Earthquake insurance in Iran: Solvency of local insurers in light of the current market practice

Ghafory-Ashtiany, Mohsen; Motamed, Hooman

doi:https://doi.org/10.5194/nhess-2023-81

Preprints

https://doi.org/10.5194/nhess-2023-81

Preprints

16 Jun 2023

| 16 Jun 2023

Status: a revised version of this preprint is currently under review for the journal NHESS.

Earthquake insurance in Iran: Solvency of local insurers in light of the current market practice

Mohsen Ghafory-Ashtiany and Hooman Motamed

Abstract. Due to its location in one of the most seismically active regions in the world, Iran has witnessed many devastating earthquakes through history. To finance a part of these losses and reconstruction expenses, earthquake insurance has been offered as a rider of fire policy by the Iranian insurers. This mechanism, if well operated, can substantially contribute to disaster risk management. On the other hand, if the pricing and management of catastrophe risk lack a sound, risk-based practice, it might add to the problems and act to the detriment of disaster risk management. In this paper, we first compare the current earthquake insurance pricing and risk management in the Iranian insurance industry with a state-of-the-art insurance regulation in the European Union (Solvency-II). Then, we examine the consequence of following each approach in terms of business profitability and viability by conducting a numerical analysis on a hypothetical portfolio of property risks in Iran. The results suggest that maintaining the current insurance pricing and risk management techniques in Iran will probably lead to a substantial accumulation of earthquake risk for domestic firms and eventually endanger the solvency of these companies in the event of large-scale earthquake losses in future.

Received: 21 May 2023 – Discussion started: 16 Jun 2023

Download & links

Mohsen Ghafory-Ashtiany and Hooman Motamed

Status: final response (author comments only)

CC1:
'Comment on nhess-2023-81- Public-Private cooperation schema', Abbas FathiAzar, 27 Jun 2023

I want to congratulate the authors on their impressive contribution to the field; to my knowledge, this work appears to be the first of its kind in Iran, systematically addressing the solvency issue. It holds significant value due to the implementation of a CAT model that I believe has the potential to surpass the quality of comparable models of renowned vendors. Additionally, the critical evaluation of existing requirements in comparison to internationally recognized solvency standards further enhances the importance of this work.
This work presents a compelling argument for transitioning from the current approach in the insurance industry in Iran to a risk-based approach, and if implemented effectively, this shift has the potential to provide protection to both policyholders and insurers in the event of extreme Earthquakes.
As it is explained in the paper, the low penetration rate of earthquake insurance makes it a bit more challenging when designing feasible solutions. One such solution that I believe can act as an ad-hoc solution in the current situation is a Public-Private cooperation schema, which is discussed in the paper very briefly. I think even if restricted solvency regulations are implemented, without the government’s help, the private insurance companies have just two ways forward: 1- play with deductible and limit (exposing the policyholder to higher risk); 2- setting high premiums (preventing the people from purchasing the policies). Therefore, based on your discretion, there might be more explanation on this issue included in the paper.
Best Regards
Abbas FathiAzar

Citation: https://doi.org/10.5194/nhess-2023-81-CC1
- AC1: 'Reply on CC1', Hooman Motamed, 10 Jul 2023
  
  Dear Mr. FathiAzar,
  Many thanks for your comments. The authors do agree with you in that only enforcing stringent regulations would not improve the market and insurance penetration and other incentives such as private-public cooperations (including Iran Catastrophe Insurance Pool) need to be implemented. We will add more contents in the conclusion section and elaborate more on solutions in this regard as far as possible.
  
  Citation: https://doi.org/10.5194/nhess-2023-81-AC1
CC2:
'Comment on nhess-2023-81', Farhad Behnamfar, 30 Jun 2023
A quick look at the paper:
Earthquake insurance in Iran: Solvency of local insurers in light of the current market practice
This is a helpful and in-time research paper, which sheds light on inner hidden layers of the insurance business in Iran, by stating finally that it has remained as a business-only activity so far!

It seems that its first row of audience should have been the decision makers in the economic sector of the government, and then the principals of the insurance companies. The last row goes to the external ears. Was it tried in the same order, since now it has ended up in an international journal?

Use of GEM’s OpenQuake as a probabilistic risk assessment platform is a highly up-to-date approach to such problems that combines the probabilistic events with their economic consequences using rich contemporary models. This is a major strong point of this paper.

Another important aspect of the study extent is its diversity as appeared in comparison of the earthquake risk solvency charge calculated by each methodology through selecting cities located in various seismicity zones contained different construction type compositions. This aspect adds to the generality of the outcome of the study.

Table 1, Earthquake premium rates: It seems that for locations like Isfahan where concrete buildings have been far more popular than the other types of buildings in recent decades, the corresponding value should be higher.

Selection of the Earthquake Model of Middle East (Şeşetyan, et al., 2018) from within a wide range of studies is not fully justified in this paper. Since it is a core engine for the calculations, it should have been chosen in a more convincing way.

Figure 1 comes by surprise as it conveys such an important data with almost no background information about the line and area sources used, GMPE for different seismic sources, the logic trees [types as threes in the paper], and the soil model!

Figure 1 in fact is not showing the 475-year PGAs. Those are much higher in the related Iranian earthquakes. Use of such inexact expressions has always produced serious misunderstandings among young engineers in the country. It is actually the base or effective peak acceleration.

