CANADA: How A Little Money Laundering Can Have A Big Impact On Real Estate Prices


APRIL 24, 2019

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

QuarterCanadaCritical Values
1984 Q3-2.141-0.064
1984 Q4-2.0530.072
1985 Q1-2.0920.132
1985 Q2-2.1540.19
1985 Q3-2.1070.283
1985 Q4-2.1680.304
1986 Q1-2.170.348
1986 Q2-2.2420.394
1986 Q3-2.2740.405
1986 Q4-2.30.448
1987 Q1-2.2290.489
1987 Q2-2.1020.51
1987 Q3-2.1210.519
1987 Q4-2.2250.551
1988 Q1-2.3050.584
1988 Q2-1.9060.59
1988 Q3-1.740.61
1988 Q4-1.7760.621
1989 Q1-1.4080.665
1989 Q2-0.80.699
1989 Q3-1.4830.712
1989 Q4-1.2040.716
1990 Q1-0.9460.739
1990 Q2-0.8520.762
1990 Q3-1.4250.819
1990 Q4-1.5380.836
1991 Q1-1.5430.855
1991 Q2-1.3870.871
1991 Q3-1.140.89
1991 Q4-1.1080.899
1992 Q1-1.2240.899
1992 Q2-1.1510.901
1992 Q3-1.2160.929
1992 Q4-1.2340.942
1993 Q1-1.2330.954
1993 Q2-1.2710.96
1993 Q3-1.2690.971
1993 Q4-1.3140.971
1994 Q1-1.3290.974
1994 Q2-1.3270.981
1994 Q3-1.3520.981
1994 Q4-1.3610.991
1995 Q1-1.3981.015
1995 Q2-1.4421.018
1995 Q3-1.4591.025
1995 Q4-1.4751.03
1996 Q1-1.4891.03
1996 Q2-1.51.059
1996 Q3-1.5111.066
1996 Q4-1.4261.071
1997 Q1-1.5111.071
1997 Q2-1.5591.076
1997 Q3-1.5841.076
1997 Q4-1.5691.076
1998 Q1-1.6021.079
1998 Q2-1.6081.084
1998 Q3-1.6211.087
1998 Q4-1.6261.092
1999 Q1-1.6681.099
1999 Q2-1.671.099
1999 Q3-1.6981.107
1999 Q4-1.6831.111
2000 Q1-1.7011.116
2000 Q2-1.5191.124
2000 Q3-1.5341.133
2000 Q4-1.5831.153
2001 Q1-1.4971.153
2001 Q2-1.5291.157
2001 Q3-1.4391.157
2001 Q4-1.0991.16
2002 Q1-0.1961.16
2002 Q2-0.1641.16
2002 Q30.0711.16
2002 Q40.8831.163
2003 Q11.1911.164
2003 Q21.6961.164
2003 Q32.0611.164
2003 Q41.8511.17
2004 Q12.4041.17
2004 Q23.0561.17
2004 Q32.7421.189
2004 Q42.141.193
2005 Q12.6151.193
2005 Q22.9911.193
2005 Q32.8291.205
2005 Q42.8971.206
2006 Q13.5761.206
2006 Q24.3111.206
2006 Q34.3181.206
2006 Q43.661.206
2007 Q13.7861.209
2007 Q24.7811.222
2007 Q34.3591.222
2007 Q42.9511.222
2008 Q12.8981.222
2008 Q22.551.222
2008 Q30.9761.222
2008 Q40.3031.226
2009 Q1-0.0351.228
2009 Q20.6121.23
2009 Q30.8671.23
2009 Q40.8231.23
2010 Q11.1291.239
2010 Q21.1661.239
2010 Q30.6441.239
2010 Q40.4511.239
2011 Q10.7841.239
2011 Q21.0091.24
2011 Q30.8571.243
2011 Q40.6491.257
2012 Q10.9221.268
2012 Q21.2011.268
2012 Q30.931.271
2012 Q40.6941.271
2013 Q10.7831.271
2013 Q21.1311.272
2013 Q30.9721.272
2013 Q40.9431.272
2014 Q11.0571.272
2014 Q21.3041.272
2014 Q31.1681.272
2014 Q41.0971.275
2015 Q11.3341.28
2015 Q21.61.28
2015 Q31.5171.28
2015 Q41.5311.28
2016 Q11.8771.28
2016 Q22.4681.28
2016 Q32.451.28
2016 Q42.2081.28
2017 Q12.9621.28
2017 Q23.3061.28
2017 Q32.2111.286
2017 Q41.7081.286
2018 Q11.8261.286
2018 Q21.9221.286
2018 Q31.4881.286

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.

