The perilous journey to Perils Pricing

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2 The perilous journey to Perils Pricing Thoughts and considerations Justin Ho, Insurance Australia Group This presentation has been prepared for the Actuaries Institute 2015 General Insurance Half Day Seminar. The Institute Council wishes it to be understood that opinions put forward herein are not necessarily those of the Institute and the Council is not responsible for those opinions.

3 So what perils should we worry about? Flood Bushfire Earthquake Storm Hail Cyclone/Hurricane/Typhoon Storm surge Tsunami Landslip/landslides Volcano Drought Meteor shower? Solar storms? Know your perils?

4 Know your perils? (2) Answer: It depends on which geographical region, class of business, layer of CAT RI program For motor: hail For home: region specific VIC: bushfires/floods Nth QLD/WA: cyclone NSW: -top layers: earthquake -lower layers: storms SE Asia: Floods, earthquakes For Commercial Lines: Business interruption Source: 2014 ICA Disaster database revalued

5 There is no I in Team : importance of collaboration, a multi-disciplinary approach Recognise that pricing for natural perils is an exercise in collaboration and requires multi-disciplined approach Natural Hazards expertise: Meteorology, hydrologists, engineers, scientists Reinsurance: catastrophe modellers Statistical and actuarial know-how Geospatial GIS expertise Product and underwriting (business acumen) Sales & Marketing, distribution channels Systems: claims, policy systems, rating engine, IT (data)

6 Communication Pricing Process: The Merry-Go Round Technical (Statistical) Cost Premium Commercial Overlays: eg -Capping and cupping by segment -Differing profit by segment Commercial Premium: is the final customer price that is charged after allowing for commercial objectives. Iterative process Portfolio Management profitability competitive environment retention strategy cross product effect customer view reputation Affordability Distributor/channel considerations Model certainty adjustments Product design Pricing-Rating Engine rating structure granularity deployment issues

7 Feeding the model: data How good are your data inputs? Exposure Sum Insured (replacement value?) Asset details: Risk location and addressing information Year of construction. Missing values? Any defaults? Construction type Other rating factors: occupancy type, roof type, dwelling type etc ->vulnerability Policy Details: Excess, deductibles, limits, External factors: Hazard Information: Topography/terrrain, meteorological, seismicity, vegetation Never enough data but make do with what you can get

8 Building Attributes: Importance of Building Location Flood risk assessment resulting in $100 s to $1000 s difference Bushfire: similar effect

9 Data: Elevation Garbage-In Garbage Out

10 What s in the black box? The model told me so Flood damage vulnerability curves Cat models are great but they are not everything! There can be deficiencies in the models we use. Don't take for granted the black box whether these are industry vendor models such as RMS, AIR for cyclone and earthquake risk assessment NFID for flood Riskfrontiers FireAus model for bushfire Limitations of some of these models are to do with: the level of granularity of outputs ie can we price at level lower than suburb: bushfire? Assumptions eg vulnerability assumptions appropriate. where possible compare against internal data and modelling Unmodelled perils: storms

11 Earthquake Example Magnitude Larger than 6 5 ~ 6 4 ~ 5 Less than 4 Magnitude Larger than 6 5 ~ 6 4 ~ 5 Less than 4 Sept. EQ Greendale Fault Feb. EQ Jun. EQ Circa 1800~ 03 Sept Sept ~ 22 Feb (Seismic Information obtained from GeoNet, GNS, NZ)

12 Pricing Issues: we all have issues Moving away from community rated to granular risk differentiation However this results in affordability issues as removing or reducing the implicit cross subsidies. The big conundrum what to do about these large premium changes. Flood / ceiling / capping strategy of premium amount Renewal book strategy: caps on premium change, % or $ change Customer referral process Do we take long term or short term view of reinsurance costs. Pricing Vs Reinsurers view of risk. Cost plus Vs Demand/Supply pricing. Component based basis? Dealing with asset location and building attributes Optional Vs Mandatory cover Dealing with uncertainty: to discount or load? Community rating? Competing objectives in the price settling process? -> Commercialised prices may not reflect technical view of risk!

13 Pricing Considerations: Reputational Risks

14 Rating Engine: Breathe deeply Area granularity does your rating engine allow for address level pricing? Peril specific pricing: components based pricing, ie each peril is identified or is it some get big mixing pot..no one know s how much is allowed for in the commercialised premium for perils and reinsurance on a per policy level or even portfolio level basis. If some of your perils embedded in the base coverage premium then how does this interact with non perils or discount structures? Lack of transparency of the breakdown of perils in commercialised premium introduce cross subsidies or impossible to perform attribution of the pricing adequacy of the portfolio. Difficulties in backing out old pricing if wrapped in other factors Multiplicative or additive rating structure. Issue of non peril rating factors such as base rate changes or other factors impacting on the peril component of the premium result in over or under collection of the peril component of the premium and deviate away from the intended pricing strategy.

15 Let s talk about it : communication is key Internal Stakeholders Portfolio (Product and underwriting) Sales and Marketing Distributors: ie Agents, Brokers, Call centre and Branch network Government and Public relations people Example of Financial/Customer Impact Analysis: Premium Change Distribution Impacts Distribution of Premiums Spilt by Area, Flood Risk, Distribution Channel, Model type Measures: Number of Policies at Risk, Premiums Values, Sum Insured Vales External Stakeholders Customers Government: local, state, federal Regulators: APRA, ASIC Community Distribution network ICA, Other insurers

16 Flood Example: Figure 1: Area impacted Angry customer disputing premium No supporting documentation Existing public flood study for the area Indicates the property as high risk ie ARI < 10 What would you do? Straight forward communication to customer?

17 Flood: example continued Figure 2:100-year flood extent

18 Flood example: continued Figure 3: 100-year flood extent after filling of land Property owner may or maynot have evidence to prove the land was elevated eg Section 149 certificate But a renter will unlikely be in position to have this information unless go to council: fair? Based on elevation data the area was re-rated as low flood risk

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