On the Technical Characteristics of Insurance Operations and Financial Performance of Non-life Insurance Companies in Nigeria.



Olufemi Adebowale Abass1, Sewhenu Francis Dansu2, Yeside Abiodun Oyetayo3



Abstract: The inverse cycle nature of insurance business suggests the adoption of unique firm characteristics upon which its operations rely. These characteristics to a large extent determine risk exposure, underwriting capacity, risk appetite, risk tolerance among others. This study evaluated the impact of these technical characteristics on the financial performance on non-life insurance companies in Nigeria. This study adopted descriptive research design and relied on secondary data of all the non-life companies operating in Nigeria between 2006-2019. Data were gathered from the annual financial statements as contained in NIA, a publication of Nigeria Insurers Association. The study used firm size, premium growth, loss ratio, liquidity, investment, capital adequacy, reserves and underwriting capacity as proxies of technical characteristics while return asset, return on equity and return on investment were used as proxies of financial performance. The results revealed a significant impact of joint technical characteristics variables on the financial performance. Specifically, the study revealed that reserves, shareholders’ fund, firm size, capital adequacy and premium growth are the main technical characteristics that influence the financial performance. The study recommended that non-life insurance companies must constantly monitor their reserves, increase shareholders fund, increase capital base, capital adequacy, and grow their portfolio through premium generation.

Keywords: Firm size; Reserves; Capital Adequacy; Underwriting Capacity; Return on Asset, Return on Equity; Return on Investment.

JEL Classification: G52; M21

1. Introduction

Industries and firms can be distinguished from one another on the basis of financial and non-financial characteristics including size, value, profitability, structure, leverage, liquidity, sales growth, age, customers’ base and so on (Malik, 2011). These characteristics are unique and are directly traceable to the operations of the identified industry (Nyabaga & Matanda, 2020). While most of the characteristics cut across various sectors, there are some characteristics that are peculiar to certain industries. In the same vein, the nature of insurance operation which is hinged on risk transfer, homogeneous exposure, charging of equitable premium among others depend highly on specific technical characteristics. These technical characteristics include size of insurance company, premium growth, loss ratio, liquidity, age of insurance company, shareholders’ fund, solvency, underwriting capacity and reserves. (Burca & Batrinca, 2014; Koc, 2016; Ngwili, 2014; Mazviona & Sakahuhwa, 2017; Poudel, 2019). The management of these characteristics reveal to a large extent capacity of insurance companies to pay claims, ability to stabilize claims ratio and ultimately determine their profitability.

Therefore, this study tends to examine the impact of these technical characteristics on the financial performance of non-life insurance companies in Nigeria.



1.1. Statement of Research Problem

Insurance business stimulates economic activities through reduction in uncertainty, optimal utilisation of capital and protection of financial wellbeing of individuals, group of individuals or organisation (Loomba, 2014; Cristea, Marcu & Carstina, 2014). While these functions had worked adequately in other developed economies, the same cannot be said for Nigeria. For example, contribution of insurance to the Nation’s GDP reduced from 0.41% to 0.31% for 2018 and 2019 respectively (Nigeria Insurers’ Digest, 2020). Moreover, the premium per capita income also declined by 30.08% while insurance penetration reduced to 0.6% for the year 2020 (Salami, 2021). Reasons for the poor performance indicators may not be unconnected to inadequate attention given to the core indices of insurance operations.

More so, Nigerian insurance market has been known to be fragmented with often poor performance. The poor performance had been traced to neglect of core firm characteristics of insurance business (Cenfri, 2018; Abass, 2019). Apart from a few larger and stronger insurers, the market is characterized with a large tail-end of insurers with small balance sheets and often weak business fundamentals. While the expense ratios are high, claims ratios seems to be too low to provide consumer value or too high to attain profitability. For example, the average profit margin for non-life insurance companies in 2018 was 3% (Cenfri Report, 2018).

The ability of the insurance sector to fulfil its role as risk manager in the economy is determined, to a large extent, by the size of its assets. This appears to be limited judging from Nigerian point of view. The industry holds only 2.5% of total financial sector assets (Cenfri Report, 2018).

This study therefore intends to find how technical characteristics (insurance company’s size, premium growth, loss ratio, liquidity, capital adequacy, reserve and investment) of insurance operations affect the financial performance (return on assets, return on equity and return on investment) of non-life insurance companies in Nigeria.



1.2. Statement of Hypotheses

Ho1 There is no significant impact of individual technical characteristics on the financial performance of non-life insurance companies in Nigeria.

Ho2 There is no significant impact of joint effect of technical characteristics on the financial performance of non-life insurance companies in Nigeria.