How A Little Money Laundering Can Have A Big Impact On Real Estate Prices - Nav Sarao

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

PeriodAvg. priceEst Avg. w/o money laundering
Jan 2008298,596292,408
Feb 2008295,700290,716
Mar 2008293,605289,580
Apr 2008294,346291,238
May 2008295,163292,676
Jun 2008290,100289,272
Jul 2008290,261291,348
Aug 2008281,721284,907
Sep 2008276,487280,872
Oct 2008266,999273,311
Nov 2008258,647266,447
Dec 2008253,881262,704
Jan 2009253,093256,760
Feb 2009249,847254,652
Mar 2009247,264253,015
Apr 2009245,351252,456
May 2009249,991256,843
Jun 2009253,596260,152
Jul 2009259,793266,882
Aug 2009262,076269,014
Sep 2009267,501273,570
Oct 2009268,780274,769
Nov 2009266,837273,197
Dec 2009270,118276,145
Jan 2010279,724278,374
Feb 2010278,753278,221
Mar 2010280,472280,200
Apr 2010281,981282,608
May 2010281,762282,956
Jun 2010284,541285,548
Jul 2010292,772293,985
Aug 2010290,646292,475
Sep 2010290,093292,053
Oct 2010286,131288,960
Nov 2010282,290285,854
Dec 2010285,353288,605
Jan 2011287,983284,949
Feb 2011285,227283,391
Mar 2011287,092285,490
Apr 2011293,993292,239
May 2011284,722285,334
Jun 2011285,906286,644
Jul 2011295,843296,452
Aug 2011294,903295,902
Sep 2011295,358296,294
Oct 2011292,267293,917
Nov 2011291,036292,939
Dec 2011292,284294,213
Jan 2012294,360289,997
Feb 2012292,381289,077
Mar 2012290,379288,105
Apr 2012299,065296,273
May 2012304,081300,854
Jun 2012306,823303,420
Jul 2012308,962306,969
Aug 2012310,043308,055
Sep 2012308,469306,816
Oct 2012310,281308,409
Nov 2012308,540307,034
Dec 2012313,744311,494
Jan 2013311,364303,399
Feb 2013313,550305,821
Mar 2013312,289305,496
Apr 2013320,921313,594
May 2013322,324315,294
Jun 2013324,518317,419
Jul 2013332,988326,066
Aug 2013335,743328,483
Sep 2013340,494332,298
Oct 2013340,045332,077
Nov 2013343,749335,063
Dec 2013352,028341,901
Jan 2014355,830338,061
Feb 2014357,876340,408
Mar 2014361,400343,930
Apr 2014375,337356,133
May 2014382,705362,545
Jun 2014387,182366,454
Jul 2014398,737377,571
Aug 2014404,754382,498
Sep 2014403,670381,623
Oct 2014402,300380,714
Nov 2014400,803379,553
Dec 2014402,898381,427
Jan 2015402,847373,797
Feb 2015404,773376,094
Mar 2015404,706376,900
Apr 2015410,445382,782
May 2015415,817387,639
Jun 2015419,474390,905
Jul 2015431,644402,500
Aug 2015436,152406,235
Sep 2015439,729408,894
Oct 2015440,484409,622
Nov 2015445,485413,404
Dec 2015450,053417,140
Jan 2016457,466414,341
Feb 2016457,759415,479
Mar 2016464,647421,559
Apr 2016461,068420,551
May 2016467,485426,173
Jun 2016468,120427,171
Jul 2016475,530435,238
Aug 2016471,957432,914
Sep 2016471,767432,727
Oct 2016471,008432,331
Nov 2016470,854432,237
Dec 2016472,374433,691
Jan 2017475,619427,494
Feb 2017476,717429,245
Mar 2017475,442429,394
Apr 2017479,790434,213
May 2017480,902435,958
Jun 2017480,152435,954
Jul 2017488,527444,754
Aug 2017487,085444,016
Sep 2017483,833441,581
Oct 2017481,762440,227
Nov 2017476,290436,230
Dec 2017476,848436,977
Jan 2018479,772430,481
Feb 2018477,860430,068
Mar 2018472,327427,143
Apr 2018477,106432,270
May 2018478,480434,201
Jun 2018480,165435,964
Jul 2018484,906442,117
Aug 2018480,374439,121
Sep 2018476,397436,152
Oct 2018481,412439,971
Nov 2018473,872434,458
Dec 2018472,907434,088
Jan 2019469,186422,882
Feb 2019459,800417,065

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.