.
If you are money laundering, that’s not the case. The objective is to move as much cash, as fast as possible. This often involves large assets, and the bigger the price – the better. Especially if there’s a recurring payment component. Both the seller and the money laundering buyer want the highest acceptable price.
Sellers often feel somewhere between a genius and a lottery winner when they find this buyer. Competition between interests align, and there’s minimal friction preventing prices from going higher. The seller assumes their master negotiation skills prevailed. The money laundering buyer gets to move more money than they were asking for. The buyer seems “irrational,” but that’s just the market. Real estate agents without a clue, begin to rationalize and normalize this behavior. There’s no more land is a popular explanation.
Understanding How Real Estate Prices Are Born
We all know how prices are born. When a homeowner finds a selling agent they love, they go into a quiet backroom, make a few strokes, and boom! The multiple listing service spits out the comparables, a.k.a. your comps. Comps are a fancy way of saying what has sold around you, like the neighbor’s house. These numbers are then used to establish a baseline price, which a selling agent tries to push higher.
No comps in your neighborhood? No problem, we’ll use the neighborhood next door. Eventually, the arbitrary line disappears that separates the pricing in neighborhoods. This is when you hear dumb things, like “Shaughnessy Heights adjacent.” This spreads like a virus, from one neighborhood to the next.
Vancouver Real Estate Prices Overheating
A time-lapse of real estate sales in the City of Vancouver. Herd behavior can be observed in clusters, as people pay over or under the list price – based on whether other people are doing it.
Source: Better Dwelling.
Poisoning The Comp System
Smarter real estate agents can already spot the problem here. Let’s look at an example, say you’re shopping for a home in Anyplace, BC. You’re watching the homes in the neighborhood climb at an average of 5% from last year. You find a place you’re ready to put on offer on, do some research, and come up with an offer. All of a sudden, a money launderer shows up, and offers the owner 10% over ask for a “quick close.” You’re not too worried, your agent told you the place a few doors down is going to be on the market next week.
Unfortunately, the new place now uses the home owned by the money launder as a comp. Now the ask is 10% more than you were expecting, because the marginal buyer set the price down the street. Someone else bites, and buys it before it “goes too high.” Now the money launderer’s buy was just validated in the system. But wait – there’s more.
Remember, the goal of laundering isn’t to buy a house, it’s to clean the money. They list the home again, let’s say another 10 points higher than bought. Bonus points if they can turn it into a wash trade, and sell it to another associated launderer. A regular family shopping down the street uses your washing machine as a comp for their buy. Behavior typically only seen in the frothiest of asset bubbles, can surface quickly. Exuberant buyers, both illicit and legit, compete and drive prices higher.
