21
Finance, Accounting and Business Analysis
Volume 8 Issue 1, 2026
http://faba.bg/
ISSN 2603-5324
DOI:
https://doi.org/10.37075/FABA.2026.1.03
Credit rating, financial performance, and value of listed insurance
companies in Nigeria
Oluwamayowa Olalekan Iredele
1*
, Haroon Haliyah Ayomide
2
Department of Accounting, University of Lagos, Nigeria
1
Department of Accounting, University of Lagos, Nigeria
2
Info Articles
Abstract
History Article:
Submitted 1 October 2025
Revised 4 February 2026
Accepted 17 April 2026
Purpose: The study determines the association between credit ratings
and key performance indicators, including Return on Assets (ROA),
Return on Equity (ROE), and firm value measured by Tobin’s Q.
Design/Methodology/Approach: The study used secondary data from
six listed insurance firms over five-year period (2020-2024), sourced from
annual reports, stock exchange filings, and rating agency publications. A
panel-least squares regression with fixed effects was employed as the
primary method of analysis alongside descriptive statistics, correlation
analysis, and diagnostic tests, using EViews software.
Findings: Contrary to theoretical predictions from Default Risk Theory
and Signaling Theory, the results reveal that, at 5% level of significance,
credit ratings has a negative and statistically insignificant association
with ROA (β = -0.0023, p = 0.8482), a positive and insignificant
association with ROE (β = 0.0243, p = 0.3245), and a negative
insignificant association with Tobin's Q (β = -0.0649, p = 0.0619). Firm
size consistently demonstrated a positive and significant relationship
with all three performance measures.
Practical Implications: Although credit ratings are essential tools for
financial stability assessment in developed markets, their limited
association with performance indicators in this study suggests that
macroeconomic instability, underdeveloped capital markets, and low
investor awareness of credit ratings in Nigeria may diminish their
effectiveness. This underscores the need for regulatory reforms, investor
education, and market development to enhance the signaling power of
credit ratings in Nigeria's insurance sector.
Originality/Value: The research contributes by filling a knowledge gap
in the literature on credit ratings in developing markets, particularly in
Nigeria’s insurance sector, where prior studies are scarce and often focus
on developed economies
Keywords:
Credit ratings;
Creditworthiness; financial
performance; Value;
Investors; Rating Agency.
JEL: M41.
*
Address Correspondence:
E-mail:
oiredele@unilag.edu.ng
1
Haliyahayomide2@gmail.com
2
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
22
INTRODUCTION
Credit rating is a recent phenomenon in the Nigerian financial sector. Augusto, the first indigenous
rating agency, was licensed in 2001 by the Securities & Exchange Commission (SEC). However, currently,
Nigeria already has three indigenous credit rating agencies (Agusto licensed in 2001, DataPro Limited
licensed in 2020 and, Global Credit Rating Company Limited Nigeria, which is affiliated to Fitch) that
operate within the Nigerian financial sector. Moreover, there are other global rating agencies such as Fitch,
S&P and that evaluate the Nigerian firms’ financial health for global local and global investors. A firm's
credit rating represents a rating agency's assessment of its overall credit worthiness and ability to meet its
financial obligations (Gatzlaff, Jiang, and Li 2019; Sharma, Sharma and Mehta 2018). Credit agencies are
worried about governance because poor governance can harm a company's financial situation and expose
debt stakeholders (hereinafter referred to as insurance policy holders) to losses (Fitch Ratings, 2023). Credit
ratings provide forward-looking assessments on the credit worthiness of issuers and issues. Credit worthiness
refers to an issuer's ability to make timely interest and principal payments in accordance with contractual
terms, but it is not an absolute indicator of default probability (S&P Global Credit Portal 2024).
