Big image analytics for (Re-) insurer

BIG IMAGE ANALYTICS FOR (RE-) INSURER

FLAVIO TROLESE4QUANT | BIG IMAGE ANALYTICS

THURSDAY, APRIL 7 2016

https://ch.linkedin.com/in/flavio-trolese-836a2b6

https://ch.linkedin.com/in/flavio-trolese-836a2b6

http://4quant.com

http://4quant.com

4Quant | BIG IMAGE ANALYTICS

BIG DATA IMAGE ANALYSIS BIG IMAGE ANALYTICS

REMOTE SENSING POTENTIAL (RE-) INSURANCE CASES Q&A


[...] Data sets that are so large or complex that traditional data processing applications are inadequate.

Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying and information privacy.

BIG DATA

https://en.wikipedia.org/wiki/Big_data




BIG DATA

Optimize Funnel Conversion

Behavioral Analytics

Customer Segmentation

Predictive Support

Market Basket Analysis and Pricing OptimizationsPredict Security Threats

Fraud Detection


IMAGE ANALYSIS

Tools and technologies (for analysis of «small (image) data»)

(limited) services for «big (image) data»

https://cloud.google.com/vision/

http://visual-recognition-demo.mybluemix.net/

https://www.microsoft.com/cognitive-services/en-us/computer-vision-api


Linearly scalable, interactive, fault-tolerant big image data processing technology for two-, three- and four-dimensional image data.Processes tera- to petabytes of image and video data in near real-time and at low costs

+ IMAGE ANALYSIS+ BIG DATA

= BIG IMAGE ANALYTICS


We do image analytics on Big Data → BIG IMAGE ANALYTICS

Our mission is to help companies monetize their image and video content.

4QUANT


Problem«Analyze phenotyping and genetic linkage of cortical bone microstructure in the mouse»

Terabytes of image data

Analysis of image data takes years with existing (small data) image analysis tools

Solution«Use a Big Data Framework in combination with image analysis algorithms»

BIG IMAGE ANALYTICS PLATFORMLinearly scalable, interactive, fault-tolerant big image data processing technology for two-, three- and four-dimensional image data

Tera- to petabytes of image and video data

Near real-time processing

TECHNOLOGY

«High-throughput phenotyping and genetic linkage of cortical bone microstructure in the mouse»K. Mader, L. Donahue, R. Müller, M. Stampanoni; BMC Genomics 2015 16:493;

«Moving image analysis to the cloud: A case study with a genome-scale tomographic study»K. Mader, M. Stampanoni; AIP Conf. Proc. 1696, 020045 (2016)

http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-1617-y








http://dx.doi.org/10.1063/1.4937539

http://dx.doi.org/10.1063/1.4937539

http://dx.doi.org/10.1063/1.4937539

http://dx.doi.org/10.1063/1.4937539

http://dx.doi.org/10.1063/1.4937539

http://dx.doi.org/10.1063/1.4937539

http://dx.doi.org/10.1063/1.4937539

http://dx.doi.org/10.1063/1.4937539


2014 20162015

HISTORY

PhD Thesis

ETH Pioneer Fellowship

Talk at Spark Summit

ETH Lecturer Assignment

Invited Big Data Workshop

Werner-Meyer-Ilse Award

Databricks Partnership

IBM Partnership

Partnership

Partnership

COPD StudyNPC Study

2013


VeracityTested validated correctness

Fully traceability of all algorithms

VarietyFor two-, three- and four-dimensional image data

Supports / parallelizes existing single CPU algorithms (e.g. ImageJ, Matlab, R)

VelocityStream-based analysis in almost real-time

Ad-hoc queries

Throughput of > GB/s

VolumeLinearly scalable beyond gigavoxels and tera- / petabytes

Elastically scale to available resources

ValueDetection of anomalies, intelligent feature recognition, tracking of millions of features, smart segmentation, parameter sweeping, pattern recognition

BIG IMAGE ANALYTICS PLATFORM

VarietyFinds insights from complex, noisy, heterogeneous, longitudinal, and voluminous imaging data. Answer questions that were previously unanswered.