Driving Exuberance In Canadian Real Estate
An index of exuberance Canadian real estate buyers are demonstrating, in relation to pricing fundamentals. Once above the critical threshold is breached, buyers are no longer using fundementals. Instead they resort to market momentum, and the possiblity of reward is justification enough.CanadaCritical Values1984 Q31985 Q31986 Q31987 Q31988 Q31989 Q31990 Q31991 Q31992 Q31993 Q31994 Q31995 Q31996 Q31997 Q31998 Q31999 Q32000 Q32001 Q32002 Q32003 Q32004 Q32005 Q32006 Q32007 Q32008 Q32009 Q32010 Q32011 Q32012 Q32013 Q32014 Q32015 Q32016 Q32017 Q32018 Q3-3-2-1012345Index
| Quarter | Canada | Critical Values |
|---|---|---|
| 1984 Q3 | -2.141 | -0.064 |
| 1984 Q4 | -2.053 | 0.072 |
| 1985 Q1 | -2.092 | 0.132 |
| 1985 Q2 | -2.154 | 0.19 |
| 1985 Q3 | -2.107 | 0.283 |
| 1985 Q4 | -2.168 | 0.304 |
| 1986 Q1 | -2.17 | 0.348 |
| 1986 Q2 | -2.242 | 0.394 |
| 1986 Q3 | -2.274 | 0.405 |
| 1986 Q4 | -2.3 | 0.448 |
| 1987 Q1 | -2.229 | 0.489 |
| 1987 Q2 | -2.102 | 0.51 |
| 1987 Q3 | -2.121 | 0.519 |
| 1987 Q4 | -2.225 | 0.551 |
| 1988 Q1 | -2.305 | 0.584 |
| 1988 Q2 | -1.906 | 0.59 |
| 1988 Q3 | -1.74 | 0.61 |
| 1988 Q4 | -1.776 | 0.621 |
| 1989 Q1 | -1.408 | 0.665 |
| 1989 Q2 | -0.8 | 0.699 |
| 1989 Q3 | -1.483 | 0.712 |
| 1989 Q4 | -1.204 | 0.716 |
| 1990 Q1 | -0.946 | 0.739 |
| 1990 Q2 | -0.852 | 0.762 |
| 1990 Q3 | -1.425 | 0.819 |
| 1990 Q4 | -1.538 | 0.836 |
| 1991 Q1 | -1.543 | 0.855 |
| 1991 Q2 | -1.387 | 0.871 |
| 1991 Q3 | -1.14 | 0.89 |
| 1991 Q4 | -1.108 | 0.899 |
| 1992 Q1 | -1.224 | 0.899 |
| 1992 Q2 | -1.151 | 0.901 |
| 1992 Q3 | -1.216 | 0.929 |
| 1992 Q4 | -1.234 | 0.942 |
| 1993 Q1 | -1.233 | 0.954 |
| 1993 Q2 | -1.271 | 0.96 |
| 1993 Q3 | -1.269 | 0.971 |
| 1993 Q4 | -1.314 | 0.971 |
| 1994 Q1 | -1.329 | 0.974 |
| 1994 Q2 | -1.327 | 0.981 |
| 1994 Q3 | -1.352 | 0.981 |
| 1994 Q4 | -1.361 | 0.991 |
| 1995 Q1 | -1.398 | 1.015 |
| 1995 Q2 | -1.442 | 1.018 |
| 1995 Q3 | -1.459 | 1.025 |
| 1995 Q4 | -1.475 | 1.03 |
| 1996 Q1 | -1.489 | 1.03 |
| 1996 Q2 | -1.5 | 1.059 |
| 1996 Q3 | -1.511 | 1.066 |
| 1996 Q4 | -1.426 | 1.071 |
| 1997 Q1 | -1.511 | 1.071 |
| 1997 Q2 | -1.559 | 1.076 |
| 1997 Q3 | -1.584 | 1.076 |
| 1997 Q4 | -1.569 | 1.076 |
| 1998 Q1 | -1.602 | 1.079 |
| 1998 Q2 | -1.608 | 1.084 |
| 1998 Q3 | -1.621 | 1.087 |
| 1998 Q4 | -1.626 | 1.092 |
| 1999 Q1 | -1.668 | 1.099 |
| 1999 Q2 | -1.67 | 1.099 |
| 1999 Q3 | -1.698 | 1.107 |
| 1999 Q4 | -1.683 | 1.111 |
| 2000 Q1 | -1.701 | 1.116 |
| 2000 Q2 | -1.519 | 1.124 |
| 2000 Q3 | -1.534 | 1.133 |
| 2000 Q4 | -1.583 | 1.153 |
| 2001 Q1 | -1.497 | 1.153 |
| 2001 Q2 | -1.529 | 1.157 |
| 2001 Q3 | -1.439 | 1.157 |
| 2001 Q4 | -1.099 | 1.16 |
| 2002 Q1 | -0.196 | 1.16 |
| 2002 Q2 | -0.164 | 1.16 |
| 2002 Q3 | 0.071 | 1.16 |