One of the major participants in Nigeria's financial service industry is the insurance sector. It helps
spread financial losses, facilitate economies of scale in investment, lower transaction costs, increase liquidity,
promote economic growth, and allocate resources efficiently (Deekor 2024; Duniya, Jimoh and Bature 2024;
Horvey, Adjei and Boateng 2024; Fashagba 2018; Fadun and Shoyemi 2018). Life insurers also encourage
investing by providing the means to accumulate personal savings through life and pension contracts
(Tamegawa 2016). In Nigeria, insurance companies are considered the cornerstone of risk management.
Their position is vital since they are the biggest institutional investors in equities, bonds, mutual funds, and
pension funds. Considering the difficulties brought on by globalization and wealth inequality, their influence
on economic growth tends to rise rather than diminish (Fadun and Shoyemi, 2018). Risk management,
essentially an insurance coverage, is inseparable from human activities since risks cannot be disregarded.
The insurance industry is inherently connected to risk, and its purpose is to help individuals return to their
pre-risk positions. The significance of insurance companies in the progress of both developed and developing
nations cannot be overstated, as they have made positive contributions to economic growth (Gatzlaff, et al.
2019). As economic activities continue to expand, the range of risks also increases. Insurance companies
now play a crucial role in preventing sudden and devastating risks faced by individuals and businesses alike.
When an economy remains stable and unaffected by environmental changes, it is considered to have
sustainable development.
Although literature has documented the impact of risk on the financial performance of listed
insurance companies in Nigeria (Duniya et al. 2024; Ogunsola 2024; Bala, Usman and Sani, 2022; Attard,
Gatt and Grech 2021; Abass and Ojikutu 2019), there is limited scholarly research on credit ratings as a
factor in insurers' financial performance. Changes in rating grades could indicate insurance companies'
financial success. A company's current financial status might be reflected by changes in its rating (Shaheen
and Javid 2014). According to Wang and Carson (2014), insurer ratings are widely used to assess financial
stability and bankruptcy risk. However, prior research has mostly concentrated on insurers in developed
nations (Rashid, Amin and Khan 2021; Gatzlaff et al. 2019; Sharma et al. 2018), with such research being
limited in developing countries.
Consequently, this study investigates whether credit ratings have a positive association with financial
performance and market value of listed insurance companies in Nigeria. The study is grounded in default
risk theory and signalling theory, which together suggest that credit ratings convey important information
about a firm's financial health and future prospects, thereby influencing investors’ perception and firm
performance. This research focuses specifically on the Nigerian insurance sector, examining whether credit
ratings serve as effective signals of financial quality in the emerging market context.
LITERATURE REVIEW
Credit Rating
A credit rating is a standardized assessment of an entity's or financial instrument's credit-worthiness.
It serves as an important tool to decide the likelihood of a borrower's financial obligations on agreed-upon
terms. Usually credit rating agencies, which can be of an independent nature, give these assessments, which
are in the form of symbolic grading systems like AAA, AA, A or BBB. The higher the rating, the lesser the
credit risks. Credit ratings are not just for corporations, they are also extended to sovereign states, debtor
financial setups and even on particular form of debts. Their primary role is to decrease the information
asymmetry voltage in the financial market by giving a good base point to investors on which to compare the
risk among the investment options (Geyikci 2023). The process of rating contains quantitative and
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
23
qualitative appraisal. Qualitative assessment is based on the quality of governance, managerial capabilities,
industry structure, and compliance with regulations, as well as broader macroeconomic factors; while
quantitative assessment is based on the quality of governance, managerial capabilities, industry structure,
and compliance with regulations, as well as broader macroeconomic factors. By combining these aspects,
agencies create a complete risk profile that contributes to the final rating.
Table 1. Credit Rating Codes of Major Rating Agencies in Nigeria.
Rating
Agency
Meaning/Description
Agusto & Co.
Highest credit quality; lowest risk of default.
Very high credit quality, slightly lower than AAA.
Strong credit quality, low risk but some sensitivity to adverse
conditions.
Moderate credit quality; financial obligations are still being met but
with more risk.
Speculative grade; some risk of financial instability.
Highly speculative, financial obligations may be difficult to meet.