On line 259 the paper says “the cities of Esfahan in central Iran and Ahvaz in south-western Iran belong to zones with the lowest PGA levels”: For Ahvaz, this is against what is seen in Fig. 1!

A drawback in Fig. 1 is seemingly its sharp contrast in some places such as Khuzestan. In other words, the so-called “PGA” cannot physically change drastically between two close points on the map.

Fig. 3: There should be some problem with the calculations related to Isfahan county as it is almost on the top between the counties regarding values of all kinds of construction!

The package of vulnerability curves developed by Mansouri and Amini-Hosseini is an extremely precious asset of the earthquake engineering community in Iran and a tall jump up in the related research works in recent years. Use of the mentioned package has been a wise act in this study.

Line 326: “The city of Esfahan, despite being located in a low seismicity zone, also shows high seismic risk solely due to its very high building exposure (the second-highest exposure value after Tehran) and the prevalence of more vulnerable building classes of masonry and adobe”: It seems the statistics behind this rationale is not up to date. Currently, the RC buildings govern the other classes in number in Isfahan.

It is suggested to compare the AAL results of this study with the recent similar study of Kohrangi et al. There are some questionable differences.

There is a significant gap between the calculations and conclusions regarding the constant-factor approach adopted by the Central Insurance of Iran. There should have been a concentrated discussion about this important point right after line 387 of the paper.

Last but not the least, this is a unique and valuable study in its kind in the country. In normal conditions, it could originate serious discussions and challenges for the bettering of the relevant sectors. Anyhow, it will have certain impacts in the times to come.

Sincerely,
Farhad Behnamfar
Citation: https://doi.org/10.5194/nhess-2023-81-CC2
- AC2: 'Reply on CC2', Hooman Motamed, 10 Jul 2023
  
  Dear Dr Behnamfar,
  Many thanks for your detailed comments. As mentioned in your Comment 2, the first audience of this sponsored resaerch are government decisionmakers and then insurance firms. Luckily, the results of the resaerch have already used by Central Insurance of Iran in designing laws related to Iran Public catastrophe Pool and also shared with and well received by public and private insurance companies. This paper tends to share the results with technical audience and other resaerchers. Table 1 rates are based on current market rates in Iran and extracted from aggregator insurance websites. We agree that these rates are an underestimation of actual risk. Earthquake Model of Middle East (EMME) has been chosen for several reasons such as participation of regional scientist in its preparation, its global credibilty, use of more recent seismological data, and its compatibility to GEM's OpenQuake platform. This is the same model used by Kohrangi et al (2021) as well. Regarding Figure 1, we think values are reasonable and comparable to GEM 2023 global hazard map and some local studies we checked. We agree to add more informatin to this section (seismic sources, GMPEs used, logic trees and soil model) will help the reader to better understand the process. We agree that phrasing in 259 might be misleading. We will rephrase that. Sharp contrast between hazard levels (Figure 1) is caused by the method of interpolation. In the risk assessment, the value of hazard is calculated in the centroid of exposure grids, so the impact of interpolation error will be minimised. The statistics we used is based on 2016 census which indicate that about half of built area in Isfahan province is either masonry and adobe. Kohrangi et al (2021) has reported 44% which is very close to our exposure split. Our AAL values for the COUNTY of Isfahan is less than what Kohrangi et al (2021) calculate for the CITY of Isfahan. Since we almost share the same hazard and exposure models, this might probably stem from different vulnerabiliy curves used in two studies. We agree to add more explanation at the end of numerical results for more clarity. Again, we would like to thank you for your constructive comments.
  
  Citation: https://doi.org/10.5194/nhess-2023-81-AC2
CC3:
'Comment on nhess-2023-81', Ali Kharrazi, 09 Jul 2023

This paper provides novel insights into insurance pricing and risk management techniques in Iran. I particularly found the discussions on the evolution of insurance provision frameworks and regulatory issues in Europe and Iran to be very interesting. Overall the research is well designed and well written, there are segments that would require some proofreading and light editing. Some suggestions to the authors to improve their work:
- I suggest the authors discuss why these five provisional capitals were chosen. An additional discussion on the diversity of the zones and construction types found in this city in section 3 would benefit the readership.
- I suggest the authors briefly overview all of the data sources before section 3.1. In this segment, it's not clear to the reader where the data to construct the portfolio of 1,500 residential dwellings was obtained.
- Figures 1-3 and maps elsewhere, I suggest removing the abbreviated names of the neighbouring countries or using standard ISO-alpha-3 country codes, e.g., SAU would be KSA and ARE would be UAE.
- I suggest the authors add some discussions on the limitations of their study and future research directions in the conclusion section.