| 2002 Q4 | 0.883 | 1.163 |
| 2003 Q1 | 1.191 | 1.164 |
| 2003 Q2 | 1.696 | 1.164 |
| 2003 Q3 | 2.061 | 1.164 |
| 2003 Q4 | 1.851 | 1.17 |
| 2004 Q1 | 2.404 | 1.17 |
| 2004 Q2 | 3.056 | 1.17 |
| 2004 Q3 | 2.742 | 1.189 |
| 2004 Q4 | 2.14 | 1.193 |
| 2005 Q1 | 2.615 | 1.193 |
| 2005 Q2 | 2.991 | 1.193 |
| 2005 Q3 | 2.829 | 1.205 |
| 2005 Q4 | 2.897 | 1.206 |
| 2006 Q1 | 3.576 | 1.206 |
| 2006 Q2 | 4.311 | 1.206 |
| 2006 Q3 | 4.318 | 1.206 |
| 2006 Q4 | 3.66 | 1.206 |
| 2007 Q1 | 3.786 | 1.209 |
| 2007 Q2 | 4.781 | 1.222 |
| 2007 Q3 | 4.359 | 1.222 |
| 2007 Q4 | 2.951 | 1.222 |
| 2008 Q1 | 2.898 | 1.222 |
| 2008 Q2 | 2.55 | 1.222 |
| 2008 Q3 | 0.976 | 1.222 |
| 2008 Q4 | 0.303 | 1.226 |
| 2009 Q1 | -0.035 | 1.228 |
| 2009 Q2 | 0.612 | 1.23 |
| 2009 Q3 | 0.867 | 1.23 |
| 2009 Q4 | 0.823 | 1.23 |
| 2010 Q1 | 1.129 | 1.239 |
| 2010 Q2 | 1.166 | 1.239 |
| 2010 Q3 | 0.644 | 1.239 |
| 2010 Q4 | 0.451 | 1.239 |
| 2011 Q1 | 0.784 | 1.239 |
| 2011 Q2 | 1.009 | 1.24 |
| 2011 Q3 | 0.857 | 1.243 |
| 2011 Q4 | 0.649 | 1.257 |
| 2012 Q1 | 0.922 | 1.268 |
| 2012 Q2 | 1.201 | 1.268 |
| 2012 Q3 | 0.93 | 1.271 |
| 2012 Q4 | 0.694 | 1.271 |
| 2013 Q1 | 0.783 | 1.271 |
| 2013 Q2 | 1.131 | 1.272 |
| 2013 Q3 | 0.972 | 1.272 |
| 2013 Q4 | 0.943 | 1.272 |
| 2014 Q1 | 1.057 | 1.272 |
| 2014 Q2 | 1.304 | 1.272 |
| 2014 Q3 | 1.168 | 1.272 |
| 2014 Q4 | 1.097 | 1.275 |
| 2015 Q1 | 1.334 | 1.28 |
| 2015 Q2 | 1.6 | 1.28 |
| 2015 Q3 | 1.517 | 1.28 |
| 2015 Q4 | 1.531 | 1.28 |
| 2016 Q1 | 1.877 | 1.28 |
| 2016 Q2 | 2.468 | 1.28 |
| 2016 Q3 | 2.45 | 1.28 |
| 2016 Q4 | 2.208 | 1.28 |
| 2017 Q1 | 2.962 | 1.28 |
| 2017 Q2 | 3.306 | 1.28 |
| 2017 Q3 | 2.211 | 1.286 |
| 2017 Q4 | 1.708 | 1.286 |
| 2018 Q1 | 1.826 | 1.286 |
| 2018 Q2 | 1.922 | 1.286 |
| 2018 Q3 | 1.488 | 1.286 |
Source: Federal Reserve Bank of Dallas, Better Dwelling.
Now in this example, just a few sales would have helped to push the comps up to 21% higher. There would also be hundreds of sales validating the price movements in between. Each time the launder injects capital, they inject a new marginal buyer. The whole time, Boomers are stoking the coals on this fire, explaining this is “earned equity.” If you want your own, you need to work as hard as they did. Standing by as each irrational player enters the market is exhausting work. Boomers also had to save uphill for a down payment… both ways, in the snow or something.
“It Wasn’t That Much Money”
Still think a small amount of money can’t influence prices? Clearly you’re not familiar with another asset class – stocks. CNBC host Jim Cramer once ranted that his fund could manipulate stock prices with as little as $5 million. Nav Singh Sarao, spoofing just $170 million worth of orders, set off events that led to the DJIA losing $1 trillion in just a few minutes. Note: the orders were spoofed – meaning he only had a fraction of the money. More formally, academics determined traders can use less than $500,000 to raise a stock price 1%, by targeting the bottom half of the liquidity spectrum.