High default risk, very weak financial condition.
Extremely weak financial position, high probability of default.
Near default, limited ability to meet obligations.
Default; failure to meet financial obligations.
Moody’s
Highest credit quality; minimal credit risk.
Very high credit quality with low credit risk.
Strong creditworthiness but sensitive to economic conditions.
Moderate credit risk; obligations are met, but riskier than A ratings.
Speculative-grade; higher risk of default.
High credit risk, financial obligations are uncertain.
Very high credit risk, high likelihood of default.
Extremely high credit risk, near default status.
In default, minimal recovery is expected.
A.M. Best
Superior financial strength; very low risk.
Excellent financial stability, but slightly lower than A+.
Good financial security, but susceptible to economic changes.
Fair financial security; moderate risk of instability.
Weak financial security; high sensitivity to economic conditions.
Poor financial strength; very high risk of default.
In default; unable to meet financial obligations.
Under regulatory supervision.
In liquidation.
Fitch Ratings
Highest credit rating; exceptionally strong ability to meet obligations.
Very high creditworthiness, but slightly lower than AAA.
Strong financial position but more susceptible to risks.
Moderate credit risk; financial obligations are still stable.
Speculative grade; financial performance is weak.
Highly speculative; financial stability is questionable.
Substantial risk of default.
Very high default risk.
Extremely high probability of default.
In default; financial obligations are not being met.
Source: Agusto, Fitch and AM Best
Credit Rating and the Insurance Sector in Nigeria
Credit ratings are regarded as efficient and comparable measure of financial health and credit
worthiness, widely used by investors, regulators, and corporate managers to. Early empirical research on the
subject such as Horrigan’s (1966) study of U.S. corporate bonds highlighted the importance of ratings in
shaping market perceptions of financial risk. Since then, methodologies have evolved considerably, with
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
24
agencies incorporating increasingly complex models and qualitative judgments into their assessments. In the
Nigerian insurance business, credit ratings are highly relevant because they dictate where various kinds of
capital can be accessed, investment decisions made, and the long-term viability of enterprise sustainability
(Joseph, Akpan and Umoh 2021). Ratings give investors and policy holders an independent view of how
financially strong insurance companies are. They also create economic incentives for these companies to
improve their governance and financial responsibility. This means credit ratings serve diagnostic and
regulatory measurement for the industry. They can help ensure that corporate practices support the overall
stability of the market.
While credit ratings are an important tool for financial stability, there are various difficulties in
realizing these tools in Nigeria. Regulatory and economic limitations, problems associated with
transparency, and anxiety regarding market perception continue to affect the reliability and trustworthiness
of the credit ratings in the insurance sector (Ezeribe and Mgbenwelu 2023). Credit default risk is a crucial
issue for the financial markets and corporate entities as it plays a significant role in the financial stability and
cost of borrowing for firms. Theoretical perspectives have claimed that a higher level of equity risk may
paradoxically coincide with high levels of credit default risk, which has been termed the "distress puzzle"
(Friewald et al. 2014; Chu et al. 2013). This paradox has been explained mostly by degrading economic
conditions which increase defaults risk and cause financial hurts to businesses (Chava and Purnanandam,
2010; Claußen, Hirth and Jäckel, 2017).
Campbell, Hilscher and Szilagyi. (2008) conducted a study which found that financially distressed
stocks have shown an above-average low return from 1981 through to 2006 in the US market. Similarly,
Dichev (1998) showed that firms with high likelihood of bankruptcy tend to perform low in the market,
hence yielding below the average returns. This underperformance has been attributed to inefficient
mechanisms to assess risk and to asymmetric flows of information in financial markets.
Theoretical Framework
The theoretical foundation of this study integrates Default Risk Theory and Signalling Theory to
explain how credit ratings may influence financial performance and firm value in Nigeria's insurance sector.