Citation: https://doi.org/10.5194/nhess-2023-81-CC3
- AC7: 'Reply on CC3', Hooman Motamed, 13 Apr 2024
  
  Dear reviewer,
  Many thanks for your time and constructive comments. Please find our answers below in italic:
  - I suggest the authors discuss why these five provisional capitals were chosen. An additional discussion on the diversity of the zones and construction types found in this city in section 3 would benefit the readership. A paragraph was added at the end of section 3.1.1. to explain why we selected these cities. We also deleted a line that might confuse the reader regarding the construction types at this stage of the paper. We added more information in the 4.2 section where we use a portfolio of dwelling sin these cities to portraits the difference between two approaches.
  - I suggest the authors briefly overview all of the data sources before section 3.1. In this segment, it's not clear to the reader where the data to construct the portfolio of 1,500 residential dwellings was obtained. The data sources we used for seismic hazard modelling are introduced in hazard, vulnerability, and exposure section separately to be more relevant to the context.
  - Figures 1-3 and maps elsewhere, I suggest removing the abbreviated names of the neighbouring countries or using standard ISO-alpha-3 country codes, e.g., SAU would be KSA and ARE would be UAE. We double checked the 3-digit ISO name of neighbouring countries and they were actually correct (Saudi Arabia: SAU and United Arab Emirates: ARE).
  - I suggest the authors add some discussions on the limitations of their study and future research directions in the conclusion section. A paragraph added to the end of the conclusion section to discuss the role of data availability in enhancement of the results.
  
  Citation: https://doi.org/10.5194/nhess-2023-81-AC7
RC1:
'Comment on nhess-2023-81', Zoran Stojadinovic, 19 Jul 2023
The overall quality of the preprint (general comments)

The overall quality of the preprint is good. The topic of earthquake insurance pricing and risk management is significant for the science community. The research is well structured and explained. The authors made a considerable effort to compare the current earthquake insurance pricing and risk management in Iran with the European Union insurance regulation (Solvency-II) in a credible way. But, there are deficiencies in the paper, mostly related to explaining the dataset, comparing methodologies and monetizing risk.
This reviewer believes that the authors should make an additional effort to demonstrate the added value of this research to the body of knowledge. Rewriting Chapter 4.2 and adding a Discussion chapter can substantially improve the paper.
Individual scientific questions/issues (specific comments)

Generally speaking, the paper is well written and explained from the beginning to Chapter 4.2. Nevertheless, here are two remarks which influence the overall quality of the research:
The authors introduce the dataset in line 168 and explain processing difficulties in Chapter 3.2.2. Please provide additional information about the method for choosing buildings and determining feature values. A dataset summary table containing information about building types and other features is necessary.

The authors fail to demonstrate how they built the exposure model in Chapter 3.2.2. How do authors determine Residential Building Values later aggregated at the county level?

The authors should rewrite Chapter 4.2. The example shown in Table 3 is oversimplified. Why and how did the authors choose “100 residential buildings of masonry, steel and RC types with a total built area of 100,000m2”? How did the authors come by a 300$ replacement cost (likely 300$/m2)? A redesigned experiment probably will not change the conclusions but still should be improved and results better discussed.
Finally, here are some topics which the authors could include and discuss in the paper:
Earthquake parametric insurance – how does it relate to the paper topic? Possibly the authors could add a separate subchapter.

How best to compare different insurance markets - perhaps including the national GDP in calculations can balance the results?

The Discussion chapter cannot solve insurance pricing issues, but the authors can present their views on limitations, opportunities, advances, future work or the way forward based on their findings.
The submitted research is promising, and I look forward to reviewing the improved version.
Technical corrections

There is a need for some technical corrections, highlighted in the attached file. The authors should carefully check the paper for unnecessary long sentences, missing articles or singular/plural mistakes.
Citation: https://doi.org/10.5194/nhess-2023-81-RC1
- AC3: 'Reply on RC1', Hooman Motamed, 06 Sep 2023
  
  The authors would like to thanks the reviewer for his detailed and useful comments provided. More information on the criteria for selecting a test portfolio will be added to Chapter 3 to remove potential ambiguities. The rationale behind selecting such portfolio is to include possible variabilities both in terms of seismotectonic nature of cities in Iran and different types of building for which premium ratios exist both in the local market (premiums calculated based on aggregator sites) and our seismic cat model. The replacement cost of buildings is the average cost of reconstruction per unit area for a conventional engineered (complying with local construction codes) which was estimated about USD 300 per sqm at the time of writing the paper. We will add a new chapter for discussing the results as well as relevant topics as the effect of cat pools, parametric insurance and public/private collaboration in post-disaster construction. Regarding the GDP, we are not sure if we understood the point raised. To us, solvency capital should be calculated based on risk perception of insurance firms and 1-in-200 year probability could be valid for the Iranian market as well.
  
  Citation: https://doi.org/10.5194/nhess-2023-81-AC3
CC4:
'Comment on nhess-2023-81', Babak Mansouri, 29 Jul 2023
Dear respected editor and authors,
The manuscript is well written with a good style. The paper is a valuable research towards scientific and systemic analysis for solvency of insurers associated to the catastrophe insurance by considering probable seismic losses considering the entire geography, seismicity, building stocks, vulnerability, etc. as a main requirement for a justifiable insurance system for the country. Utilizing the Openquake platform and tailoring the input data and preparing the databases for the country-specific calculation is one of the strong aspect for this manuscript.
Moreover, the paper describes and presents the problems associated with the existing insurance policy according to the scientific calculation and compares the outcome with a well-received European scheme in order to evaluate the solvency of the local insurers. However, there are some points that need to be addressed/modified or explained further as listed in bellow:
Line 11: It is suggested to write "fire insurance policy" instead of "fire policy".

Line 18: It is mostly "risk management practice" rather than "...techniques).

A brief summary of the quantitative findings is suggested in the ABSTRACT.

Line 30: It also hit big cities like Sarpol Zahab but you may say "if the epicenter was within or very close to big cities....."