Smack That Ask: It’s Not What You Pay, It’s What You Think People Will Pay
An example of Dynamic Layering, the spoofing technique used by Nav Singh Sarao. The lower dots are bids placed, that only sometimes execute as a trade. Free markets can’t effectively determine if participants are executing trades in good faith – required for natural price balance.
Source: US Department of Justice.
Each of the situations are different, but have two common things – influence and intent. While not that much money, each example precipitated events that had a big impact. The actual trades weren’t so important, so much as influencing volatility. Setting the marginal buyer definitely counts as an event that influences market direction.
Each one of these events are also easily mistaken for an accident, which conceals intent. Fat finger, trade algo gone wild, and/or eager market buyer. Each one of these situations could have been caused by regular, everyday occurrences. Now it’s unlikely that money laundering is focusing on systematic trading of homes to inflate prices. It could however, be one of the times an unintentional destabilization of a market is just a side effect.
Velocity may also be playing a large roll here. When cash goes into one house, it’s eventually sold. That cash likely gets pumped through multiple transactions for the purposes of layering. That means more houses are being bought with the money, and profits. More sophisticated operations also have combine layering with an integration platform. Bonus points if the integration platform is registered with FINTRAC. That way the integration platform is also in charge of submitting suspicious transaction reports.
Combine this with an opaque comp system with closed data, and it’s really hard to catch. The chances of buyers being able to do their own due diligence on a property buy is virtually nil. Closed systems also mean no wide scale analysis of the transaction. There’s very little way for anyone outside of regulators to actually be able to determine it.
Where’s The Money At?
While Canadian cities are debating whether dirty money impacts prices, the rest of the world made up its mind. Transparency International UK found a significant correlation between shell companies, and elevated prices. London for instance, has 87,000 homes owned by anonymous companies. According to Christoph Trautvetter of Netzwerk Steuergerechtigkeit, the estimated impact from dirty money in London is 20% of the price increases.
London, UK Average Home Sale Price
The average sale price of a London, UK home. The estimate removes the 20% of annual gains attributed to the influence of money laundering. The number also assumes no laundering was done prior to 2008. LOL.Avg. priceEst Avg. w/o money launderingJan 2008May 2008Sep 2008Jan 2009May 2009Sep 2009Jan 2010May 2010Sep 2010Jan 2011May 2011Sep 2011Jan 2012May 2012Sep 2012Jan 2013May 2013Sep 2013Jan 2014May 2014Sep 2014Jan 2015May 2015Sep 2015Jan 2016May 2016Sep 2016Jan 2017May 2017Sep 2017Jan 2018May 2018Sep 2018Jan 2019200,000250,000300,000350,000400,000450,000500,000UK Pounds
| Period | Avg. price | Est Avg. w/o money laundering |
|---|---|---|
| Jan 2008 | 298,596 | 292,408 |
| Feb 2008 | 295,700 | 290,716 |
| Mar 2008 | 293,605 | 289,580 |
| Apr 2008 | 294,346 | 291,238 |
| May 2008 | 295,163 | 292,676 |
| Jun 2008 | 290,100 | 289,272 |
| Jul 2008 | 290,261 | 291,348 |
| Aug 2008 | 281,721 | 284,907 |
| Sep 2008 | 276,487 | 280,872 |
| Oct 2008 | 266,999 | 273,311 |
| Nov 2008 | 258,647 | 266,447 |
