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Core Technologies & Methods

Much of the WRN programme is mediated through the modelled world and this environment rests upon a platform of technology, information and methods which underpin and enable research and operational services. The development of core technologies and methods is a primary aim of the Network and a specific reason for integrating public science with the industry so opportunities afforded by fundamental breakthroughs and facilities can be translated into innovation quickly and efficiently.

Latest on Core Technologies & Methods

  • The Insurance Industry Must Champion Sustainability

    Date: Dec 01, 2013 | Type: Paper | Attachment: Download File ›
    Journal: Thunderbird International Business Review Vol. 55, No. 6 November/December 2013 |

    Pillar: Core Technologies & Methods
    Hub: Insurance & Sustainable Business

    Authors: Matthew I. Shea, James W. Hutchin
    Fields: Sustainablity

    Summary: The insurance industry is uniquely placed in our economies as a private market mechanism for the sharing of risk, with the global pooling of what would be risks otherwise carried by individuals estimated at US$400 trillion (Insurance Working Group of the United Nations Environment Programme Finance Initiative, 2009). As risk pooling is instrumental for the efficient functioning of economies and societies, the insurance industry is understandably an object of regulation and public policy. Furthermore, as the risk pooling afforded is possible only with investors’ willingness to put capital at risk, profits are necessary for its continued existence.

    Can Sustainability be a Source of Competitive Advantage in the Insurance Industry?

    Date: Dec 01, 2013 | Type: Paper | Attachment: Download File ›

    Pillar: Core Technologies & Methods
    Hub: Insurance & Sustainable Business

    Authors: Matthew Shea and James Hutchin
    Fields:

    Summary: We wish to determine if insurers can acquire a competitive advantage if they integrate insureds’ sustainability performance into their underwriting models. Such a finding has profound implications for the insurance industry and the greater social and economic activity it drives.

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    A MapReduce Framework for Analysing Portfolios of Catastrophic Risk with Secondary Uncertainty

    Date: Apr 22, 2013 | Type: Paper | Attachment: Download File ›

    Pillar: Core Technologies & Methods
    Hub: Technologies and Platforms

    Authors: A. Rau-Chaplin, B. Varghese, Z. Yao
    Fields: MapReduce model, secondary uncertainty, risk modelling, aggregate risk analysis

    Summary: The design and implementation of an extensible framework for performing exploratory analysis of complex property portfolios of catastrophe insurance treaties on the Map-Reduce model is presented in this paper. The framework implements Aggregate Risk Analysis, a Monte Carlo simulation technique, which is at the heart of the analytical pipeline of the modern quantitative insurance/reinsurance pipeline.

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    Rapid Post-Event Catastrophe Modelling and Visualization

    Date: Oct 01, 2012 | Type: Paper | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods
    Hub: Technologies and Platforms

    Authors: Eric Mason, Andrew Rau-Chaplin, Kunal Shridhar, Blesson Varghese2 and Naman Varshne
    Fields: post-event earthquake analysis; catastrophe modelling; loss estimation; loss visualization

    Summary: Catastrophe models capable of rapid data ingestion, loss estimation and visualization are required for postevent analysis of catastrophic events such as earthquakes. This paper describes the design and development of the Automated Post-Event Earthquake Loss Estimation and Visualization (APE-ELEV) system for real-time estimation and visualization of losses incurred due to earthquakes. A model for estimating expected losses due to earthquakes in near realtime is described and implemented. Since immediately postevent data is often available from multiple disparate sources, a geo-browser is described that helps users to visualize and integrate hazard, exposure and loss data.

    Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk

    Date: Oct 01, 2012 | Type: Paper | Conf: International Conference for High Performance Computing, Networking, Storage, and Analysis | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods
    Hub: Technologies and Platforms

    Authors: A. K. Bahl, O. Baltzer, A. Rau-Chaplin and B. Varghese
    Fields:

    Summary: At the heart of the analytical pipeline of a modern quantitative insurance/reinsurance company is a stochastic simulation technique for portfolio risk analysis and pricing process referred to as Aggregate Analysis. This paper explores parallel methods for aggregate risk analysis risk analysis.

    Likelihood inference for Archimedean copulas in high dimensions under known margins

    Date: Sep 28, 2012 | Type: Article | Journal: Journal of Multivariate Analysis - Special Issue on Copula Modeling and Dependence | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods

    Authors: Marius Hofert, Martin Mächler, Alexander J. McNeil
    Fields:

    Summary: This paper gives theoretical insight about how to compute complicated densities in high dimensions (required for estimation)

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    A Platform for Parallel R-based Analytics on Cloud Infrastructure

    Date: Sep 01, 2012 | Type: Paper | Conf: International Workshop on Cloud Technologies for High Performance Computing | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods
    Hub: Technologies and Platforms

    Authors: Ishan Patel, Andrew Rau-Chaplin and Blesson Varghese
    Fields: Cloud computing; Amazon Cloud Services; Parallel Analytics; R and Snow

    Summary: Analytical workloads abound in application domains ranging from computational finance and risk analytics to engineering and manufacturing settings. In this paper the authors describe a Platform for Parallel R-based Analytics on the Cloud (P2RAC. The goal of this platform is to allow an Analyst to take a simulation or optimization job (both the code and associated data) that runs on their personal workstations and with minimum effort have them run on large-scale parallel cloud infrastructure. If this can be facilitated gracefully, an Analyst with strong quantitative but perhaps more limited development skills can harness the computational power of the cloud to solve larger analytically problems in less time. P2RAC is currently designed for executing parallel R scripts on the Amazon Elastic Computing Cloud infrastructure. Preliminary results obtained from an experiment confirm the feasibility of the platform.