2. Review of the Literature

Firm characteristics according to Bannier and Hänsel (2008) are the managerial and demographic fickle which are embedded in the internal attributes in a company. The internal attributes according to Malik (2011) can further be sub divided into financial and non-financial variables. While financial variables as the determining factors that are directly driven from items in a balance sheet and profit and loss accounts, the non-financial variables are those factors cannot be driven from the items in the balance sheet and profit and loss accounts.

Relatedly, scholars have argued about the suitability of these firm characteristics across various sectors. The line of argument is based on identified core activities in respective industry.

In lieu of this, technical characteristics of insurance business must be based on its core technical operations (Kozak, 2011; Almajali, Sameer & Yahya, 2012; Charumathi, 2012).

Therefore, core technical characteristics associated to insurance business include; age, size, premium growth, loss ratio, liquidity, investment, capital adequacy, solvency margin, reserves, shareholders’ fund, reinsurance dependence, underwriting capacity and leverage (Pervan & Pavic Kramaric, 2012; Dogan, 2013; Mehari & Aemiro, 2013; Batrinca, 2014; Kaya, 2015; Kozak, 2015; Mazviona, Dube & Sakahuhwa, 2017; Ajao & Ogieriakhi, 2018; Ochingo & Muturi, 2018).

For the purpose of this study, technical characteristics of insurance operations shall be conceptualized into; size of an insurance company, premium growth rate, loss ratio, liquidity, investment, capital adequacy, reserves, underwriting capacity.



2.1. Technical Characteristics of Insurance Operations

Insurance company’s size according to Brown (2009) refers to how large or small firm is, it measures a firm’s market value in relation to its competitors. It enables an organisation obtain a competitive edge over its rivals through the creation of opportunities and cost reduction through economies of scale (Dogan, 2013). Big insurance companies can effectively diversify their assumed risk, possess a greater capacity to deal with adverse market fluctuations and respond quickly to changes in market conditions compared to small insurers (Harwick, 1997; Wyn, 1998). Various studies have linked performance of insurance companies to their size (Malik, 2011; Burca & Batrinca, 2014; Velnampy & Niresh, 2015; Batool & Sahi, 2019).

Premium is the insurance rate and the number of unit power exposure (Abate, 2012). Charging of premium according to Daniel and Tilahun (2013) is expected to cover claim cost (loss ratio), while and other expenses like management expenses, sales expenses, profit of insurer and re-insurance premium. Premium growth is an important technical characteristics of insurance operations because it measures the rate of sales growth, market penetration, profitability in the succeeding year, and measures contribution of insurance to Gross Domestic Product (GDP) and determines the profitability level of insurance companies (Akilo, 2015; Etale, 2011; Burca & Batrinca, 2014; Mehari & Aemiro, 2013; Kozak, 2015; Kaya, 2015).

Loss ratio also known as claims ratio is measured by the ratio of incurred claims to premium earned. It demonstrates the effectiveness of the underwriting activities of insurance companies (Kaya, 2015). Loss ratio reflects the adequacy of insurers underwriting performance and emphasizes the efficiency of the insurer’s underwriting activity (Adam & Buckle, 2003; Burca & Barinca, 2014). Though, there is a divergent view on the relationship between loss ratio and financial performance. While some studies have shown an inverse relationship between loss ratio profitability (Pervan & Visic, 2012; Dogan, 2013; Kaya, 2015), some authors argue otherwise (Burca & Barinca, 2014; Hussaine & Joo, 2019).

Liquidity on the other hand characterizes the ability of an organisation to meet its payment obligations in a short term by using liquid funds at its disposal (Turney & Robbins, 2015). Liquidity from insurance operation’s point of view refers to the capability of an insurer to pay liabilities like operating expenses and payment for losses/benefits under insurance policies (Chen & Wong, 2004). It indicates insurance companies’ ability to finance all its contractual obligations like claims payment, underwriting expenses, claims expenses, reinsurance expenses, investment and maturity of liabilities (Iswatia, 2007). Relationship between liquidity and financial performance of an insurance company has generated debates. While the first dichotomy is based on the risk and return theory which believes liquidity is statistically related to the profitability (Ngwili, 2014; Liu, Shiu & Liu, 2016; Hussaine & Joo, 2019). On the other hand, some related studies showed no statistically significant relationship (Mehari & Aemiro, 2013; Abdeljawad & Dwaikat, 2019; Poudel, 2019).

Investment practice involves the act of sacrificing current money or other resources into different securities for future benefits (Epetimehin, 2014). According to Husain and Nikita (2016), investment practice of insurance companies involves the dispensation that allowed assets into various investments to earn additional revenues. Chui and Kwot (2008) emphasized the importance of investment in the overall operations of insurance companies. Palande, Shah and Lunawat (2013) suggest that insurance companies invest their shareholder’s funds, policyholder’s fund and other temporally available financial resources.