Default Risk Theory
The Default Risk Theory posits that the credit worthiness of a firm reflects the likelihood of default
on its financial obligations (Merton 1974). A firm with a high probability of default will typically receive a
lower credit rating, indicating elevated risk and limited access to cheap capital. Within the Nigerian context,
where capital markets are still developing, credit ratings thus serve as an essential indicator of financial
stability and long-term solvency (Okafor et al. 2023). Firms with stronger credit ratings tend to enjoy lower
borrowing costs and improved profitability measures such as Return on Assets (ROA) and Return on Equity
(ROE), as these ratings enhance investor confidence and reduce the perceived cost of financial distress.
Signalling Theory
The Signalling Theory complements this view by asserting that a firm’s credit rating transmits
information about its financial quality to external stakeholders (Spence 1973). In imperfect markets,
managers use observable financial outcomes such as stable earnings, consistent dividends, and improved
ratings — to signal their firm’s underlying performance and growth prospects (Connelly et al. 2011).
Consequently, higher credit ratings can be interpreted as positive signals of managerial competence and firm
efficiency, which investors incorporate into market valuation indicators like Tobin’s Q. Thus, credit ratings
serve a dual role: as a measure of default risk and as a strategic signal that shapes investor expectations and
share value.
Integrating these two theories provides a comprehensive framework for analysing the relationship
between credit ratings and firm performance. The Default Risk Theory explains the risk-based assessment
behind rating assignment, while Signalling Theory captures the informational effects that ratings exert on
market perception. Within this framework, the study assumes that credit ratings are both outcomes and
predictors of firm performance. Strong ratings reduce financing costs, leading to higher ROA and ROE,
while simultaneously enhancing market valuation through Tobin’s Q. Conversely, weaker ratings limit
access to affordable capital, constrain profitability, and dampen investor confidence. This theoretical
integration thus underpins the study’s empirical analysis of how variations in credit ratings affect the
operational and market performance of Nigerian manufacturing firms.
Empirical Review
Credit Rating and Financial Performance
The relationship between credit ratings and financial performance has been extensively studied, with
research examining both the determinants of credit ratings and the subsequent effects of ratings on firm’s
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
25
profitability. Adams, Burton, and Hardwick (2003) examined the determinants of credit ratings for UK firms
using a Multinomial Logit Model. They found that firm profitability is positively associated with higher
credit ratings, and that lower financial leverage is a key determinant of better credit ratings. Additionally,
liquidity and cash flow management were found to be critical, as companies with strong liquidity positions
tend to enjoy more favourable credit ratings. Their findings suggest that firms must maintain optimal
financial ratios to facilitate positive ratings from credit rating agencies, with consequent implications for
market credibility, investment appeal, and long-term financial health.
Credit Ratings and Profitability
The reverse relationship, that is, how credit ratings influence subsequent financial performance has
received less attention, particularly in emerging markets. Theoretically, higher credit ratings should improve
access to capital at lower costs, thereby enhancing profitability. However, empirical evidence has been
mixed. Sharma, Sharma and Mehta (2018) conducted a comprehensive review of literature on credit ratings
and financial stability, noting that while developed markets show stronger associations between ratings and
performance, emerging markets exhibit weaker and more inconsistent relationships. They attribute this to
market inefficiencies, weak institutional frameworks, and information asymmetry that persist in developing
economies.
Shaheen and Javid (2014) investigated the impact of credit ratings on firm performance in Pakistan,
an emerging market context similar to Nigeria. Using panel data regression techniques, they found that
credit rating changes had significant impacts on firm performance indicators, with rating upgrades associated
with improved profitability metrics. However, they noted that the strength of this relationship varied
depending on firm size, industry, and macroeconomic conditions. Their study suggests that in emerging
markets, the effectiveness of credit ratings as performance drivers is contingent upon contextual factors.
Usman and Yahaya (2023) examined the relationship between corporate governance and credit ratings in
Nigerian firms, finding that governance quality positively influences credit ratings. Their study provides
important context for understanding how credit ratings are determined in Nigeria, though they did not
explicitly examine the reverse relationship, particularly — how ratings affect performance.