Flavio Trolese / CFOCorporate Finance

HR / Administration

Dr. Kevin Mader / CTOR&D

Product Development

Scientific Consulting

Joachim Hagger / CEOGeneral Management

Business Development

Fundraising

MANAGEMENT TEAMM.Sc. in Physics ETH

Co-founder and managing partner of Netcetera, an IT consulting company, 390 employees

BScIT at ZHAW

Co-Founder and managing partner of Panter AG, an IT consulting company, 40 employees; Co-Founder and managing partner of Colab Zurich / ImpactHub Zurich (> 350 Members)

PhD on “High-throughput, synchrotron based tomographic microscopy tools” at ETH/PSI

ETH Pioneer Fellowship, Lecturer in the X-ray microscopy group D-ITET ETH Zurich


Transportation Material screeningINDU

STRY

&

TECH

NO

LOGY

PathologyRadiology

Image intelligence

Pharma

Remote sensing Human swarms

Imaging CRO

GEO

IMAG

ING

MED

ICIN

E &

PH

ARM

A


13© SBB AG l Innocircle l SBB Innovation – 06.10.2015

EXAMPLESVideo-to-Text Change detections

Measurements Track monitoring

https://docs.google.com/document/d/1WnL0hVPM_R_mS6qYh3p7ix24C9bwuFSLVe071zeOzsc/edit

https://docs.google.com/presentation/d/1bIUl0zM4VH8NWuLSuk4nD_3UGLwOKCEMDC49Y2UMRNM/edit#slide=id.ge2a7a4df5_3_5

https://docs.google.com/presentation/d/1bIUl0zM4VH8NWuLSuk4nD_3UGLwOKCEMDC49Y2UMRNM/edit#slide=id.ge2a7a4df5_3_5

http://4quant.com/Railway-Check/


MEDIA


REMOTE SENSING

New, exciting sources of images with meter resolution, updated almost daily

225 GB / y 333 TB / y 333 TB / y 15 PB / y


REMOTE SENSING / BIAP

Meaningful Results

BIAP

Petabytes of satellite image data

e.g. flood risk calculations

4Quant’s BIAPVM VMVM VM

VM VMVM VM


Integrate Deep Learning Algorithms to automatically identify unknown, or changing regions in the image

INTEGRATION OF MACHINE INTELLIGENCE


Utilize high-temporal resolution and decades of archives...

… to see new insights in the data and extract quantitative results for building new models

HISTORICAL CHANGES IN SURFACE PATTERNS


Satellites produce lots of data. What can we do with it?

Data courtesy of Planet Labs

Location and size of water-features

Distance to nearestwater feature

Building locationIdentifyingHigh-Risk areas

TRANSFORM IMAGE DATA INTO MEANING QUANTITIES

http://4quant.com/Flood-Risk/






REAL-TIME DAMAGE ESTIMATION

Often after a major incident (hail storm, fire, flood), experts are required to assess the overall lost value. A timely and accurate loss assessment helps insurers to allocate the right amount of provisions in time.

Using satellite and drone images, 4Quant accelerates and improves the process of loss assessment. Automated

analysis of the damaged assets may be both faster and more reliable than the traditional, manual assessment.

This helps insurers to allocate resources more precisely both in volume and time.


ACCELERATION / IMPROVEMENT OF CLAIMS MODELINGFast and reliable information on damages is also crucial for claims modeling. Modeling firms undertake huge efforts to investigate damage events to improve their predictive capabilities.

As 4Quant may help insurers in assessing insured events, we may also support modeling firms with a thorough first-level event assessment. Using event imagery analytics enables modelers to base their equations on a growing base of robust data.

This in turn helps insurers to source improved severity curves in ever more reliable predictive hazard models.


➔ Our trained algorithms calculate the expected claims in real time with great accuracy

➔ Results can be directly integrated intoinsurer’s claims management system

ONLINE CLAIMS MANAGEMENT FOR CUSTOMERS

Example: effective car insurance claims handling

Process:

➔ After an accident, the driver or garage makes pictures of the damaged car

➔ Our database knows the topology of the healthy car


REAL-TIME INFORMATION FOR INSURANCE LINKED SECURITIES

Combining trained algorithms with real-time satellite imagery, 4Quant develops models for real time hurricane analytics.

This enables 4Quant to provide value for insurers as the sponsors of Cat Bonds, and also for investors, asset managers, and rating agencies.

Parametric Cat Bonds are indexed to the natural hazard caused by nature, such as atmospheric pressure in the eye of a hurricane.

Rapid assessment of such parameters is key to enable liquid markets and effective risk transfer.

However, often parameters are not available in real time.


INSURANCE MODELSWorldwide Loss Events 1980-2013

2014 Munchener Ruckversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at February 2014


ACCOUNTING FOR CLIMATE CHANGEClimate Change Predictions




ACCOUNTING FOR CLIMATE CHANGE


IMPACT OF CLIMATE CHANGE



Image-supported premium adaptation of car insurances


ADVANCED ANALYTICS: INNOVATION DRIVER IN INSURANCE

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Data & Analytics

Big image analytics for (Re-) insurer