Home Exchange

Targeting 100% on Home Exchange Safety

home exchange safety

I’m working on some updated posts about travel safety. And I just read this post about home exchange safety from Emmanuel Arnaud, the CEO of the HomeExchange network. I applaud HE for releasing data on safety. The sharing economy benefits from consumer access to data. The recent Uber report on safety is another move in the right direction.

HomeExchange is holding up member/home verification as a cornerstone of their safety policy. And I think this is a good move in general. Though the value of fake listings seems limited in a home exchange platform. They can’t do a simultaneous swap because the fake listing owner would easily be tracked down in the other person’s home. And offering a fake home for a points stay will just lead to the account being shut down when the sad guest shows up. Either way, no benefit to the fake lister. Nonetheless, I think identity verification probably prevents some scammers from trying to use the platform.

Here’s the HomeExchange press release on their verification statistics:

Since our launch in 2011, we have prioritized the verification of every home/member we feature. Our verification process includes confirming identity and home address with a government issued ID and a utility bill. 55% of our subscribers based in the US are verified, and 64% of our global subscribers are verified. We strive to increase these numbers and pave the way for other companies in the industry. Our goal is to have 100% of our subscribers verified by April, 2020.

The goal of 100% verification by April 2020 seems quite ambitious. I look forward to seeing the numbers in May.

As for numbers on safety, here’s what HomeExchange reports:

Hosts who choose any peer-to-peer accommodation platform should know their risk upfront. We are happy to share that in 2019 99.9% of exchanges occurred without any cases submitted by the host. Out of the 0.1% of the exchanges where the host did submit a case, 66% were accidental damage for an average cost of $310. Other types of cases include malicious damage, theft, and cleaning charges. In the last 12 months, the highest claim cost by a host was below $6,000.

That’s consistent with information GuestToGuest shared with me five years ago when I wrote about home exchange insurance. Of course this means that in 0.1% of home exchanges the host has a problem that merits opening a case. That’s a very low percentage. But that still amounts to about 2000 sad hosts in 2019.*

Keep in mind that the recent Uber safety report claimed 99.9% of rides are incident-free. But headlines covering this report focused on the 3000+ cases of sexual assault in the past year. 0.1% is not zero.

Is a zero incident rate expectation reasonable? Well that is our expectation for airline safety. The accident rate for major jets in 2018 was 1 in 5.4 million flights, which is actually a percentage so close to zero that it’s not worth typing out. But to be fair, when an airplane crashes people usually die. So the standards should be super high for aviation. I think it’s reasonable to have similarly high standards for sexual assault in ride hailing services.

With home exchanges we’re mostly talking about accidental damage of property. Not really a big deal in the grand scheme of things. In this case I think 0.1% is acceptable. Even with malicious damage or theft I’m ok with that low rate. It’s only property. And HomeExchange has an insurance system that should cover these costs. It’s only in cases of harm to people that I think a zero incident rate needs to be the goal.

We don’t yet have data from HomeExchange on how many cases were filed by guests. Or how many of these cases are harm or risk to people rather than property. I hope HomeExchange will release this data. Their transparency will encourage sharing and discussion of this information across the travel industry.

* HomeExchange couldn’t share data on total number of swaps in 2019 so I came up with this number by taking their report of exchange nights per month (which counts each person in a swap separately), dividing that by 4 (a high estimate for number of people in a swap on average), and dividing the result by 4 (a guess at average number of nights per swap). Rounding this up I came up with about 200,000 swaps over 12 months.

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