Presentatie Willis Towers Watson

Solidariteit en de Technologische Revolutie Wichert Hoekert Peter Hoogveld

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Introductie

Solidariteit: (n)iets nieuws….

Verzekeraarsperspectief

Pensioenfondsperspectief

Solidariteit

Vragenlijst en conclusies

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?

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Substantief Warm Organisch Kans

Formeel Koud Mechanisch Risico

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Behoefte Maatschappij

Politiek

Individu

Solidariteit Verzekeraar

Pensioenfonds

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Solidariteitsschuif Technologische ontwikkelingen

Terugtredende overheid Risicodeling

Herverdeling

Premie Privaat Eigenbelang

Belasting Publiek Altruïsme Onverzekerbare?

Verzekerbare

Verzekeraar

Pensioenfonds

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Ga naar www.menti.com en gebruik de code 58 76 05

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Behoefte Maatschappij

Politiek

Individu

Solidariteit Verzekeraar

Pensioenfonds

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Behoefte Maatschappij

Politiek

Individu

Solidariteit Verzekeraar

Pensioenfonds

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Verzekeraarsperspectief

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Hoe het begon

Ontwikkeling van statistische technieken vlucht na introductie computers

Doen wat nodig en nuttig was

Ken de klant

Toenemende Boeren, Coöperaties concurrentie en VOC Disruptie!

Consumptie, meer Data Johan de Witt en behoefte aan Edmund Halley verzekeringen maakte al gebruik analyse Portefeuille management willistowerswatson.com © 2018 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only.

van “big data” in hun tijd!

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De Data & Analyse “ijsberg” Evolutie of cyclisch? Innovatie en normalisering in the analytische benadering “Before Tooling” § Pre-­1996

Mature GLM § 1997 to 2014?

Analytics

Early ML/Current § 2015 to 2017?

Analytics

Analytics

Data

Data

Data

§ GLIM 3.5/4.0 § § Data not organized § for analytics § “Coding” type skills §

Analytics

Mature ML/Next § 2018 onwards?

Analytics Data

Data

§ Many and varied § Slick GLM/ML tool Slick GLM tool interface Data organized for tools § (New) data not yet § Data organized for (GLM) analytics ML analytics organized for ML Speed of thought analytics § Speed of thought analytics analytics § “Coding” type skills

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Data en digitale disruptie in de verzekeringssector Wat voedt het en wat is de impact?

Voeding voor verandering “Advanced analytics”

Impact op de sector Investeringen

(Big) Data

§ Interne analytische teams en technologie § Start-­ups § Digitale transformatie

Technologie

Samenwerking

Data Science

§ IoT providers § Data providers

Dichter bij de klant Hype en ruis Start-­ups

§ Direct / multi-­channel contact § Affinity relaties § App ontwikkeling

Disruptie!

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Opkomende concepten in “advanced analytics” Predictive analytics

Predictive analytics is the branch of advanced analytics which is used to make predictions about future unknown events.

It uses many techniques from data mining, statistics, modelling, machine learning and artificial intelligence. Increasingly, machine learning techniques are used to underpin prescriptive analytics.

Fraud detection

Individual claims reserving

Cross-­ selling and targeting

Underwriting

Claims payments

This concept is not new to insurance but some of the data underpinning predictive models and some of the techniques being used to build predictive models arguably is.

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Opkomende concepten in “advanced analytics” Machine learning

Machine learning is a subfield of computer science and artificial intelligence which deals with building systems that can learn from data, instead of explicitly programmed instructions.

Random forests

Neural networks

GBMs Logistic regression

K means clustering

Machine learning is a critical component of the predictive analytics process in a world that is increasingly (dirty) data rich.

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Opkomende concepten in “advanced analytics” Big data

Big Data refers to both large volumes of data with high level of complexity and the analytical methods applied to them which require more advanced techniques and technologies in order to derive meaningful information and insights.

UBI & Telematics

Wearables Social media

IoT Home Devices

Insurers with most data tend to be multi-­product (particularly composites), have a strong on-­line/app presence, have a significant direct channel, partner or offer products that utilise IoT and telematics devices.

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Opkomende concepten in “advanced analytics” Big data -­ potentiële impact op onverzekerbaarheid .

*Research of the Institute of Actuaries of Australia

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Impact van advanced analytics op verzekeren Verzekeraars verbeteren hun mogelijkheden om meer geïnformeerde beslissingen te maken binnen de gehele waardeketen Marketing and Distribution

Product development (UBI)

Underwriting and risk management

Customer management

Pricing

Retention segmentation and programme design

Agent/Broker performance evaluation

60

3500

40

3000

20

2500

0

Claims management

Asset management

Fraud detection

2000

-­20

1500

-­40 -­60

1000

-­80

500

-­100

0 Low rating factor

High rating factor exposure excess res

P&C to Life cross-­selling

Web-­scraping and feature design in commercial lines

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Topic modelling and large loss modelling

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Wat is Blockchain: new kid on the block Gartner Hype Cycle for Emerging Technologies 2015

Gartner Hype Cycle for Emerging Technologies 2016

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Wat is Blockchain: bijna bij de “trog” van de desillusie

Gartner Hype Cycle for Emerging Technologies 2017

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Wat is Blockchain?

It is a shared distributed (digital) ledger technology Decentralized

Centralized

Distributed willistowerswatson.com © 2018 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only.

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Bewijs van impact op de verzekeringsindustrie – groeiende bedreiging van insurtech P2P

Healthcare

UBI/Auto

Reinsurance

Product insurance

Spot Insurance Marketplace & online consumer platforms Backend

Accelerators

Sharing Economy

IoT Data, Software & Analytics

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Impact technologie op solidariteit: evolutie of revolutie

Technische mogelijkheden Van alle tijden

Correlaties in data Bijjsturen vanuit politiek klimaat

De producten en het speelveld zal wijzigen

Solidariteit onderwerp van debat

Black De box evolutie Marktwerking gaat wat Verzekeren sneller? doel op zich

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Pensioenfondsperspectief

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Risicodeling

Herverdeling Beoogde herverdeling Geaccepteerde herverdeling Perverse herverdeling

Verzekeraar

Pensioenfonds

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Resterende levensverwachting

Verzekeraar

Pensioenfonds

organisatie

Laagste inkomenssixtiel t.o.v. geen ervaringssterfte

Hoogste inkomenssixtiel t.o.v. geen ervaringssterfte

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Verzekeraar

Pensioenfonds

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Conclusie en vragen

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Solidariteit is en blijft van alle tijden Menselijke natuur en rationeel belang voor verzekeraars

Invloed van technologie op solidariteit bij verzekeraars lijkt van evolutionaire aard Invloed van technologie op solidariteit bij pensioenen zou van revolutionaire aard kunnen zijn Zelfbeschikking over eigen informatie is van cruciaal belang Een modern actuaris moet zich ook kunnen profileren op gebied van technologie en ethiek willistowerswatson.com © 2018 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only.

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Resultaten survey

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Dank u!

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