Evidence from the Insurance Sector
Wang and Carson (2014) emphasized that insurer ratings are widely used to assess financial stability
and bankruptcy risk. In their analysis of U.S. insurance companies, they found that credit ratings serve as
important predictors of insurer financial distress and failure. However, their focus was on ratings as
indicators of risk rather than as drivers of performance improvement. Joseph, Akpan and Umoh (2021)
examined credit ratings and investment decision-making in Nigeria's insurance industry. They found that
credit ratings play a role in shaping institutional investment decisions, but noted significant challenges
related to regulatory frameworks, market transparency, and investor awareness that limit the effectiveness
of ratings in the Nigerian context.
The literature suggests that while credit ratings reflect financial performance (with stronger firms
receiving higher ratings), the evidence for a reverse causal relationship—where higher ratings drive improved
performance—is mixed, particularly in emerging markets. In developed economies with efficient capital
markets, higher ratings may reduce financing costs and enhance operational performance. However, in
emerging markets characterized by information asymmetry, weak institutions, and underdeveloped capital
markets, this mechanism may be weak or absent. Furthermore, obtaining and maintaining credit ratings
involves costs (agency fees, compliance expenses, governance investments) that may offset potential benefits,
particularly in markets where ratings do not strongly influence stakeholder behaviour or access to capital. In
Nigeria's insurance sector, regulatory and economic limitations, transparency issues, and low investor
reliance on ratings may further diminish the performance benefits of high credit ratings (Ezeribe and
Mgbenwelu 2023). Given the foregoing, the current study hypothesizes that:
H
1
: There is a statistically positive significant association between credit rating and Return on Assets
(ROA) of the listed insurance companies in Nigeria
H
2
: There is a statistically positive significant association between credit rating and return on equity
of the listed insurance companies in Nigeria
Credit Rating and Value of Firms
A substantial body of research has examined how credit rating announcements and changes affect
firm valuations, primarily through event study methodologies that capture market reactions to rating news.
Evidence from Developed Markets
Early research in developed markets established that credit rating changes have significant market
impacts. Ekstedt and Hammarstrand (2019) analysed differences in the impact of credit rating
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
26
announcements between U.S. and European financial markets. Their results showed stronger market
reactions to rating announcements in the U.S. than in Europe, likely due to higher investor reliance on credit
ratings in the U.S. financial system. Importantly, they found that negative rating changes caused larger
market disruptions than positive changes, reinforcing the notion that bad news has a disproportionate impact
on financial markets compared to good news. This asymmetry suggests that investors are more responsive
to downgrade risk than to upgrade potential.
Evidence from Emerging Markets
Scholarly works on emerging market have yielded more novel findings, suggesting that the
relationship between credit ratings and firm value is context-dependent and often weaker than in developed
markets.
Kenourgios, Umar and Lemonidi (2020) studied the impact of credit rating announcements on
sovereign bonds using global financial data, with particular focus on BRICS and GIIPS countries (which
include several emerging economies). They concluded that sovereign bond yields were highly responsive to
downgrades, particularly in these emerging and vulnerable economies. These findings indicate that bond
markets are especially sensitive to credit rating downgrades, as they signal increased borrowing costs and
heightened risk of financial instability. However, their focus was on sovereign debt rather than corporate
equity valuations.
Geyikci (2023) examined "The Effectiveness of Credit Rating Announcements in the Risk Perception
of Financial Markets in Emerging Economies" using event study methodology. The research found that
credit rating downgrade events had a significant negative impact on stock markets, increasing market
volatility. The results provided evidence that markets tend to react more strongly to negative than to positive
announcements, as downgrades signal financial distress and reduced investor confidence. However, Geyikci
also noted substantial heterogeneity across emerging markets, with some countries showing strong reactions
and others showing muted responses, depending on market development and institutional quality.