| Dec 2008 | 253,881 | 262,704 |
| Jan 2009 | 253,093 | 256,760 |
| Feb 2009 | 249,847 | 254,652 |
| Mar 2009 | 247,264 | 253,015 |
| Apr 2009 | 245,351 | 252,456 |
| May 2009 | 249,991 | 256,843 |
| Jun 2009 | 253,596 | 260,152 |
| Jul 2009 | 259,793 | 266,882 |
| Aug 2009 | 262,076 | 269,014 |
| Sep 2009 | 267,501 | 273,570 |
| Oct 2009 | 268,780 | 274,769 |
| Nov 2009 | 266,837 | 273,197 |
| Dec 2009 | 270,118 | 276,145 |
| Jan 2010 | 279,724 | 278,374 |
| Feb 2010 | 278,753 | 278,221 |
| Mar 2010 | 280,472 | 280,200 |
| Apr 2010 | 281,981 | 282,608 |
| May 2010 | 281,762 | 282,956 |
| Jun 2010 | 284,541 | 285,548 |
| Jul 2010 | 292,772 | 293,985 |
| Aug 2010 | 290,646 | 292,475 |
| Sep 2010 | 290,093 | 292,053 |
| Oct 2010 | 286,131 | 288,960 |
| Nov 2010 | 282,290 | 285,854 |
| Dec 2010 | 285,353 | 288,605 |
| Jan 2011 | 287,983 | 284,949 |
| Feb 2011 | 285,227 | 283,391 |
| Mar 2011 | 287,092 | 285,490 |
| Apr 2011 | 293,993 | 292,239 |
| May 2011 | 284,722 | 285,334 |
| Jun 2011 | 285,906 | 286,644 |
| Jul 2011 | 295,843 | 296,452 |
| Aug 2011 | 294,903 | 295,902 |
| Sep 2011 | 295,358 | 296,294 |
| Oct 2011 | 292,267 | 293,917 |
| Nov 2011 | 291,036 | 292,939 |
| Dec 2011 | 292,284 | 294,213 |
| Jan 2012 | 294,360 | 289,997 |
| Feb 2012 | 292,381 | 289,077 |
| Mar 2012 | 290,379 | 288,105 |
| Apr 2012 | 299,065 | 296,273 |
| May 2012 | 304,081 | 300,854 |
| Jun 2012 | 306,823 | 303,420 |
| Jul 2012 | 308,962 | 306,969 |
| Aug 2012 | 310,043 | 308,055 |
| Sep 2012 | 308,469 | 306,816 |
| Oct 2012 | 310,281 | 308,409 |
| Nov 2012 | 308,540 | 307,034 |
| Dec 2012 | 313,744 | 311,494 |
| Jan 2013 | 311,364 | 303,399 |
| Feb 2013 | 313,550 | 305,821 |
| Mar 2013 | 312,289 | 305,496 |
| Apr 2013 | 320,921 | 313,594 |
| May 2013 | 322,324 | 315,294 |
| Jun 2013 | 324,518 | 317,419 |
| Jul 2013 | 332,988 | 326,066 |
| Aug 2013 | 335,743 | 328,483 |
| Sep 2013 | 340,494 | 332,298 |
| Oct 2013 | 340,045 | 332,077 |
| Nov 2013 | 343,749 | 335,063 |
| Dec 2013 | 352,028 | 341,901 |
| Jan 2014 | 355,830 | 338,061 |
| Feb 2014 | 357,876 | 340,408 |
| Mar 2014 | 361,400 | 343,930 |
| Apr 2014 | 375,337 | 356,133 |
| May 2014 | 382,705 | 362,545 |
| Jun 2014 | 387,182 | 366,454 |
| Jul 2014 | 398,737 | 377,571 |
| Aug 2014 | 404,754 | 382,498 |
| Sep 2014 | 403,670 | 381,623 |
| Oct 2014 | 402,300 | 380,714 |
| Nov 2014 | 400,803 | 379,553 |
| Dec 2014 | 402,898 | 381,427 |
| Jan 2015 | 402,847 | 373,797 |
| Feb 2015 | 404,773 | 376,094 |
| Mar 2015 | 404,706 | 376,900 |
| Apr 2015 | 410,445 | 382,782 |
| May 2015 | 415,817 | 387,639 |
| Jun 2015 | 419,474 | 390,905 |
| Jul 2015 | 431,644 | 402,500 |
| Aug 2015 | 436,152 | 406,235 |
| Sep 2015 | 439,729 | 408,894 |
| Oct 2015 | 440,484 | 409,622 |
| Nov 2015 | 445,485 | 413,404 |
| Dec 2015 | 450,053 | 417,140 |
| Jan 2016 | 457,466 | 414,341 |
| Feb 2016 | 457,759 | 415,479 |
| Mar 2016 | 464,647 | 421,559 |
| Apr 2016 | 461,068 | 420,551 |
| May 2016 | 467,485 | 426,173 |
| Jun 2016 | 468,120 | 427,171 |
| Jul 2016 | 475,530 | 435,238 |
| Aug 2016 | 471,957 | 432,914 |
| Sep 2016 | 471,767 | 432,727 |
| Oct 2016 | 471,008 | 432,331 |
| Nov 2016 | 470,854 | 432,237 |
| Dec 2016 | 472,374 | 433,691 |
| Jan 2017 | 475,619 | 427,494 |
| Feb 2017 | 476,717 | 429,245 |
| Mar 2017 | 475,442 | 429,394 |
| Apr 2017 | 479,790 | 434,213 |
| May 2017 | 480,902 | 435,958 |
| Jun 2017 | 480,152 | 435,954 |
| Jul 2017 | 488,527 | 444,754 |
| Aug 2017 | 487,085 | 444,016 |
| Sep 2017 | 483,833 | 441,581 |
| Oct 2017 | 481,762 | 440,227 |
| Nov 2017 | 476,290 | 436,230 |