Capital adequacy is the level of capital required by insurance companies to enable them withstand operational risks that they are exposed to in order to absorb the potential loses and protect the policyholders (Nyabaga & Matanda, 2020). It is instrumental to the survival of an insurance company because it generates a good level of profitability (Ikonic et al, 2011). The importance of capital adequacy as one of the major technical attributes of insurance operations had been echoed by Ikonic (2011), Kaya (2013), Too and Simiyu (2018) and Ochingo and Muturi (2018).

Reserve is an amount representing actual or potential liabilities kept by an insurer to cover debts to policyholders. Reserve in insurance is built to guarantee payment of insurance to policyholder (Osadez, 2002). Insurance reserve is formed by an insurance company to ensure future payments insured sums and insurance compensation (Shulieshova, Domanska & Wasilewski, 2015). The need for reserving according to Kneysler (2009) include; delayed and uncertain costs, claims reserving, under requirements and quantum of reserves.

Shareholders’ fund is made up of called up capital which gives an insurance company continuity of ownership and reserves that do not include loan capital. According to Soye and Adeyemo (2018), shareholder’s fund represents a protection net of cushion that allows an insurance company to remain solvent and continue operation despite unexpected disturbance.

Underwriting capacity is the maximum amount of liability that an insurance company agrees to assure from its underwriting activities (Kagan, 2018). It represents an insurer’s ability to retain risk and assume larger unexpected risk (Onaolapo, 2005; Oyetayo & Abass, 2020). Several studies had demonstrated that insurance companies with high underwriting capacity tend to assume more risk, shows insurer’s ability to pay its obligations and possess better financial performance (Mankai & Belgacem, 2013; Burca & Batrinca, 2014; Soye & Adeyemo, 2018; Oyetayo & Abass, 2020).



2.2. Financial Performance

Financial performance refers to the degree to which financial objectives is being or has been accomplished. It shows organisation’s overall financial health over a given period of time (Bhunia, Mukhuti & Roy 2011). Financial performance of business organisation is measured with the use of financial ratios. Abate (2012) defines financial ratios as a class of financial metrics that are used to assess a business’ ability to generate earnings as compared to its expenses and other relevant costs incurred during a specific period of time. Most commonly and widely used financial performance metrics in insurance business are return on asset, return on investment and return on equity (Carton, 2004; Al-Shami, 2008; Malik, 2011; De Villiers, 2012; Delen, Kuzey & Uyar, 2013; Turley & Robbins 2015).



2.3. Measures of Financial Performance

Return on Asset (ROA) reveals how much profit a company earns for its assets (Delen et al, Kuzey & Uyar, 2013). It indicates how profitable a company is relatively to its assets. It gives an idea as to how efficient management is in using its assets to generate earnings. Assets include cash in bank, account receivable, property, equipment, inventory and furniture. The higher the firms return on total assets, the better the firm is.

Return on Equity (ROE) measures overall firm performance. It compares net profit after taxes (minus preferred stock dividend, if any) to the equity that shareholders have invested in the firm (Mankai & Belgacem, 2013). A high return on equity often reflects the firm’s acceptance of strong investment opportunities and return on the ownership interest (shareholder’s equity) of common stakeholders. Therefore, it shows how well a company uses investment funds to generate earnings growth.

Return on Invested Capital (ROIC) measures insurance company’s efficiency in allocating the capital under its control in profitable investment. This metric gives an indication of a company’s actual capacity to generate returns through utilization of its productivity assets. It is expressed in net premium earned from underwriting activities, annual turnover, return on investment and return on equity (Greene & Segal, 2004).



3. Materials and Methods

The study employed descriptive research design. The population of the study comprised forty-one (41) licensed non-life insurance companies operating in Nigeria as at 31st January 2020. Non-life insurance companies are companies that underwrite all risks except risk(s) associated with life. Census sampling technique was adopted using secondary data. Secondary data used for the study covered a fourteen (14) year period from 2006-2019. The data were gathered from the audited annual financial reports of NIA Digest (a self-regulatory body of all insurance and reinsurance companies operating in Nigeria). Data extracted were used as proxies for size of insurance companies, premium growth, loss ratio, liquidity, investment, capital adequacy, reserves, underwriting capacity, return on asset, return on equity and return on investment. Due to inconsistent in raw data, they were transformed using logarithmic transformation of model.