Zega, Massie and Tasik (2017) conducted a study on market reactions to Indonesia's Investment
Grade Rating Announcement using event study methodology. Their result showed that positive credit rating
announcements caused short-term increases in stock prices, but the effect diminished over time. This
suggests that although investors initially view credit upgrades favourably, the long-term impact may be
limited unless accompanied by substantial economic improvements. This finding highlights a key challenge
in emerging markets: rating changes may generate temporary sentiment shifts without fundamentally
altering long-term valuations.
Evidence from Insurance Markets
Kjendalen and Torsnes (2022) conducted an empirical study specifically in the European insurance
market, examining the effect of credit rating change announcements on stock prices. Their research
employed an event study approach demonstrating that downgrades had a negative impact on stock prices,
while upgrades had minimal or insignificant positive effects. This asymmetry indicates investor scepticism
toward positive rating changes, possibly due to concerns about the credibility of rating agencies or doubts
about sustained improvements in credit quality. Their focus on the insurance sector is particularly relevant
to the current study, though their European context differs significantly from Nigeria's institutional
environment.
The Distress Puzzle
Theoretical perspectives have identified what has been termed the "distress puzzle"—the paradox that
higher equity risk may coincide with elevated credit default risk (Friewald et al., 2014; Chu et al., 2013).
This paradox has been explained largely by deteriorating economic conditions that simultaneously increase
default risk and harm firm valuations (Chava and Purnanandam 2010; Claußen, Hirth and Jäckel 2017).
Campbell, Hilscher and Szilagyi (2008) found that financially distressed stocks exhibited below-average
returns from 1981 through 2006 in the U.S. market. Similarly, Dichev (1998) showed that firms with high
bankruptcy probability tend to underperform in the market, yielding below-average returns. This
underperformance has been attributed to inefficient risk assessment mechanisms and information
asymmetry in financial markets. These findings suggest that in some contexts, markers of financial distress
(including low credit ratings) may be associated with poor market valuations, though the direction of
causality remains debated.
Research specifically examining credit ratings and firm value in emerging market insurance sectors
remains limited. Rashid, Amin and Khan (2021) examined credit ratings and firm value in emerging
economies more broadly, finding mixed results. They noted that in markets with weak institutional
frameworks and low investor sophistication, credit ratings often fail to serve as effective signals of firm
quality, resulting in weak or inconsistent relationships with market valuations. Gatzlaff, Jiang and Li (2019)
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
27
provided international evidence on credit ratings and firm performance across multiple countries. Their
findings suggested that the relationship between credit ratings and firm value varies substantially across
institutional contexts, with stronger effects observed in countries with well-developed capital markets, strong
rule of law, and high levels of investor protection.
The literature reveals that credit rating changes significantly affect firm valuations in developed
markets, with downgrades typically causing sharp negative reactions and upgrades generating modest
positive responses. However, in emerging markets, these effects are more heterogeneous and often weaker,
reflecting market inefficiencies, institutional constraints, and low investor sophistication.
In Nigeria's context, several factors may further attenuate the relationship between credit ratings and
firm value: (1) underdeveloped capital markets with low liquidity and limited institutional participation; (2)
macroeconomic instability that creates noise and overwhelms rating signals; (3) weak regulatory
enforcement and corporate governance standards that reduce rating credibility; (4) low investor awareness
and understanding of credit ratings; and (5) transparency challenges and perceived conflicts of interest in
rating practices (Ezeribe and Mgbenwelu 2023).
Furthermore, the "distress puzzle" literature suggests that in some contexts, relationships between
credit risk indicators and firm valuations may be non-linear or even counterintuitive. In markets where
information asymmetry is high and risk assessment mechanisms are inefficient, credit ratings may fail to
function as intended signals of firm quality.
