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  • Insurance
  • Innovation
  • United Kingdom

On-Demand Insurance by Trov Takes Leave from BtoC

FACTS

  • The British InsurTech market witnesses a strategic shift as Trov –industry pioneer in on-demand insurance market for goods– announces they are taking leave from the BtoC sector.
  • This strategic choice only applies to the UK for now. Their existing customers will still enjoy insurance coverage up until October the 1st, when the service will definitely be disabled.
  • Trov didn’t yet specify if likewise changes were planned on their other markets: Australia (their home country) and the US.
  • This decision is consistent with a strategic shift announced in 2018 and based on several partnerships with retailers, banks, insurance companies, car makers and mobility players.
  • This strategy would lead Trov’s activity to evolve from selling alternative on-demand insurance services to becoming a service provider with “Powered by Trov”.

CHALLENGES

  • Making their model profitable. This strategic shift is meant to ensure profit. A low cost, flexible model isn’t easy to monetise, while partnerships with large scale groups already allowed them to profit from making their infrastructure available.
  • Insisting on mobility. As the mobility sector is witnessing in-depth changes and consumption models in the car industry have been evolving, mobility players became their preferred targets within the frame of a partnerships-based strategy.

MARKET PERSPECTIVE

  • Trov recently confirmed they would be focusing on the BtoB market. They signed a partnership with PSA for their Free2move mobility service.
  • Just like other InsurTechs and FinTechs, Trov makes a pragmatic choice and favours partnerships or white level service provision for their distribution model.
  • Trov’s strategy also highlights a new trend: Open Banking first emerged and set the ground for Open Insurance. This evolution directly relates to the launch of distribution platforms for financial products, which caused much upheaval on associated business models.