This study formulates a linear panel model of the following form:

(1)

Where is Technical Characteristics

is Financial Performance

Breaking down the independent variable ( ) further into components;

, (1a)

Breaking down the dependent variable ( ) further into component parts;

(1b)

Model Equation

Model 1

Due to inconsistent in raw data, the above models were transformed using logarithmic transformation of model as follows:



Table 1. Variable Measurement

Variable

Measurement

Definition

Expected outcome

Independent

Firm Size

log of total assets)

+/-

Independent

Premium growth (PG)

GPW (New)-GPW (Old)

GPW (Old)

+/-

Independent

Loss Ratio

Net Claim

Net Premium Income

+/-

Independent

Liquidity

Cash and cash equivalent

+/-

Independent

Investment

Financial Assets (Short-term + Long term investment

+/-

Independent

Capital Adequacy

Shareholders’ fund

Net premium earned

+/-

Independent

Share capital

Reserve

+/-

Independent

Shareholders’ fund

Shareholders’ fund

+/-

Independent

Underwriting capacity

Combined ratio + reserve

+/-

Dependent

Return on Assets

Profit after tax

Total Assets

+/-

Dependent

Return on Equity

Profit after Tax (PAT)

Shareholders’ equity

+/-

Dependent

Return on Investment

Profit earned on investment

Cost of Investment

+/-

Table 2. Descriptive Analysis


SC

SF

LIQ

INV

FS

PG

LR

UD

CA

ROA

ROE

ROI

Mean

14.767

15.393

13.039

14.428

15.914

-1.599

-1.474

-0.302

0.949

-3.092

-2.658

2.014

Median

15.035

15.602

13.260

14.828

16.062

-1.521

-1.348

-0.299

0.942

-3.126

-2.610

1.998

Maximum

17.541

17.667

17.106

17.142

19.561

1.257

1.889

4.576

3.079

12.462

0.199

9.248

Minimum

0.000

0.000

0.000

0.000

0.000

-6.316

-6.412

-3.256

-1.944

-8.242

-7.922

-4.336

Std. Dev.

2.121

2.173

2.381

2.324

2.310

1.193

1.016

0.765

0.863

1.510

1.169

1.452

Skewness

-5.922

-6.274

-2.380

-4.316

-5.712

-0.666

-1.057

0.875

0.057

3.726

-0.545

0.808

Kurtosis

41.733

44.730

13.676

26.729

40.103

4.080

7.137

10.672

3.063

42.256

5.521

7.673

Jarque-Bera

19413.110

22469.260

1616.677

7544.401

17834.860

34.790

255.352

732.702

0.199

18892.870

89.290

289.335

Probability

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.905

0.000

0.000

0.000

Sum

4193.875

4371.585

3703.046

4097.427

4519.604

-454.256

-418.676

-85.780

269.481

-878.188

-754.937

572.112

Sum Sq. Dev.

1273.542

1335.832

1604.088

1528.036

1509.498

403.053

291.924

165.723

210.851

645.419

387.062

596.759

Observations

284.000

284.000

284.000

284.000

284.000

284.000

284.000

284.000

284.000

284.000

284.000

284.000

The result of the descriptive statistics in table 2 indicates a normal distribution for variables ROA, ROE and ROI as the probability gives values of 0.0000, 0.0000 and 0.0000 respectively which is lesser than 5%. The standard deviation coefficient of all the variables is positive which implies the level of contribution of the independent’s variables to financial performance of the selected Insurance firms. The level of the data distribution is symmetry to the positive variables while variables show a low kurtosis as they all indicate positive values and higher than one. Kurtosis tend to have heavy tails, or outliers. According to the table above none of the variables sets shows a low kurtosis as they all indicate positive values and higher than one.

Table 3. Correlation Matrix

 

SC

SF

LIQ

INV

FS

PG

LR

UD

CA

ROA

ROE

ROI

sc

1.00

 

 

 

 

 

 

 

 

 

 

 

sf

0.95

1.00

 

 

 

 

 

 

 

 

 

 

lq

0.66

0.67

1.00

 

 

 

 

 

 

 

 

 

in

0.81

0.87

0.56

1.00

 

 

 

 

 

 

 

 

fs

0.93

0.98

0.69

0.87

1.00

 

 

 

 

 

 

 

pg

0.22

0.20

0.28

0.18

0.21

1.00

 

 

 

 

 

 

Lr

0.16

0.21

0.07

0.21

0.22

0.08

1.00

 

 

 

 

 

ud

0.04

0.05

0.07

0.05

0.08

0.02

0.20

1.00

 

 

 

 

ca

0.16

0.22

0.01

0.09

0.10

0.19

0.06

0.34

1.00

 

 

 

roa

0.29

0.24

0.21

0.18

0.24

0.19

0.13

0.05

0.01

1.00

 

 

roe

0.32

0.27

0.12

0.18

0.19

0.15

0.10

0.02

0.27

0.72

1.00

 

roi

0.1144

0.1299

0.1582

0.0168

0.1158

0.1065

0.0405

0.0475

0.0524

0.0835

0.0691

1.0000

Table 3 reveals that return on assets has a negative relationship with share capital, shareholders fund, liquidity, investment, firms’ size and capital adequacy while return on assets as a premium growth, loss ratio and underwriting with investment practice of the selected insurance firms in Nigeria at 0.1946, 0.1263, and 0.0472 respectively.