| Dec 2017 | 476,848 | 436,977 |
| Jan 2018 | 479,772 | 430,481 |
| Feb 2018 | 477,860 | 430,068 |
| Mar 2018 | 472,327 | 427,143 |
| Apr 2018 | 477,106 | 432,270 |
| May 2018 | 478,480 | 434,201 |
| Jun 2018 | 480,165 | 435,964 |
| Jul 2018 | 484,906 | 442,117 |
| Aug 2018 | 480,374 | 439,121 |
| Sep 2018 | 476,397 | 436,152 |
| Oct 2018 | 481,412 | 439,971 |
| Nov 2018 | 473,872 | 434,458 |
| Dec 2018 | 472,907 | 434,088 |
| Jan 2019 | 469,186 | 422,882 |
| Feb 2019 | 459,800 | 417,065 |
Source: HM Land Registry (UK), Better Dwelling.
There’s a similar setup brewing in Canada, politicians are just a little less willing to look into it. Transparency International Canada found 50,000+ Greater Toronto homes bought by companies without known beneficial ownership. Even worse, $20 billion of the funds used were not subject to any anti-money laundering checks. In Vancouver, local politicians are still claiming money laundering is over exaggerated. Meanwhile, in European Parliament, Vancouver is literally being used as an example of opaque ownership distorting home prices.
Money Laundering Through Commodities Is Old News, The Velocity Is New
Laundering money through real estate is far from new, but the velocity and volume is. Traditionally, launderers would buy, hold, and sometimes even rent the places out. The lack of scrutiny in real estate transactions, has always made it a prime landing spot. Every city has a few well known families connected to local mobs, that just happen to be in real estate. The impact to home prices are minimal when the volume is low and slow.
Treating real estate like a global commodity market makes it fast and high volume. The real estate industry in Canada encourages foreign capital. In fact, Canadian banks openly helped clients with “placement,” obfuscating deposit trails. The faster you can place, the faster prices rise, and the more they welcome foreign capital – the easier the wash.
This has always been an issue stock markets have had to deal with. Equity is issued, artificial volume inflates prices, and launderers liquidate to unsuspecting victims. Equity markets have increased ownership transparency on larger exchanges, making it more difficult. However, it’s still common, especially on European and Asian stock exchanges. Treating real estate like a stock market encourages the same type of laundering, without the transparency.
Fun fact: The now defunct Vancouver Stock Exchange was popular with money launderers. It was so popular, Forbes called Vancouver the “Scam Capital of The World” in 1989. The Coordinated Law Enforcement Unit in British Columbia warned the government of organized crime on the exchange as early as 1974. Those warnings were largely ignored. Are you also sensing a pattern here?
Money laundering is not the sole reason for much higher prices, but it fans the flames. Low interest rates and easy lending allow regular families to provide liquidity. If a launderer can’t get clean cash, they don’t transact. There’s no appeal without house horny buyers overbidding comps, or rapidly flipping.
Money laundering investors however, can influence the direction of the market. A real estate market is only as good as its last comp, set by the marginal buyer. If that marginal buyer was laundering money, they have motivation to overpay. Regular households buying into this, provide comp validation, and liquidity. Most households never consider where their liquidity is going to come from.
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