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Presentation about introductory Python delivered in front of CSSU.
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Insurance IoT is a social good! Because: 🔵 Expected losses can be reduced structured programs with both real-time mitigation actions to solve a specific situation, and behavioral change mechanisms to promote safer behaviors (both in personal and commercial lines) 🔵 Rate can be matched to risks better: - Smaller and more accurate pricing clusters allow a large part of profiles to receive a lower rate - Even with the ability to price the individual probability of loss (cluster of one) the insurance foundation isn’t canceled (The risk of each policy will contribute to the expected losses of the portfolio; The premiums paid by many lucky policyholders will be used to pay the claims of the few unlucky policyholders who had an accident in a period of coverage) 🔵 IoT data can be used to increase the effectiveness and efficiency of the claim process, so improving the combined ratio ceteris paribus ⏩ Large part of the policyholders will pay less (and portfolios currently difficult to insure will become more insurable) Insurance IoT (and telematics) is not about providing a discount Insurance IoT (and telematics) is about creating economic value using the data and sharing part of this value with policyholders (and agents & brokers) An integrated holistic adoption of the IoT paradigm is a game changer for your insurance business and a social good: ◾ it allows to improve the availability and affordability of insurance coverages ◾while allowing the sector to write a profitable business Below you can enjoy a selection of best practices in both personal and commercial lines - written with some of the IoT Insurance Observatory members - that have already started to obtain results from their IoT business transformation journeys
Insurers' journeys to build a mastery in the IoT usage
Insurers' journeys to build a mastery in the IoT usage
Matteo Carbone
Robert Gifford; JOUR 414 Capstone
Famous Olympic Siblings from the 21st Century
Famous Olympic Siblings from the 21st Century
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I celebrated 7 decades of help from others with a short talk regarding my gratitude.
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Regression analysis Simple Linear Regression Multiple Linear Regression
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Monte Carlo simulation : Simulation using MCSM
Cracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptx
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Value Proposition canvas- Customer needs and pains
Value Proposition canvas- Customer needs and pains
How to Get Started in Social Media for Art League City
How to Get Started in Social Media for Art League City
Insurers' journeys to build a mastery in the IoT usage
Insurers' journeys to build a mastery in the IoT usage
Famous Olympic Siblings from the 21st Century
Famous Olympic Siblings from the 21st Century
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A DAY IN THE LIFE OF A SALESMAN / WOMAN
A DAY IN THE LIFE OF A SALESMAN / WOMAN
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
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Regression analysis: Simple Linear Regression Multiple Linear Regression
Intro to Python
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Intro to Python
CSSU Nov/28/2007 By Georgi Petrov & Atanas Dyulgerov
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