Table 4. Test of Hypothesis

Dependent Variable: ROA



Method: Panel Least Squares













Variable

Coefficient

Std. Error

t-Statistic

Prob.











SC

-0.462076

0.129897

-3.557264

0.0004

SF

0.400253

0.272484

1.468907

0.1430

UD

0.105148

0.123848

0.849005

0.3966

LR

0.159587

0.087023

1.833845

0.0677

LIQ

-0.009895

0.052300

-0.189192

0.8501

INV

0.053087

0.077741

0.682872

0.4952

FS

-0.123253

0.214590

-0.574362

0.5662

CA

-0.148807

0.136376

-1.091159

0.2761

PG

0.185844

0.076036

2.444167

0.0151

C

-0.406137

0.619415

-0.655679

0.5126











R-squared

0.128948

Mean dependent var

-3.104628

Adjusted R-squared

0.101247

S.D. dependent var

1.509181

S.E. of regression

1.430743

Akaike info criterion

3.587798

Sum squared resid

579.3081

Schwarz criterion

3.713401

Log likelihood

-515.6125

Hannan-Quinn criter.

3.638104

F-statistic

4.654963

Durbin-Watson stat

2.198601

Prob(F-statistic)

0.000009









Table 4 further shows that share capital, premium growth individually has a significant influence ROA at 0.0004 and 0.0151 respectively. Shareholders’ fund, underwriting, loss ratio, liquidity, Investment, that firms’ size, and capital adequacy showed otherwise at 0.1430, 0.3966, 0.0677, 0.8501, 0.4952, 0.5662 and 0.2761 respectively. However, technical characteristics jointly influence ROA at 0.000009.



Table 5. Test of Hypothesis

Dependent Variable: ROE



Method: Panel Least Squares













Variable

Coefficient

Std. Error

t-Statistic

Prob.











SC

-0.450341

0.091201

-4.937897

0.0000

SF

-0.418690

0.190895

-2.193306

0.0291

UD

0.145617

0.086748

1.678633

0.0943

PG

0.145183

0.053252

2.726359

0.0068

LR

0.110674

0.060956

1.815638

0.0705

LIQ

0.019419

0.036663

0.529649

0.5968

INV

0.013759

0.054453

0.252679

0.8007

FS

0.688529

0.150276

4.581767

0.0000

CA

-0.234916

0.095544

-2.458724

0.0145

C

-0.325189

0.433775

-0.749673

0.4541











R-squared

0.286953

Mean dependent var

-2.681312

Adjusted R-squared

0.264197

S.D. dependent var

1.168045

S.E. of regression

1.001937

Akaike info criterion

2.875393

Sum squared resid

283.0934

Schwarz criterion

3.001310

Log likelihood

-409.8074

Hannan-Quinn criter.

2.925830

F-statistic

12.60957

Durbin-Watson stat

1.247894

Prob(F-statistic)

0.000000









Table 5 reveals that share capital, shareholders’ fund, premium growth, firm size, and capital adequacy individually influences return on asset at 0.0000, 0.0291, 0.0068, 0.0000 and 0.0145 respectively. While there is no significant influence of underwriting, loss ratio, liquidity and investment on return on equity at 0.0943, 0.0705, 0.5968 and 0.8007 respectively. However, the table reveal a joint effect of technical characteristics on return on equity at 0.000000.



Table 6. Test of Hypothesis

Dependent Variable: ROI



Method: Panel Least Squares













Variable

Coefficient

Std. Error

t-Statistic

Prob.











SC

-0.202731

0.125173

-1.619604

0.1063

SF

1.257000

0.266886

4.709872

0.0000

UD

0.225825

0.119543

1.889079

0.0597

PG

0.194477

0.070785

2.747428

0.0063

LR

0.091204

0.080714

1.129974

0.2593

LIQ

0.032825

0.051625

0.635833

0.5253

INV

-0.260193

0.073045

-3.562101

0.0004

FS

-0.650270

0.212937

-3.053814

0.0024

CA

-0.639733

0.133826

-4.780320

0.0000

C

0.402823

0.631442

0.637941

0.5240











R-squared

0.117302

Mean dependent var

1.961387

Adjusted R-squared

0.093446

S.D. dependent var

1.539799

S.E. of regression

1.466091

Akaike info criterion

3.631797

Sum squared resid

715.7578

Schwarz criterion

3.743685

Log likelihood

-612.8533

Hannan-Quinn criter.

