Linking Millions of People Policies and Places

GIS Development Manager

IAG Direct Insurance - Geospatial Information

Hugh Saalmans

Linking millions of

people, policies and places

insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

agenda

insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

agenda

insurance & IAG

“...the business of manufacturing promises”

~ Warren Buffet, 2012

what is insurance?

insurance is a sizable industry

$19,689,000,000

1.3% GDP

Source: APRA June 2012 Quarterly GI Performance Statistics

claims paid p.a.

insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

pricing & location based risk

agenda

pricing is affected by…

reinsurance costs

pricing is affected by…

industry competition

pricing is affected by…

government

fees & charges

but most affected by…

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

but most affected by…

...how much it will cost each time

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

location based risk

bushland

location based risk

distance to bushland = a bushfire risk factor

park

bushland

location based risk

distance to parks = a burglary risk factor

park

bushland

location based risk

distance to main roads = a collision risk factor

park

bushland

location based risk

regional geology determines earthquake risk

G - N A F

calculating location based risk

geocodingL O C A T I O N

G - N A F

calculating location based risk

spatial relationshipsWhat’s nearby?

geocodingL O C A T I O N

G - N A F

calculating location based risk

modellingWhat could happen?

spatial relationshipsWhat’s nearby?

geocodingL O C A T I O N

G - N A F

calculating location based risk

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

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

insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

geocoding & addressing

agenda

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

DI & geocoding

status? geocoding and geo-pricing rolled out nationally

geocoding

100% overall geocoding rate

>95% household geocoding rate

what is geocoding?

what is geocoding?

converting addresses into usable locations

3 areas for improvement

1. input addresses

2. address matching

3. reference addresses (G-NAF)

geocoding

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

good address capture has:

structured input

predefined pick lists

rapid address lookup

input addresses

locality issues

local names vs gazetted

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

input addresses

locality issues

vanity suburbs

input addresses

Kingswood

Heights

the geocoding engine

evaluate, reconfigure, test it

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

address matching

the geocoding engine

add your own logic

talk to your vendor

address matching

insurance & IAG

pricing & location based risk

geocoding & addressing

G-NAF

agenda

G-NAF

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)

errors

mostly transient

range from amusing to business impact

can impact customers

use DIY database rules and QA to limit the impact

G-NAF

errors

examples:

units being 1km from their building address

addresses assigned to the wrong duplicate locality

alias and principals with diff. cords

G-NAF

completeness

postcodes sparsely populated on addresses

G-NAF

completeness

sub-dwellings generally don’t have unique coords

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

G-NAF

timeliness

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

That’s why G-NAF Live is encouraging

G-NAF

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