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Please find below the judging results for your proposal.

Finalist Evaluation

Judges'' comments

The scope of opportunities and the potential for cascading programs if an when a scheme could really take root are strong features of this proposal. The lack of a clear anchor or starting point, with any actual potential partners (or testimonials from prospective insurance company partners and the government programs mentioned) is a serious challenge to have to address in the start-up phase. Budgeting is quite modest but is explained as due to reliance on virtual platforms, whereas scale of at least an initial outreach plan would have given a more solid grounding for the budget estimates; as it is the approach seems to be starting from scratch, knocking on virtual doors, and this may not be the best way to get traction with actual and very necessary implementation partners. The computation of impacts should be a strong point in favor of this proposal going forward. However some methodological questions were triggered; it would have been preferable to have a clearer explanation as to what the percentages actually relate to in terms of numbers of people/households and how the figures were arrived at.

Semi-Finalist Evaluation

Judges'' ratings


Judges'' comments

Dear authors,

Thank you very much for your proposal to our contest. Our judges have decided to advance your proposal to the Semi-Finalists round. For the revision phase, we would like to provide you with some feedback from the judges that should help you improve your proposal and address open questions for the finalist round.

Judges found your proposal to link risk data and analytics, risk reduction measures, insurance solutions, digital technology and gamification in a fresh and compelling way. They found the novel linkage of incentivising risk management action through gaming with potential for reducing insurance premiums intriguing and to have 'game-changer' potential to transform the way that policyholders engage with insurance. The potential for applying machine learning to link compliance with risk reduction 'conditions' informed by real time forecasting, and to further incentivize by bridging individual home and/or business owner policies with municipal level insurance holds tremendous potential for revolutionizing insurance. Many additional dimensions are suggested; this is a tip of the iceberg type project which makes 'learning to swim' fun by simulating the sinking conditions through a game-enabled VR/AR interface and rewards winning with the potential for driving down risk that is dynamically linked to driving down insurance costs. Another exciting dimension is the way the proposed scheme could also incentivize overcoming free-rider tendencies by making the impact of other players' risk reduction actions relevant to your (or your municipal) insurance cost/premium.

Judges however saw that the links to social protection schemes were not evident and that this area of the proposal could be strengthened and saw potential for integrating such schemes into this the proposal.

The judges agreed that the potential for scale and replication is promising. One judge saw that deploying the pilot in Chennai would be very interesting and that even if not fully functional at that stage, uptake and development potential is likely to be exponential.

Please note also that, as semi-finalists to the contest, you are requested to provide a detailed budget for the spending of the seed funding (40,000 euros) that the team winning the Judge’s choice award will be granted for the implementation of their proposal.

Good luck and all the best,
The contest fellows

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