3.676366

F-statistic

4.916964

Durbin-Watson stat

0.550724

Prob(F-statistic)

0.000003









Table 6 discloses that shareholders’ fund, premium growth, investment, firm’s size and capital adequacy individually influences return on investment at 0.0000, 0.0063, 0.0004, 0.0024 and 0.0000 respectively. Meanwhile, share capital, underwriting, loss ratio and liquidity show no individual significant influence on ROI at 0.1063, 0.0597, 0.2593 and 0.5253 respectively. However, technical characteristics jointly influence return on investment.



4. Discussion of Findings

This study revealed that share capital/ reserve, shareholders’ fund, firm size, capital adequacy and premium growth significantly are major technical operations influence financial performance (return on assets, return on equity and return on investment) of non-life insurance companies in Nigeria. This outcome shares a convergent view Malik (2011), Kaya (2011), Burca and Batrinca (2014), Koc (2016), Too and Simiyu (2018), Efuntade and Akinola (2020), Oyetayo and Abass (2020) and Muema and Abdul (2021). Though, Kaya (2011) and Efuntade and Akinola (2020) in their results suggested loss ratio and liquidity respectively as an important characteristics of insurance operation.

On the other hand, the findings revealed that there is negative and statistical relationship of underwriting capacity, loss ratio, liquidity and investment on the financial performance (return on assets, return on equity and return on investment) of non-life insurance companies in Nigeria. This outcome shares similar view with Batool and Sahi (2019). The finding is at variance with Koc (2016), Burca and Batrinca (2014) and Efuntade and Akinola (2020) especially investment and liquidity.



5. Conclusion and Recommendations

The study examined the individual technical characteristics of insurance operations and joint effect of technical characteristics of insurance operations on the financial performance of non-life insurance companies in Nigeria for a fourteen-year period of 2006-2019. This study further assert the importance of specific firm characteristics to insurance operations. The outcome the regression result revealed joint significant effect of technical characteristics on return on assets, return on equity and return on investment. However, a closer look at the individual characteristics suggests that share capital, shareholders’ fund, firm size, capital adequacy, and premium growth significantly influenced all the financial performance variables (return on assets, return on equity and return on investment). However, loss ratio, and investment showed a weak influence on the financial performance variables with more emphasis on return on investment. However, there is negative influence of underwriting capacity and liquidity on all the financial performance variables.

Hence, major operational characteristics of insurance non-life insurance companies operating in Nigeria are share capital, shareholders’ fund, size of an insurance company, capital adequacy, premium growth, ability to monitor loss ratio and investment proceeds. Hence, non-life insurance business which is short term business compared to life insurance companies must concentrate on building share capital or reserve, must surpass the regulated shareholders’ fund in order to assume more risk and by extension generate increase in premium growth. Moreover, they must continually increase the asset base through diversification either in related or non-related businesses. Attention must also be given to investment income that may help shore up the profitability level. Lastly, net claim must be monitored vis-à-vis net premium income.

References

Abass, O. A. (2019). Empirical analysis of reinsurance dependence on the profitability of general insurance business in Nigeria. Academic Journal of Economic Studies, 5(4), pp. 36–43.

Abate, G. (2012). Factors affecting profitability of insurance company in Ethiopia: panel evidence. Thesis Submitted to the Department of Accounting and Finance Addis Ababa University, Ethiopia.

Abdeljawad, I. & Dwaikat, L. M. (2019). The determinants of profitability of insurance companies in Palestine. Faculty of Economics and Social Sciences. https://repository.najah.edu/bitstream/handle/20.500.11888/14257.

Adam, M. & Buckle, M. (2003). The determinants of operational performance in the Bermuda insurance market. Working Paper, European Business Management School, University of Wales.

Ajao, M. G. & Ogieriakhi, E. (2018). Firm specific factors and performance of insurance firms in Nigeria. Amity Journal of Finance, 3(1), pp. 14-28.

Almajali, A. & Yahya, Z. (2012). Factors affecting the financial performance of Jordanian insurance companies listed at Amman Stock Exchange. Journal of Management Research, 4(2), pp. 266-289.

Al-shami, H. (2008). Determinants of insurance company’s profitability in UAE. Unpublished MSC Thesis, Utara Malaysia University, Kedah, Malaysia. www.ep3.uum.edu.my/256/.

