Startup Uses Data Analytics, Cuts Residential Rental Defaults in Half

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By using behavioural, demographic and social analysis, Zora gives landlords a more reliable way of screening prospective tenants

Each year landlords lose over $31 Billion dollars in unpaid rent, repairs and eviction fees that result from bad tenants. We have analyzed millions of data points to identify traits of good, longĀ­term tenants"

Zora, a Halifax based company with offices in Las Vegas, announced today the release of their software which helps landlords reduce default rates by nearly 50 per cent. By analyzing behavioral, demographic and social patterns for each rental applicant, Zora predicts with great accuracy who is likely to be a good, long­-term tenant.

"Each year landlords lose over $31 Billion dollars in unpaid rent, repairs and eviction fees that result from bad tenants. We have analyzed millions of data points to identify traits of good, long-­term tenants and are now putting that data into the hands of landlords to protect them from such losses," says Zora co-founder and CEO Milan Vrekic.

Zora positions their tenant screening algorithm, known as the Z Score, as a direct alternative to (FICO) credit scores.

"Credit scores indicate who is financeable, but not who is reliable. We have conclusive evidence that landlords who rely solely on in­-person interviews to screen tenants did as well as those who relied on credit scores," explains Colin White, co-founder and CTO.

The company looks at over 80 risk factors to give landlords a Z Score ­ a numerical tenant quality score from 1 to 100 for each rental applicant.

Once a landlord finds a great tenant, Zora helps them keep that tenant by giving them tools to streamline the most tedious tasks involved with renting, such as lease signing, maintenance and rent collection.

Landlords can sign up to screen and manage tenants using Zora at http://www.zora.io.

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Milan Vrekic
Zora
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