Line 111: Please explain briefly about "life" and "non-life" insurance.

Starting from line 119: Needs more explanation on how Solvency II has been carried out. The paragraph describes the first Pillar...how about the other two pillars?

Line 152: Not clear what is meant by "motor".

Line 168: 1500 residential dwellings. Please indicate that these are "Housing Units" and not buildings.

Please justify better why only 1500 housing units (HU) have been taken into account (can this represent the solvency as intended... please justify better). How the dataset has been distributed for each big city and what is the overall share for each city from 1500 HU. Why your calculation does not consider the complete building pool since you are utilizing Openquake? Because it seems more useful to use the complete building pool to understand the national shortcomings and to devise a better policy and to assign more proper premiums for the selected policy. Or this may be a scope for your future research... please mention it in such case. If there is as purpose for such choice please clarify (for example: it may be just for a sake of comparing two solvency schemes just in a relative sense).

Table 1 & Table 2 and text: premium rate... what is the unit?

Line 217: instead of "national level" please indicate "country level" conforming with your formula....and spell-check "country" in Eq 5

Line 290: Is this 55% housing units or buildings... it seems housing units is correct... please also recheck the paper for this issue.

Line 301: It is Fig. 4

4: please indicate the reference in the caption.

Line 314: incomplete sentence.

Line 323: change to: Figure 1 and Figure 2

There is a mixture of "one-in 200" (text), "1-in-100" (Figure 6), "1-in-200' (text and Figures... it seems "1-in-200 years" is correct. Please check and correct all the text and Figures (caption and above legends).

Figure 6 – to cite in the text.

Line361: Is this 300 USD per m² (square meters)

Table 3 and Line 387: Please indicate number of housing units involved... otherwise it seems too low for big cities .

Line 400: 1-in200 years

Please recheck referencing and references... Line 297, "Mansouri and...[38]" please use proper referencing scheme... it is actually GEM-EMME WP4 project accomplished in IIEES in 2013 (relevant to section 3.2.3 first paragraph). "Mansouri, B., and Amini-Hosseini, K., 2013, “Global Earthquake Risk Model (GEM) - Earthquake Model of the Middle East Region (EMME) - WP4: Seismic Risk Assessment”, Final Report, 2013"
Citation: https://doi.org/10.5194/nhess-2023-81-CC4
- AC4:
  'Reply on CC4', Hooman Motamed, 06 Sep 2023
  Dear reviewer,
  
  Many thanks for reviewing our paper and providing constructive comments. Please find below answers to your comments in bold fonts:
  
  Line 11: It is suggested to write "fire insurance policy" instead of "fire policy": Thanks, we will use your suggested term for better clarity.
  
  Line 18: It is mostly "risk management practice" rather than "...techniques).: Will be replaced.
  
  A brief summary of the quantitative findings is suggested in the ABSTRACT.> We will add more results to the abstract.
  
  Line 30: It also hit big cities like Sarpol Zahab but you may say "if the epicenter was within or very close to big cities.....": The population of Sar-e Pol-e Zahab city at the time of 2017 earthquake was 46,000 which is equivalent to small cities.
  
  Line 111: Please explain briefly about "life" and "non-life" insurance.: An explanation will be added.
  
  Starting from line 119: Needs more explanation on how Solvency II has been carried out. The paragraph describes the first Pillar...how about the other two pillars?: A brief description will be added on other two pillars However, the topic of the paper is more related to Solvency Capital Requirement (SCR) which is mainly Pillar One.
  
  Line 152: Not clear what is meant by "motor".: Motor is the line of business for automobiles.
  
  Line 168: 1500 residential dwellings. Please indicate that these are "Housing Units" and not buildings.: Clarification will be added.
  
  Please justify better why only 1500 housing units (HU) have been taken into account (can this represent the solvency as intended... please justify better). How the dataset has been distributed for each big city and what is the overall share for each city from 1500 HU. Why your calculation does not consider the complete building pool since you are utilizing Openquake? Because it seems more useful to use the complete building pool to understand the national shortcomings and to devise a better policy and to assign more proper premiums for the selected policy. Or this may be a scope for your future research... please mention it in such case. If there is as purpose for such choice please clarify (for example: it may be just for a sake of comparing two solvency schemes just in a relative sense)> 1500 dwelling are selected because this is a reasonable amount of risk assumed by a medium insurance company in Iran. Our intention would be to examine how an average insurance company in the Iranian market could accumulate loss over time event by providing earthquake coverage for a small portfolio of buildings. The risk ratio has been assumed to be constant withing the cities (both because of the resolution of our model -Shahrestan and risk ratios extracted from the market. That is why spatial variability does not play a role here.
  
  Table 1 & Table 2 and text: premium rate... what is the unit? Rate (ratio of two USD values) is dimensionless.
  
  Line 217: instead of "national level" please indicate "country level" conforming with your formula....and spell-check "country" in Eq 5: We will harmonise that throughout the paper.
  
  Line 290: Is this 55% housing units or buildings... it seems housing units is correct... please also recheck the paper for this issue.: That is true. But in large numbers the ratio would be valid for buildings as well. We will modify this.
  
  Line 301: It is Fig. 4> We will correct this.
  
  4: please indicate the reference in the caption.: We will add the reference to caption.
  
