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    Home»Real Estate»StreetWire partners with MetroList on home value insurance product
    Real Estate

    StreetWire partners with MetroList on home value insurance product

    adminBy adminSeptember 26, 2024No Comments0 Views
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    Multiple listing services (MLSs) have a wealth of data, and one technology company thinks it has found an innovative way to use it.

    Real estate data company StreetWire has partnered with Northern California MLS MetroList to produce an insurance product called Home Value Lock. It’s designed to protect homeowners from declining home values.

    The coverage is good for three years after the closing date on a home purchase, and the insurance covers up to 10% of the original purchase price. StreetWire believes Home Value Lock will minimize the risk of losing money on a home purchase in situations where a family has to move unexpectedly.

    “Home Value Lock is an important step toward much-needed innovation in the real estate sector after the wave of funding and regulatory changes that have followed the recent National Association of Realtors litigation,” MetroList CEO Dave Howe said in a statement. “We believe that MLS data is consistently underutilized in the financial services sector, and the launch of Home Value Lock will prove its tremendous value proposition.

    The company provides an example of how the product works. Someone buys a house for $500,000 but then decides to sell due to a job relocation or an expanding family. If the value of the home fell by 10% after being purchased, the insurance claim would pay out $50,000, or 10% of the original sale price.

    To claim the payout, a homeowner would first need to sell the house. They must add the coverage within 30 days of buying the house. Home Value Lock is currently available only in California.

    “As a data modeling network, we have an acute understanding of the power and value of MLS data to better identify housing market patterns,” StreetWire CEO Oliver Tickner said in a statement. “Our goal is to re-benchmark the value of that dataset for financial services.”

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