Anand Rathi Wealth Service Limited (2019). Annual report 2018-2019.

Ashraf, S. H. & Singhal, N. (2016). Strategies for long term investment by non-life companies in India. Arabian Journal of Business and Management Review, 6(6), pp. 2-7.

Bannier, C. E. & Hansel, D. N. (2008). Determinants of European banks’ engagement in loan securitization. Conference on the Interaction of market and credit risk, pp. 6-7, 2007, Berlin.

Batool, A. & Sahi, A. (2019). Determinants of financial performance of insurance companies of USA and UK during global financial crisis (2007-2016). International Journal of Accounting Research, 7(194), pp. 01-09.

Bhunia, A.; Mukhuti, S. S. & Roy, S. G. (2011). Financial performance analysis-a case study. Current Research Journal of Social Sciences, 3(3), pp. 269-275.

Burca, A. M. & Batrinca, G. (2014). The demand for reinsurance in the Romanian insurance market. International of Academic Research in Accounting, Finance and Management Sciences, 4(1), pp. 299-308.

Carton, R. B. (2004). Measuring organisational performance: an exploratory study. The University of Georgia, Athens, Georgia. https://getd.libs.uga.edu/pdfs/carton_robert_b_200405_phd.pdf.

Cenfri, (2018). The role of insurance in inclusive growth: Nigeria in brief.

Charumathi, B. (2012). On the determinants of profitability of Indian life insurers- an empirical study, Proceedings of the World Congress on engineering, pp. 978-988, London, 2012 & July. London, UK: ISBN.

Daniel, M. & Tilahun, A. (2013). Firm specific factors that determine insurance company performance in Ethiopia. European Scientific Journal, 9 (10), pp. 245-255.

Delen, D.; Kuzey, C. & Uyar, A. (2013). Measuring firm performance using financial ratios: decision tree approach. Journal of Expert System with Applications, (40), pp. 3970-3983.

Dogan, M. (2013). Does firm size affect the firm profitability. Evidence from Turkey. Research Journal of Finance and Accounting, 4(4), pp. 53-59.

Efuntade, A. O. & Akinola, A. O. (2020). Firm characteristics and financial performance in quoted manufacturing companies in Nigeria. International Journal of Business and Finance Management Research, 7(1), pp. 25-32.

Epetimehin, F. M. (2014) Investment: an index of growth in insurance industry. Jorind 12 (1) June, 2014. www.transcampus.org/journals; www.ajol.info/journals/jorind

Etale, L. M. (2019). Insurance sector development and economic growth in Nigeria: an empirical analysis. International Journal of development and Economics Sustainability, 7(4), pp. 34-48.

Greene, W. & Segal, D. (2004). Profitability and efficiency in the US life insurance industry. Journal Of Productivity Analysis, 21(3), pp. 229-247.

Hardwick, P. (1997). Measuring cost inefficiency in the UK life insurance industry, applied financial economics. Administrative Science Quarterly, 45(1), pp. 81–112.

Harrison, J., Rouse, P. & De Villiers, C. (2012). Accountability and Performance measurement: a stakeholder perspective. Journal of CENTRUM Cathedra, 5 (2), pp. 243-258.

Ikonić, D.; Arsić, N. & Milošević, S. (2011). Growth potential and profitability analysis of insurance companies in the Republic of Serbia. Chinese Business Review, 10(11), pp. 998-1008.

Iswatia, S. & Anshoria, M. (2007). The influence of intellectual capital to financial performance at insurance companies in Jakarta Stock Exchange (JSE), Proceedings of the13th Asia Pacific Management Conference, Melbourne, Australia.

Kaya, O. E. (2015). Capital adequacy in the insurance business and assessment of Turkish insurance sector within the scope of solvency II. Ph.D. Thesis, Gazi University, Ankara, Turkey.

Kneysler O. (2009), Практичні засади управління активами страхової компанії, Scientific notes. Series “Economy”, 12, pp. 224–235.

Koc, I. O. (2016). Determining factors in financial performance of publicly traded insurance companies at Istanbul stock exchange. International Journal of Business and Social Science, 7(11), pp. 169-177.

Kozak, S. (2011). Determinants of profitability of non-life insurance companies In Poland during integration with the European financial system. Electronic Journal of Polish Agricultural Universities, 14(1), pp. 1-9.

Liu, H. H.; Shiu, Y. M. & Liu, T. C. (2016). Reinsurance from the United Kingdom general insurance industry. Geneva Papers on Risk and Insurance Industry, 41(2), pp. 307-324.

Loomba, J. (2014). Risk Management and Insurance Planning. Delhi, India: PHI Learning Private Limited.