  Line 314: incomplete sentence.: We will correct this.
  
  Line 323: change to: Figure 1 and Figure 2: we will correct this.
  
  There is a mixture of "one-in 200" (text), "1-in-100" (Figure 6), "1-in-200' (text and Figures... it seems "1-in-200 years" is correct. Please check and correct all the text and Figures (caption and above legends).: We will harmonise that to avoid misunderstanding.
  
  Figure 6 – to cite in the text.> Will be added.
  
  Line361: Is this 300 USD per m² (square meters): Yes, it is. It is based on the USD equivalent of the average quality "construction" in Iran at the time of conducting the research.
  
  Table 3 and Line 387: Please indicate number of housing units involved... otherwise it seems too low for big cities .: Will be added.
  
  Line 400: 1-in200 years> Will be modified.
  
  Please recheck referencing and references... Line 297, "Mansouri and...[38]" please use proper referencing scheme... it is actually GEM-EMME WP4 project accomplished in IIEES in 2013 (relevant to section 3.2.3 first paragraph). "Mansouri, B., and Amini-Hosseini, K., 2013, “Global Earthquake Risk Model (GEM) - Earthquake Model of the Middle East Region (EMME) - WP4: Seismic Risk Assessment”, Final Report, 2013"> the reference will be corrected.
  
  Citation: https://doi.org/10.5194/nhess-2023-81-AC4
RC2:
'Comment on nhess-2023-81', Anonymous Referee #2, 31 Jul 2023
The article addresses the adequacy of the solvency capital for catastrophe properties in Iran calculated according to the current regulation. For a chosen portfolio of residential buildings, event-based probabilistic seismic risk assessment is performed and the results in terms of Average Annual Loss (AAL) and loss Exceedance Probability (EP) are used to calculate the Solvency Capital Requirement (SCR) according to the Solvency-II Directive instructions. The required solvency capital for the same buildings’ portfolio obtained adopting the methodology introduced by the Iranian Directive No. 69 was estimated as well. The comparison between the Solvency-II and Directive 69 solvency capitals showed the limits of the insurance solvency regulation currently adopted in Iran. The outcomes of the study also underlined the need of adopting a stochastic earthquake risk model to calculate solvency capital and to ensure Iranian insurance companies to cover future catastrophe losses to happen in Iran.
This research is valuable for worldwide scientific communities as well as private stakeholders. The scientific quality of the paper is good. Scientific data, models adopted, and results are presented in a well-structured way. However, the presentation quality of this study could be improved. Specifically, the following comments and suggestions may be considered by the authors:
In table A1 is shown the level of risk associated with different building typologies in Iran, according to the study of Ghafory-Ashtiany M. (1991). However, there is no description of hazard scale used. May be useful to know the correspondence between such hazard levels and intensity measure (e.g., PGA ranges) used to define it.

Table 1 shows averaged earthquake insurance premiums for different building typologies in five provincial capital cities of Iran. To allow an easier understanding of the table contents, the values reported should be further commented. For instance, the cities of Tehran, Tabriz, Kerman presents a premium rate for masonry buildings equal to 1.1, while the cities of Esfahan and Ahvaz a premium rate of 0.78. Is such difference in the premium rate due only to the different hazard level? Is it due also to the different construction features of masonry buildings in the area (e.g., Adobe and Traditional or Confined Masonry, as reported in table A1)? Also, if the difference is only due to the different hazard level, why are the premium rates for masonry buildings the same in the city of Kerman and Tabriz while the rates for other typologies are different (e.g., 0.50 in Tabriz and 0.37 in Kerman for steel buildings)? Please, provide additional comments on it.

Event-based stochastic modelling is adopted in this study to quantify seismic risk. Despite this study focuses on the comparison of solvency capital calculation methods, a brief description of the risk assessment procedure adopted in the study could be useful. Please, consider briefly describing how hazard, exposure and vulnerability are incorporated in the process to generate event loss tables and how OpenQuake platform performs seismic risk calculation. At least, references to documents reporting such descriptions should be provided.

In section 3.2.2 the exposure modelling is described. As no information on building’s construction year is provided in 2016 census data, all dwellings built between 2011 and 2016 are assumed constructed with modern material such as steel and RC. Are such dwellings equally divided into the two building typologies (RC and steel)? Such distribution should be specified as the two typologies could have different seismic performance (e.g., as shown in figure 4).

In section 3.2.3 a better description of vulnerability classes is needed. Nine vulnerability classes are identified by the adopted vulnerability model (Mansouri and Amini-Hosseini). Two classes for masonry buildings are defined. How do these two classes differ? For instance, do they differ in terms of number of storyes? Do they differ in terms of quality construction? Moreover, how the model characterize the quality construction? In other words, what is the meaning of “medium-quality construction” according to the model? Are there also other vulnerability classes for buildings characterized by low-quality and high-quality construction? A better description is needed. Moreover, in line 279 the authors claim that the buildings vintage is used as proxy for the quality of construction. Please, provide an example of how the building’s age is used as proxy for the quality of construction.

In line 281, it is stated that an auxiliary population dataset with a 30-arc-second resolution is used to disaggregate the county-level building exposure data. First, a brief description of the downscaling procedure of exposure data adopted for such disaggregation should be provided. Also, please add a comment for justify why a finer resolution for exposure modelling is needed for losses calculation.