    Visual analysis of social networks in space and time

    Date: Jun 22, 2012 | Type: Article | Conf: Nokia Data Challenge Workshop, Pervasive 2012, 20 - 22 Jun 2012, Newcastle, UK | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby, Roger Beecham, Jo Wood
    Fields:

    Summary: In this paper, the authors designed and applied novel interactive visualisation to investigate how social networks - derived from smartphone logs - are embedded in time and space.

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    Visualisation of Origins, Destinations and Flows with OD Maps

    Date: May 01, 2010 | Type: Paper | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood.
    Fields: GIS & Geovisualisation

    Summary: Presents a new technique for the visual exploration of origins (O) and destinations (D) arranged in geographic space.

    Efficiently sampling nested Archimedean copulas

    Date: May 01, 2010 | Type: Paper | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods
    Hub: Science & Innovation

    Authors: Marius Hofert
    Fields: Statistics & Modelling

    Summary: Efficient sampling algorithms for both Archimedean and nested Archimedean copulas are presented

    A novel way of exploring spatial variation in data

    Date: Mar 18, 2010 | Type: Paper | Ext. Link: Click Here ›

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood.
    Fields: GIS & Geovisualisation

    Summary: A presentation of rectangular hierarchical cartograms for mapping socio-economic data and a demonstration of cartograms by mapping the Office for National Statistics Output Area Classification (OAC) by unit postcode (1.52 million in Great Britain) through the postcode hierarchy, using these to explore spatial variation.

    Rethinking Map Legends with Visualization

    Date: Jan 01, 2010 | Type: Paper |

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood.
    Fields: GIS & Geovisualisation

    Summary: This design paper presents new guidance for creating map legends in a dynamic environment. It suggests is a set of guidelines for legend design in a visualization context and a series of illustrative themes through which they may be expressed.

    A novel visualisation technique for spatial data

    Date: Jan 01, 2010 | Type: Paper | Attachment: Download File ›

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood. Robert Radburn, Roger Beecham.
    Fields: GIS & Geovisualisation

    Summary: At Leicestershire County Council, spatial treemaps are used to analyse labour markets and commuting behaviour. This novel visualization technique, presented at InfoVis 2008, has resulted in a number of insights and discoveries.

    Using Twitter and HiVE and QR Codes to enable collaborative spatial analysis

    Date: Jan 01, 2010 | Type: Paper | Attachment: Download File ›

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood.
    Fields: GIS & Geovisualisation

    Summary: The demonstration of a new approach to collaborative visual analysis, in which descriptions of graphics are shared online. HiVE – a high-level descriptive language – captures the way in which graphics are built and configured.

    New Ways of Visualising Seasonal Climate Forecasts

    Date: Apr 01, 2009 | Type: Article |

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , David Stephenson , Jason Dykes and Jo Wood. Rachel Lowe and Tim Jupp
    Fields: Climate Change

    Summary: Seasonal climate forecasts are used by climate scientists, government departments, utility agencies, health agencies and in agriculture. Uncertainties in environmental data and in numerical prediction models make such forecasts inherently probabilistic. Good decisions require that this uncertainty in predictions be communicated to users. Some established methods have limitations, prompting this collaborative work between data visualizers and climate scientists facilitated by the Willis Research Network.

    Visualization of Uncertainty and Analysis of Geographical Data

    Date: Jan 01, 2009 | Type: Paper |

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood. Naz Khalili-Shavarini and David Mountain
    Fields: GIS & Geovisualisation

    Summary: A team of five worked on this challenge to identify a possible criminal structure within the Flitter social network. This summary of the work emphasises one of those applications detailing the geographic analysis and uncertainty handling of the network data.

    Techniques for exploring property price data

    Date: Jan 01, 2009 | Type: Article |

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood. Andrew Crooks
    Fields: GIS & Geovisualisation

    Summary: The price of property and how it varies spatially within cities through time can be linked to the economic and social processes of urban systems. Treemaps (Shneiderman, 1992) are used for visually exploring 1.8 million property sales in London between 2000 and 2007 – and focus on how the layout and ordering of elements in the treemap can reveal different information.

    Flow tree for Exploring Spatial Trajectory

    Date: Jan 01, 2009 | Type: Paper |

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby , Jason Dykes and Jo Wood. Robert Radburn
    Fields: GIS & Geovisualisation

    Summary: This paper presents a novel alternative representation of origin-destination topology that makes it more amenable to the visualization of structure and spatial organisation of trajectories.

    Reliability Analysis of Infrastructure Networks Using OBDD

    Date: Nov 03, 2008 | Type: Paper |

    Pillar: Core Technologies & Methods
    Hub: Science & Innovation

    Authors: Charles Scawthorn and Mohammad Javanbarg. J. Kiyono, Kyoto University Y. Ono, Kyoto University
    Fields: Seismic

    Summary: The authors of this paper propose a method for computing terminal-pair reliability of infrastructure networks based on Binary Decision Diagram (BDD)

    Google Earth and Risk Management - A New Future

    Date: Aug 11, 2008 | Type: Article |

    Pillar: Core Technologies & Methods
    Hub: Mapping and Geospatial Science

    Authors: Aidan Slingsby
    Fields: GIS & Geovisualisation

    Summary: The WRN's Dr Aidan Slingsby talks Google, Geovisualisation and GIS to reinsurance magazine, The Review

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As economic, social and environmental uncertainties increase, institutions and populations seek greater resilience to support sustainable growth. Science and insurance lay at the heart of understanding, managing and sharing these risks, building more secure futures at local and global scales.

The Willis Research Network (WRN) operates across the full spectrum of risk from natural catastrophe, to legal liability, financial and security issues linked across driving themes: Resilience, Security & Sustainable Growth; Managing Extremes; Insurance & Risk Management and Mastering the Modelled World.

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