Malik, H. (2011). Determinants of insurance companies’ profitability: an analysis of insurance sector of Pakistan, Academic Research International, 1(3), pp. 315-321.

Mankai, S. & Belgacem, A. (2013). Interactions between risk-taking, capital, And reinsurance for property-liability insurance firms. Working Paper No. 2014-154.

Marcu, M. C. & Carstina, S. (2014). The relationship between insurance and economic growth in Romania compared to the main results in Europe-theoretical and empirical analysis. Procedia Economics and Finance, 8, pp. 226-235.

Mazviona, B.; Dube, M. & Sakahuhwa, T. (2017). An analysis of factors affecting the performance of insurance companies in Zimbabwe. Journal of Finance and Investment Analysis, pp. 1-17.

Mehari, D. & Aemiro, T. (2013). Firm specific factors that determine insurance companies’ performance in Ethiopia. European Scientific Journal, 9(10), pp. 245-255.

Muema, F. M. & Abdul, F. (2021). Firm characteristics and financial performance of commercial banks listed on the Nairobi securities exchange. Journal of Economics and Finance, 12(3), pp. 01-13.

Ngwili, K. P. (2014). The relationship between liquidity and profitability of insurance companies in Kenya. A Research Project Submitted in Partial Fulfilment for the award of the degree of Masters of Business Administration. University of Nairobi. http://erepository.uonbi.ac.ke/bitstream/handle/11295/76818/Kiio_The%20relationship%20between%20liquidity%20and%20profitability%20of%20insurance%20companies.pdf.

Nigeria Insurers’ Digest (2020). Nigeria insurance digest. Nigerian Insurers Association; Lagos. Nigeria.

Nyabaga, R. M. & Matanda, J. W. (2020). Effect of firm characteristics on financial performance of listed commercial banks in Kenya. International Journal of Economics and Financial Issues, 10(3), pp. 255-262.

Ochingo & Muturi (2018). Effect of firm characteristics on the financial performance of savings and credit cooperatives society in Kenya, p. 17.

Onaolapo, W. (2005). Imperatives of capital in insurance operations.

Osadez S. (2002). Страхування, tutorial / Ministry of Education and Science of Ukraine. Kyiv National Economic University, Ukrainian financial and banking school, p. 599

Oyetayo, Y. A. & Abass, O. A. (2020). Underwriting capacity and financial performance of non-life insurance in Nigeria. Academic Journal of Economics Studies, 6(2), pp. 73-80.

Palande, P. S., Shah, R. S., Lunawat, M. L. (2003). Insurance in India: Changing policies and emerging opportunities. New Delhi: Response Books.

Pervan, M., &Visic, J. (2012). Influence on firm size on its business success. Croatian Operational Research Review,3, pp. 213-223.

Poudel, B. (2019). Impact of ownership structure on the profitability of Nepalese insurance companies. Nepalese Journal of Business, 6(3), pp. 52-65.

Rynki Finansowe, Ubezpieczenia, 74(2), pp. 533-546.

Shulieshova, I., Domanska, T., & Wasilewski, M. (2015). Insurance reserves of insurance companies in Poland and Ukraine as solvency basis and financial stability of insurance companies. Finanse,

Soye, Y. A. & Adeyemo, D. L. (2018). Underwriting capacity and income of Insurance companies: (a case of Nigeria). International Journal of Innovative Science and Research Technology, 3 (10), pp. 731- 738.

Too, I. C., & Simiyu, E. (2018). Firms’ characteristics and financial performance of general insurance firms in Kenya. International Journal of business Management & Finance, 1(39), pp. 672-689.

Turley, G., & Robbins, G. (2015). A framework to measure financial performance of Local Governments. Retrieved from http://www.tandfonline.com/loi/flgs20.

Velnampy, T. & Niresh, J. (2012). The relationship between capital structure and profitability. Global Journal of Management and Business Research, 12(13), pp. 66-73.

Wyn, J. (1998). The fourth wave, Best’s Review, 99, pp. 53-57.



1 Department of Insurance, Faculty of Management Sciences, Lagos State University, Nigeria, Address: LASU Main Road Ojo Campus, 102101, Lagos, Nigeria, Corresponding author: lollyphem@gmail.com.

2 Department of Insurance, Faculty of Management Sciences, Lagos State University, Nigeria. Address: LASU Main Road Ojo Campus, 102101, Lagos, Nigeria, E-mail: Francisdansu.gmail.com.

3 College of Insurance and Financial Management, Nigeria, Address: KM 40, Lagos Ibadan Express Way, Oloke Torotoro by Asese, Ogun State, Nigeria, E-mail: yesideoyetayocifm@gmail.com.

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