The authors should provide a definition of “country” level adopted in this study. Indeed, in figures 3,5 and 6 the “country border” seems representing the national border, while in Tables 1 and 2 the country level seems to be smaller than the province level but still different to the city level. A precise definition of the scale is important also to understand input data used (e.g., exposure data provided by census).

In figure 3 the residential building value is reported. How is it calculated? Which database is used to derive such value? Is the value adopted differ only based on buildings construction material or other parameters (such as quality of construction) are considered for its evaluation? Also, is this value assumed constants in the entire country, regardless the building location (e.g., province, city)? Please, provide additional information about residential building values adopted. Furthermore, to be consistent with comment in lines 285 – 292, maps in figure 3 might be also shown in terms of number of buildings instead of in terms of exposure value.

Vulnerability curves adopted for losses calculation are described in section 3.2.3. However, it is not clear the translation of physical damage into monetary losses. In other words, once the damage ratio is given, how are economic losses calculated? Is it function of the replacement cost for the building? Is the building surface also considered for losses calculation? Even if the value of replacement costs is presented in line 360, I would be better to introduce it before showing maps with expected losses (Figure 5 and Figure 6).

Economic losses shown in Figure 5 may do not allow an exhaustive comprehension of seismic risk in Iran. In other words, in location where AAL is high it is not easy to understand if it is high due to the exposure (i.e., the presence of many buildings exposed to earthquakes) or due to the high seismic hazard as well as to the high vulnerability of residential buildings in the area. Please consider adding a figure showing the value of losses/m². It could be also useful to confirm comment reported in lines 317 – 330.

The assumptions made for the application presented in section 4.2 could be oversimplified. Despite the main aim of this study is to compared solvency capitals calculated with different approaches, the assumption that 100 buildings are covered by earthquake policies in each of the selected cities in the country, regardless their residential population, may lead solvency capital values (shown in table 3) too unrepresentative of real cases. In fact, 100 buildings could correspond to the 100% of residential buildings in a city and to the 1% of residential buildings in another city, depending on how populated they are. Thus, it would be more appropriate to define a fixed percentages of buildings covered by earthquake policies in each city and estimate the number of buildings covered based on the total number of residential buildings in the city. Moreover, differences in the diffusion of a given typologies in each area of the country should be considered. Instead of assuming the same percentage of masonry, RC and steel buildings in each city, it would be more appropriate to derive the percentage of occurrence of such typologies in each city from the exposure model (Figure 3) and to adopt such percentages for a better exposure/vulnerability characterization at city level. Therefore, the authors may consider adopting more appropriate assumption for that application.

As this study may be hard to understand for those who are not experts in the field of earthquake insurance, please consider the following suggestions:

In line 196 CRESTA zones are introduced. Please, provide a brief description of the CRESTA zones.

Likewise, the Weighted Total Value Insured (WTIV) the Total Insured Value (TIV) are mentioned in in lines 195 and 196. Please consider providing their definition and how they are derived.

In line 235 the event loss table (ELT) is introduced. What is the information provided in the ELT? Please, provide a briefly description on its contents.

Additionally, it is recommended to implement the following modifications (technical corrections):
The acronym “VaR” is presented in line 199. However, it is already used before (e.g., line 157). Please, add the specification for the acronym at its first mention.

In line 317 replace “figure 4” with “figure 5”. Likewise, replace “figure 5” with “figure 6” in line 331. Please, check the numbering of all figures.

The description of the figure in line 331 (one-in-200-year losses) is not in line with the figure caption 6 caption (Earthquake 1-in-100 loss). Please, modify it.

Please, correct the following typing errors:

Line 102: replace “Christchurch quakes” with “Christchurch earthquake”.

Line 112: use the square brackets as in the line 107.

Line 297: modify the reference “Mansouri and Amini-Hosseini [38]” using the proper reference scheme.
Citation: https://doi.org/10.5194/nhess-2023-81-RC2
- AC6: 'Reply on RC2', Hooman Motamed, 07 Sep 2023
  
  Dear reviewer,
  
  We would like to thank you for your precious comments to which we answered in bold font in the below:
  
