Linking Millions of People Policies and Places

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GIS Development Manager IAG Direct Insurance - Geospatial Information Hugh Saalmans Linking millions of people, policies and places

Transcript of Linking Millions of People Policies and Places

Page 1: Linking Millions of People Policies and Places

GIS Development Manager

IAG Direct Insurance - Geospatial Information

Hugh Saalmans

Linking millions of

people, policies and places

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insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

agenda

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insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

agenda

insurance & IAG

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“...the business of manufacturing promises”

~ Warren Buffet, 2012

what is insurance?

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insurance is a sizable industry

$19,689,000,000

1.3% GDP

Source: APRA June 2012 Quarterly GI Performance Statistics

claims paid p.a.

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insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

pricing & location based risk

agenda

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pricing is affected by…

reinsurance costs

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pricing is affected by…

industry competition

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pricing is affected by…

government

fees & charges

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but most affected by…

how often a customer will need to make a claim; and

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but most affected by…

...how much it will cost each time

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to predict claims and claims cost - we need to determine the risk of something happening

to do that, we start with each property’s location and then assess its risk

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location based risk

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bushland

location based risk

distance to bushland = a bushfire risk factor

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park

bushland

location based risk

distance to parks = a burglary risk factor

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park

bushland

location based risk

distance to main roads = a collision risk factor

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park

bushland

location based risk

regional geology determines earthquake risk

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G - N A F

calculating location based risk

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geocodingL O C A T I O N

G - N A F

calculating location based risk

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spatial relationshipsWhat’s nearby?

geocodingL O C A T I O N

G - N A F

calculating location based risk

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modellingWhat could happen?

spatial relationshipsWhat’s nearby?

geocodingL O C A T I O N

G - N A F

calculating location based risk

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claim frequencyHow often?

modellingWhat could happen?

spatial relationshipsWhat’s nearby?

geocodingL O C A T I O N

G - N A F

calculating location based risk

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damage curvesHow severe?

claim frequencyHow often?

modellingWhat could happen?

spatial relationshipsWhat’s nearby?

geocodingL O C A T I O N

G - N A F

calculating location based risk

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insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

geocoding & addressing

agenda

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DI & geocoding

why? geocoding is the only cost effective method of locating risks, at the property level, on a national scale

1:1 pricing - a foundation of our strategy

What do we use?

geocoding

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DI & geocoding

status? geocoding and geo-pricing rolled out nationally

geocoding

100% overall geocoding rate

>95% household geocoding rate

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what is geocoding?

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what is geocoding?

converting addresses into usable locations

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3 areas for improvement

1. input addresses

2. address matching

3. reference addresses (G-NAF)

geocoding

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UNIT2LEVEL310-20ALFREDSTREETNORTHNORTH SYDNEY2060NSW

need a good

address structureStreet 2/3/10-20 Alfred St N

Suburb Nth Sydney NSW 2060

legacy addresses will need to be cleansed

input addresses

sub-dwelling typesub-dwelling no

level typelevel no

street numberstreet name

street typestreet suffix

localitypostcode

state

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good address capture has:

structured input

predefined pick lists

rapid address lookup

input addresses

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locality issues

local names vs gazetted

e.g. 96% of customers provide an unofficial suburb name in Tamworth

input addresses

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locality issues

vanity suburbs

input addresses

Kingswood

Heights

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the geocoding engine

evaluate, reconfigure, test it

G-NAF 360o test (geocode G-NAF itself)

address matching

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the geocoding engine

add your own logic

talk to your vendor

address matching

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insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

agenda

G-NAF

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is it any good – yes it is

errors – yes, but limited

completeness - ~95% complete

timeliness – can take up to 12 months for new addresses to be added

G-NAF (reference addresses)

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errors

mostly transient

range from amusing to business impact

can impact customers

use DIY database rules and QA to limit the impact

G-NAF

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errors

examples:

units being 1km from their building address

addresses assigned to the wrong duplicate locality

alias and principals with diff. cords

G-NAF

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completeness

postcodes sparsely populated on addresses

G-NAF

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completeness

sub-dwellings generally don’t have unique coords

Your customer data can be an additional “G-NAF data source”... use it!

G-NAF

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timeliness

Some new houses are insurable before address is in G-NAF

That’s why G-NAF Live is encouraging

G-NAF

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location is fundamental to insurance

geocoding - 3 areas of improvement (to get >95%)

addresses – clean, structured, well captured

engine – tested, optimised, customised

G-NAF – postcodes, sub-dwellings,

G-NAF Live

summary