Digital Insurance Agenda

twingz: Propelling the paradigm shift from reactive to predictive behaviours – this time for water

Written by Roger Peverelli and Reggy de Feniks - Founders The DIA Community on Jul 15, 2019

twingz introduces insurers, property owners and asset managers to a predictive damage control and prevention solution. Through predictive analytics, twingz provides a service that reduces operational costs related to maintenance and damages caused by water and fire and thus has a positive impact on the value of a property. twingz is currently expanding its businesses in Germany with FUNK, VKB and Generali as insurance clients and several real estate companies.

Whereas insurers usually provide financial power AFTER a damage occurs in a reactive manner, twingz provides an opportunity to shift from a reactive driven management approach to a predictive damage and preventive control solution. Twingz detects anomalies in water and energy consumption through artificial intelligence (AI) and machine learning.
Consumption patterns are learned, and deviations are recognized by firstly breaking up large data sets gathered from electricity and water meters and secondly analyzing and classifying these data sets. The insights lead to predictions of future incidents and preventing an increasing threat through a water or fire damage.  The data streams that the twingz damage prevention SaaS services analyze can be taken from existing meter infrastructure or building information management systems of Siemens Mindsphere, Schneider electric, Honeywell and similar.

The Vienna-based startup supports property management in shifting from a “reactive-” to “predictive management” and a far more efficient solution that is also highly integrated with claims automation. The frequency and cost of damages are increasing at an exponential rate; therefore, they partner with claims-automation solutions from Omni:us to help the insurance industry manage that burden.

Key-benefits:
The predictive monitoring AI is supporting following new cases:

  • more profitable growth in commercial real estate, residential and multifamily homes
  • new insurance services allowing for predictive and sustainable services to consumers and property owners
  • new digital insurance products for a new greenfield market in bancassurance
  • support a turnaround from a loss-making business by reducing accruals, operating costs and increase the profitability of owned property
  • Speed: a typical pilot project can be up and running in just a few weeks and provide predictive analytics results from the second week of operation. 

How it works

Why we selected twingz for DIA Amsterdam
twingz allows for a paradigm shift from reactive to predictive and thus a change in behavior towards incidents and a reduction in cost and time spent on damages. twingz damage prevention solutions help open a channel for continuous customer engagement, contribute to improved risk analysis & underwriting, a swifter more efficient claims management process and reducing payouts.

While at DIA Munich 2018 twingz focused on the fire damage prevention possibilities, at the DIA Amsterdam 2019, Werner Weihs-Sedivy, CEO & Co-Founder and Gareth Lewis from Sales & Marketing introduced twingz’s water leakage detection solution. The combination of both water flow data and energy flow data from meter readers provide a breakthrough in preventive management and predictive solutions. With minimal or no technical adaptations needed for the property infrastructure leaks creating only several drops (microleaks) to high-flow leaks like pipe bursts are easily detected and anomalies flagged.

Who is twingz?
twingz was originally founded by Werner Weihs-Sedivy, CEO and Chris H. Leeb Strategic Expert in December 2010. Back in the days the original idea of twingz was to communicate with devices and other things and to be reachable in networks. Shortly thereafter in 2011 Dietmar Millinger (Senior Architect & ML expert) joined the team and completed the founder’s group. In 2016, twingz opened a second operational office in Amsterdam, the Netherlands.

Since 2010, their focus has lied in machine learning and artificial intelligence based predictive analytics services and solutions. twingz can read data from various electricity, water, heat flow and other meters, classify it per type of appliance, analyze consumption, and present insightful reports to customers, consumers and insurance companies. Insights generated in real time can be integrated into their platforms such as Siemens Mindsphere and Niko group. Platforms provide an integrated view of property management and show anomalies in consumption patterns or leakages, thus supportive to fire and water damage prevention, enabling predictive maintenance and cost savings.

twingz has launched successful game changing solutions in fields of quick pattern recognition and anomaly detection. The first successful pilots started in 2016 and early 2017 in Holland with Delta Lloyd (now Nationale Nederlanden) on detecting household appliances and their consumption. Consumers can proactively avoid potential incidents through an interactive alerting system.
Water & Fire damage prevention solution with KBC Insurance Belgium for residential real estate
Predictive maintenance for industrial production for residual current and real power monitors
Several pilots for water damage prevention for existing and new commercial real estate and multifamily homes. Non-intrusive monitoring of activity of elderly people living alone at home as part of an AAL (Ambient Assisted Living) project with one of the largest relief organizations in Germany and an energy provider.

‘Almost 10 years ago we wanted to enable devices to communicate and be transparent. We now do so by using methods which allow early detection of anomalies in any type of flow data. And we are taking it further with the development of AI enabled algorithms that allow companies to help clients to prevent water and fire damage whilst helping to consume resources most sustainably.’ Werner Weihs-Sedivy co-founder & CEO twingz

https://www.twingz.com/

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