  In table A1 is shown the level of risk associated with different building typologies in Iran, according to the study of Ghafory-Ashtiany M. (1991). However, there is no description of hazard scale used. May be useful to know the correspondence between such hazard levels and intensity measure (e.g., PGA ranges) used to define it.: These are seismic zone codes based on Standard 2800 (design of buildings to seismic loads in Iran). More description will be added for better clarity.
  Table 1 shows averaged earthquake insurance premiums for different building typologies in five provincial capital cities of Iran. To allow an easier understanding of the table contents, the values reported should be further commented. For instance, the cities of Tehran, Tabriz, Kerman presents a premium rate for masonry buildings equal to 1.1, while the cities of Esfahan and Ahvaz a premium rate of 0.78. Is such difference in the premium rate due only to the different hazard level? Is it due also to the different construction features of masonry buildings in the area (e.g., Adobe and Traditional or Confined Masonry, as reported in table A1)? Also, if the difference is only due to the different hazard level, why are the premium rates for masonry buildings the same in the city of Kerman and Tabriz while the rates for other typologies are different (e.g., 0.50 in Tabriz and 0.37 in Kerman for steel buildings)? Please, provide additional comments on it.: The premium ratio values reported in this table are those used currently by the insurance market in Iran. Although they are based on the 1991 study of Ghafory-Ashtiany but they have evolved over time by the market. The authors are aware that some of the values might not sound reasonable, but they preferred to keep them as they are as the current practice in the market.
  Event-based stochastic modelling is adopted in this study to quantify seismic risk. Despite this study focuses on the comparison of solvency capital calculation methods, a brief description of the risk assessment procedure adopted in the study could be useful. Please, consider briefly describing how hazard, exposure and vulnerability are incorporated in the process to generate event loss tables and how OpenQuake platform performs seismic risk calculation. At least, references to documents reporting such descriptions should be provided: We tried to put more weight on the main topic of the paper Solvency, as you mentioned. There are many details involved in the modelling of risk that might overshadow the main topic. However, more information on the damage and financial loss calculation will be added for better clarity in sub-chapter 3.2 (Modelling the earthquake risk in Iran).
  In section 3.2.2 the exposure modelling is described. As no information on building’s construction year is provided in 2016 census data, all dwellings built between 2011 and 2016 are assumed constructed with modern material such as steel and RC. Are such dwellings equally divided into the two building typologies (RC and steel)? Such distribution should be specified as the two typologies could have different seismic performance (e.g., as shown in figure 4).: That is true. Because the 2016 census data lacked the year of construction we used the prevailing distribution construction years of 2011 census and made assumptions to complete the "construction year" field. As you mentioned, we assumed that any number of dwellings reduced in each county for each construction type in 2016 belongs to the oldest year built group and whatever added belongs to either RC and Steel (because the number of Masonry dwellings was reduced in almost all counties between 2011 and 2016). As we new the construction type of the post-2011 buildings we distribute them to the corresponding type. It means we did not divide them equally between RC and Steel types.
  In section 3.2.3 a better description of vulnerability classes is needed. Nine vulnerability classes are identified by the adopted vulnerability model (Mansouri and Amini-Hosseini). Two classes for masonry buildings are defined. How do these two classes differ? For instance, do they differ in terms of number of storyes? Do they differ in terms of quality construction? Moreover, how the model characterize the quality construction? In other words, what is the meaning of “medium-quality construction” according to the model? Are there also other vulnerability classes for buildings characterized by low-quality and high-quality construction? A better description is needed. Moreover, in line 279 the authors claim that the buildings vintage is used as proxy for the quality of construction. Please, provide an example of how the building’s age is used as proxy for the quality of construction.: The only difference between two classes of masonry buildings is the period of construction (before 1976 and after 1976 according the paper) which is a proxy of construction quality. The height of the class is assumed to be low-rise in both cases. More information on the adoption of construction period as a proxy of quality will be added to the section.
  In line 281, it is stated that an auxiliary population dataset with a 30-arc-second resolution is used to disaggregate the county-level building exposure data. First, a brief description of the downscaling procedure of exposure data adopted for such disaggregation should be provided. Also, please add a comment for justify why a finer resolution for exposure modelling is needed for losses calculation.: The requested information will be added to the section including the method of downscaling and why it is necessary (due to the variation of seismic hazard across the county).
  The authors should provide a definition of “country” level adopted in this study. Indeed, in figures 3,5 and 6 the “country border” seems representing the national border, while in Tables 1 and 2 the country level seems to be smaller than the province level but still different to the city level. A precise definition of the scale is important also to understand input data used (e.g., exposure data provided by census).: That could be a spelling issue for "county" and "country". We will double check that.
  In figure 3 the residential building value is reported. How is it calculated? Which database is used to derive such value? Is the value adopted differ only based on buildings construction material or other parameters (such as quality of construction) are considered for its evaluation? Also, is this value assumed constants in the entire country, regardless the building location (e.g., province, city)? Please, provide additional information about residential building values adopted. Furthermore, to be consistent with comment in lines 285 – 292, maps in figure 3 might be also shown in terms of number of buildings instead of in terms of exposure value.: Three class of age (according to the period of construction) have been considered for major types of construction (RC, Steel and Masonry) and the value of construction for each time at the present time has been depreciated to estimate the value of dwelling for each type and each age class.
  
  Vulnerability curves adopted for losses calculation are described in section 3.2.3. However, it is not clear the translation of physical damage into monetary losses. In other words, once the damage ratio is given, how are economic losses calculated? Is it function of the replacement cost for the building? Is the building surface also considered for losses calculation? Even if the value of replacement costs is presented in line 360, I would be better to introduce it before showing maps with expected losses (Figure 5 and Figure 6).: Each pixel of the study has an ELT calculated by multiplication of damage ratios of each event for each of the building classes by number of dwellings in each construction class and average built area of each dwelling and its corresponding value. The economic loss of each pixel is calculated by dividing the sum of all events losses by number of years simulated.
  
  Economic losses shown in Figure 5 may do not allow an exhaustive comprehension of seismic risk in Iran. In other words, in location where AAL is high it is not easy to understand if it is high due to the exposure (i.e., the presence of many buildings exposed to earthquakes) or due to the high seismic hazard as well as to the high vulnerability of residential buildings in the area. Please consider adding a figure showing the value of losses/m2. It could be also useful to confirm comment reported in lines 317 – 330.: This is true. That is why we use exposure maps, degree of vulnerability of different building types, and seismicity of each region to interpret the resulted risk. The normalisation of losses by exposure will result in AAL ratio. A table of AAL ratios will be added in the appendix.
  
