Balancing Innovation and Profitability: Technological Diversification in Iran’s Insurance Industry

Seyed Amirhossein Shojaei; Bashar Yaser Almansour

doi:10.1515/apjri-2024-0011

Abstract

This study explores how technological diversification affects financial performance in Iran’s insurance industry. Using semi-structured interviews with six experts, including CEOs and faculty members, key indicators of technological diversification were identified, such as new underwriting software and digital advertising platforms. A 33-item questionnaire was developed based on these insights and distributed to top managers of Iranian insurance companies, with secondary financial data sourced from the Central Insurance of Iran. The study employes regression analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the impact of technological diversification on financial performance, controlling for firm size, debt ratio, and company age. Findings indicate a significant negative relationship between technological diversification and both Return on Equity (ROE) and Return on Assets (ROA), suggesting that the costs of adopting new technologies may outweigh their short-term financial benefits. Additionally, high debt ratios were found to adversely affect ROA, highlighting the financial risks of excessive borrowing.

Keywords: technology; diversification; technological diversification; financial performance; insurance; Iran

JEL Classification: D21; G22; H11; O33

Corresponding author: Seyed Amirhossein Shojaei, Faculty of Business and Management, Muscat University, Muscat, Oman, E-mail: amirhosein.shojaee@yahoo.com

Appendix 1: Technological Diversification Interview Questions

How do you define technological diversification in insurance?
What are its indicators?

Appendix 2: Technological Diversification Questionnaire

#	Statement
1	My company measures risk exposure by software (risk exposure ranks risks according to their probability of occurrence multiplied by the potential loss)
2	My company uses risk prediction modelling and risk analysis
3	My company is using universal underwriting software
4	My company is using technology to have a standard working environment including space, light, etc. to increase efficiency
5	My company uses the capacity of its sister companies or investors (e.g. banks) to sell insurance products
6	My company is using modern technologies in its properties
7	My company’s underwriting software is comprehensive and efficient
8	My company has a unique platform for data sharing with other Iranian insurance companies
9	My company has regular staff training programs for new technologies applied to insurance
10	My company uses start-ups and/or insurance applications widely
11	Research and development is a must for my company
12	My company widely uses expert (not general) loss adjusters for claim handling
13	My company uses multiple sources for data-keeping
14	My company uses “pay as you drive” or “pay based on how you drive” in car insurance
15	My company requires “zip code” as a mandatory field to prevent risk accumulation in a particular geographical area
16	My company uses a call center
17	My company uses virtual classes/meetings nationwide
18	My company widely uses novel methods of approaching new customers, such as pop-up ads on mobile phones, e-mails, etc.
19	My company’s website is frequently updated
20	My company is forced to look after new technologies in insurance by competitive rules or regulations
21	My company is keen to create or write new insurance products
22	My company is willing to enter into other businesses (such as the stock exchange market, banks, and real estate) to make more profit
23	My company widely uses IT as a tool for underwriting as well as claim handling
24	My company uses modern approaches for advertising (such as in-app ads, web-based ads, etc.)
25	My company widely uses specialized experts in different fields (e.g. engineering, medical science, etc.) for risk assessment and claim investigations
26	My company is prevented from using new technologies in insurance
27	My company is willing to customize its unique software
28	My company uses a blockchain approach for data-keeping
29	My company collects enough data and evidence while underwriting a policy to prevent fraud
30	My company widely uses IoT (internet of things) in our insurance industry (e.g., in biometrics, weather sensors, car sensors, etc.)
31	My company widely applies artificial intelligence (i.e., interactive robots or machines) for underwriting or paying claims
32	My company widely uses big data analytics in our actuary calculations
33	My company is willing to outsource some activities such as human resources, finance, and agents to contractors through an automated strategy

Appendix 3: Preliminary CFA Analysis

Figure A1 shows the results of the Confirmatory Factor Analysis (CFA), with all t-values for the 12 retained statements exceeding the 1.96 threshold. This signifies a significant correlation between the latent variable (technological diversification) and the statements listed in Table 2. Consequently, these statements are effective in capturing the extent of technological diversification in Iran’s insurance industry, underscoring their reliability as indicators.

Figure A1:

CFA analysis based on the t-values.

Figure A2 demonstrates Stone-Geisser’s Q2 test for model predictability, a method validated by Singh and Alhamad (2021), Civelek (2018), and Risher and Hair (2017). Positive Q2 values for ROA (0.575) and ROE (0.20) indicate the model’s strong predictive ability, confirming its reliability in estimating performance indicators (Alnsour 2024; GhalichKhani and Hakkak 2016; Henseler, Ringle, and Sinkovics 2009).

Figure A2:

CFA analysis based on CV redundancy.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/apjri-2024-0011).

Received: 2024-04-07

Accepted: 2024-10-04

Published Online: 2024-10-28

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