Assessing the Technical Efficiency of Traditional and Corporate Agents in Indian Life Insurance Industry: Slack-based Data Envelopment Analysis Approach

Shetty, Ankitha; Basri, Savitha

doi:10.1177/0972150917749722

Cited by 10 publications

(5 citation statements)

References 37 publications

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“…To the authors' best knowledge, there are 22 studies on the specific case of the Indian insurance sector. Among these 22 studies, Tone and Sahoo (2005), Sinha (2007aSinha ( , 2012Sinha ( , 2015, Sinha and Chatterjee (2009), Dutta and Sengupta (2011), Chakraborty et al (2013), Chakraborty (2016a), Parida and Acharya (2017), Anandarao et al (2018), Shetty and Basri (2018) and Savitha et al (2019) focussed on the life insurance sector. Sinha (2007bSinha ( , 2017a Mandal and Dastidar (2014), Bawa and Kaur (2014) and Chakraborty (2016bChakraborty ( , 2018 zeroed in on the nonlife insurance sector.…”

Section: Related Literaturementioning

confidence: 99%

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An empirical investigation of efficiency and productivity in the Indian non-life insurance market

Ilyas

Rajasekaran

2019

BIJ

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Purpose The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of efficiency, productivity and returns-to-scale economies. In addition to this, it identifies the determinants of efficiency. Design/methodology/approach This study employs a two-stage data envelopment analysis (DEA) bootstrap approach to estimate the level and determinants of efficiency. In the first stage, the DEA bootstrap approach is employed to estimate bias-corrected efficiency scores. In the second stage, the truncated bootstrapped regression is used to identify the effect of firm-level characteristics on the efficiency of insurers. Moreover, the bootstrapped Malmquist index is used to examine the productivity growth over the observation period 2005–2016. Findings The bootstrapped DEA results show that the Indian non-life insurance sector is moderately technical, scale, cost and allocative efficient, and there is a large opportunity for improvement. Moreover, the results reveal that the public insurers are more cost efficient than the private insurers. It is also evident that all the insurers irrespective of size and ownership type are operating under increasing returns to scale. Malmquist index results divulge an improvement in productivity of insurers, which is attributable to the employment of the best available technology. Bootstrapped DEA and bootstrapped Malmquist index results also show that the global financial crisis of 2008 has not severely affected the efficiency and productivity of the Indian non-life insurance sector. The truncated regression results spell that size and reinsurance have a statistically significant negative relationship with efficiency. It also shows a statistically significant positive age–efficiency relationship. Practical implications The results hold practical implications for the regulators, policy makers, practitioners and decision makers of the Indian non-life insurance companies. Originality/value This study is the first of its kind that comprehensively investigates different types of robust efficiency measures, determinants of efficiency, productivity growth and returns-to-scale economies in the Indian non-life insurance market for an extended time period.

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Section: Related Literaturementioning

confidence: 99%

“…Besides, it found that the mean productivity growth of the private insurers is higher than the public insurers. Shetty and Basri (2018) utilised DEA to assess efficiency of traditional individual agents and corporate agents in the life insurance market. The study uses the panel data set of 12 life insurers for the period 2012-2016.…”

Section: Related Literaturementioning

confidence: 99%

An empirical investigation of efficiency and productivity in the Indian non-life insurance market

Ilyas

Rajasekaran

2019

BIJ

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“…Because millions of insurers, healthcare providers, patients, and consumers are involved in the insurance ecosystem (Shetty & Basri, 2017), it is easy for the industry to get hindered by money-and time-wasting inefficiencies resulting from billions of forms, human error and poor coordination between parties (Shetty & Basri, 2020).…”

Section: Fidentiaxmentioning

confidence: 99%

Block Chain Application in Insurance Services: A Systematic Review of the Evidence

et al. 2022

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The Insurance industry participates in various processes that are characterized by data exchange, which is modified or updated by many parties. Hence, the insurance industry can benefit from the adoption of blockchain technology. However, there is a lack of understanding of the technology, the legal implications and the issues in implementing the technology. This paper aims at finding potential opportunities for the insurance sector on the implementation of blockchain technology. It also discusses issues and concerns for insurance companies wanting to adopt block chain technologies. A search was carried out for relevant electronic bibliographic databases (searched by means of keywords), articles published in scientific journals, websites of consultancy firms and blockchain developers, and reference lists of relevant review articles. Articles were screened and eligibility was based on participants, procedures, interventions comparisons, outcomes (PICO) model and criteria for PRISMA (Preferred Reporting Items for Systematic Reviews). A total of 23 papers were finalized after scrutiny for this study whereby the results disclose that blockchain, as a single source of reality, has the potential to improve productivity and mitigate the complexity of the insurance processes. Examples of real-world applications and insurance use cases are presented to demonstrate the strengths & capabilities of the technology. This study also considers the present-day issues, risks and concerns in the implementation of the blockchain technology. Finally, the challenges and obstacles in the application of Blockchain technology in the Insurance Sector is highlighted and presented.

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“…Anandarao et al (2019) reported that ICICI Prudential Life Insurance, Shriram Life Insurance and Tata AIA Life Insurance rank first in the overall efficiency along with LIC. Shetty and Basri (2020) divulged that there was no significant difference in the efficiency scores of traditional and corporate agents. Roy and Saha (2018) too observed that the LIC was the only efficient company.…”

Section: Review Of Literaturementioning

confidence: 99%

Revenue efficiency evaluation of life insurance companies in India: identification of leaders and laggards

Bhatia

Mahendru²

2021

BIJ

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PurposeThe purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.Design/methodology/approachRevenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.FindingsThe empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.Originality/valueAs per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.

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Assessing the Technical Efficiency of Traditional and Corporate Agents in Indian Life Insurance Industry: Slack-based Data Envelopment Analysis Approach

Cited by 10 publications

References 37 publications

An empirical investigation of efficiency and productivity in the Indian non-life insurance market

An empirical investigation of efficiency and productivity in the Indian non-life insurance market

Block Chain Application in Insurance Services: A Systematic Review of the Evidence

Revenue efficiency evaluation of life insurance companies in India: identification of leaders and laggards

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