  The assumptions made for the application presented in section 4.2 could be oversimplified. Despite the main aim of this study is to compared solvency capitals calculated with different approaches, the assumption that 100 buildings are covered by earthquake policies in each of the selected cities in the country, regardless their residential population, may lead solvency capital values (shown in table 3) too unrepresentative of real cases. In fact, 100 buildings could correspond to the 100% of residential buildings in a city and to the 1% of residential buildings in another city, depending on how populated they are. Thus, it would be more appropriate to define a fixed percentages of buildings covered by earthquake policies in each city and estimate the number of buildings covered based on the total number of residential buildings in the city. Moreover, differences in the diffusion of a given typologies in each area of the country should be considered. Instead of assuming the same percentage of masonry, RC and steel buildings in each city, it would be more appropriate to derive the percentage of occurrence of such typologies in each city from the exposure model (Figure 3) and to adopt such percentages for a better exposure/vulnerability characterization at city level. Therefore, the authors may consider adopting more appropriate assumption for that application.>The selection of a rather small portfolio of 1500 buildings is reasonable for a medium size insurance company in Iran. Here, we did not intend to portray different levels of risk, since we already did that by creating the risk maps. The main objective of this example is to consider different seismicity zones in Iran in the calculation. As seen, results show that event a small portfolio of flats can impose significant amount of risk to a medium size firm in Iran.
  
  As this study may be hard to understand for those who are not experts in the field of earthquake insurance, please consider the following suggestions:
  
  In line 196 CRESTA zones are introduced. Please, provide a brief description of the CRESTA zones.> Will be added.
  
  Likewise, the Weighted Total Value Insured (WTIV) the Total Insured Value (TIV) are mentioned in in lines 195 and 196. Please consider providing their definition and how they are derived.: More information will be added as far as possible.
  
  In line 235 the event loss table (ELT) is introduced. What is the information provided in the ELT? Please, provide a briefly description on its contents.More information will be added as far as possible.
  Additionally, it is recommended to implement the following modifications (technical corrections):
  The acronym “VaR” is presented in line 199. However, it is already used before (e.g., line 157). Please, add the specification for the acronym at its first mention.
  
  In line 317 replace “figure 4” with “figure 5”. Likewise, replace “figure 5” with “figure 6” in line 331. Please, check the numbering of all figures.
  
  The description of the figure in line 331 (one-in-200-year losses) is not in line with the figure caption 6 caption (Earthquake 1-in-100 loss). Please, modify it. Will be modified.
  
  Please, correct the following typing errors:
  
  Line 102: replace “Christchurch quakes” with “Christchurch earthquake”. We meant "two" earthquakes happened in 2011 in NZ.
  
  Line 112: use the square brackets as in the line 107.Will be modified.
  
  Line 297: modify the reference “Mansouri and Amini-Hosseini [38]” using the proper reference scheme.Will be modified.
  
  Citation: https://doi.org/10.5194/nhess-2023-81-AC6
AC5: 'Comment on nhess-2023-81', Hooman Motamed, 07 Sep 2023

Dear Dr. Pazzi,
We tied to address the constructive comments we received from the reviewers as far as possible. Upon your approval we will start to modify the manuscript according the answers we provided to comments.

Best regards,
Hooman Motamed (On behalf of all authors)

Citation: https://doi.org/10.5194/nhess-2023-81-AC5

Mohsen Ghafory-Ashtiany and Hooman Motamed

Viewed

Total article views: 733 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
530	162	41	733	14	12

HTML: 530
PDF: 162
XML: 41
Total: 733
BibTeX: 14
EndNote: 12

Views and downloads (calculated since 16 Jun 2023)

Month	HTML	PDF	XML	Total
Jun 2023	160	37	6	203
Jul 2023	165	42	16	223
Aug 2023	57	13	3	73
Sep 2023	36	17	8	61
Oct 2023	24	12	1	37
Nov 2023	10	5	0	15
Dec 2023	11	7	1	19
Jan 2024	14	6	0	20
Feb 2024	28	18	2	48
Mar 2024	20	4	1	25
Apr 2024	5	1	3	9

Cumulative views and downloads (calculated since 16 Jun 2023)

Month	HTML	PDF	XML	Total
Jun 2023	160	37	6	203
Jul 2023	165	42	16	223
Aug 2023	57	13	3	73
Sep 2023	36	17	8	61
Oct 2023	24	12	1	37
Nov 2023	10	5	0	15
Dec 2023	11	7	1	19
Jan 2024	14	6	0	20
Feb 2024	28	18	2	48
Mar 2024	20	4	1	25
Apr 2024	5	1	3	9

Viewed (geographical distribution)

Total article views: 700 (including HTML, PDF, and XML) Thereof 700 with geography defined and 0 with unknown origin.

Country	#	Views	%

Latest update: 13 Apr 2024

Short summary

Iranian insurers has been offering earthquake cover since 1990's. However, despite international best practices they do not still use modern methods for risk pricing and management. As such, they seem to continue accumulating seismic risk over time. This paper examines the viability of this market in Iran by comparing the local market practice with international best practices in earthquake risk pricing (catastrophe modelling) and insurance risk management (European Solvency II regime).


Total:	0
HTML:	0
PDF:	0
XML:	0