Given these considerations and the limited prior research on credit ratings in Nigeria's insurance
sector, this study hypothesizes that:
H
3
: There is a statistically positive significant association between credit rating and value of the listed
insurance companies in Nigeria
METHODS
This study adopts an ex-post facto research design, which is appropriate for examining relationships
using existing data without experimental manipulation. It utilizes secondary data obtained from audited
annual reports of sampled firms and credit rating publications from Agusto & Co., which is the most
established indigenous rating agency in Nigeria. Data were collected for six (6) listed insurance companies
registered on the Nigerian Exchange Group (NGX) over a five-year period from 2020 to 2024, yielding a
balanced panel of 30 firm-year observations.
The rationale for selecting these firms is threefold: (i) they are subject to credit rating evaluation by
recognized rating agencies, (ii) they have publicly available financial reports with consistent disclosure
quality, and (iii) they were actively traded on the NGX during the study period. A purposive sampling
technique was adopted to select firms meeting the following criteria: (a) availability of credit ratings from
Agusto & Co. or A.M. Best for at least five consecutive years, (b) consistent reporting of financial statements
and stock market data without major gaps or restatements, and (c) active trading on the NGX during the
study period. The final sample comprises firms that have been rated for at least five consecutive years from
2020 to 2024, ensuring sufficient data availability for meaningful panel data analysis.
Variable Measurement
Dependent Variables
Three performance indicators serve as dependent variables:
Return on Assets (ROA): Measures operational efficiency and profitability by indicating how
effectively a firm utilizes its assets to generate earnings. It is calculated as Net Income divided by Total
Assets. Higher ROA indicates superior asset utilization and operational performance.
Return on Equity (ROE): Measures shareholder returns by indicating how effectively a firm
generates profit from shareholders' equity. It is calculated as Net Income divided by Total Shareholders'
Equity. Higher ROE indicates better returns to equity investors.
Tobin's Q: Measures market value relative to asset replacement cost, serving as a proxy for firm value
and growth prospects. It is calculated as Market Capitalization divided by Total Assets. A Tobin's Q greater
than 1 suggests that the market values the firm above its asset replacement cost, indicating positive growth
expectations and intangible value.
Independent Variable
Credit Rating (CR): The primary independent variable represents the firm's creditworthiness as
assessed by Agusto & Co., Nigeria's leading indigenous rating agency. Credit ratings are originally assigned
as letter grades (e.g., AAA, AA, A, BBB, BB, B, etc.) following international rating conventions.
For empirical analysis, these ordinal letter grades are converted into numerical values using the
following coding scheme:
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
28
AAA rating = 4 (Highest credit quality; lowest risk of default)
AA rating = 3 (Very high credit quality)
A rating = 2 (Strong credit quality)
BBB and below = 1 (Moderate to high credit risk)
This coding scheme follows conventions established in prior empirical studies (Sharma et al. 2018;
Shaheen and Javid 2014) and allows credit ratings to be incorporated into linear regression models.
However, it is acknowledged that this approach involves treating an ordinal categorical variable as
continuous, which assumes equal intervals between rating categories—an assumption that may not perfectly
hold in practice. As a limitation, this measurement approach may not fully capture non-linear relationships
between rating changes. Future research could employ alternative specifications such as dummy variables
for each rating category or threshold models to address this limitation.
Control Variable
Firm Size (FS): Measured as the natural logarithm of total assets, firm size serves as a control variable
to account for scale effects on financial performance. Larger firms may benefit from economies of scale,
greater market power, diversification advantages, and enhanced access to capital markets. Conversely, they
may face bureaucratic inefficiencies or diseconomies of scale. Controlling for firm size allows the study to
isolate the effect of credit ratings on performance while holding constant the influence of firm scale.
Model Specification
The relationship between credit ratings and financial performance is estimated using the following
panel regression model:







(1)







(2)







(3)
Where:


= Return on Asset of the 6 listed Insurance companies


= Credit Rating of firm at the time


= Firm Size (Natural Log of total asset)


= Return on Asset of the 6 listed insurance companies



(4)
Where:

= Error term capturing unobserved variations for equation
Table 2. Sources and Measurement of Variables
Variable
Definition
Measurement
Source
Credit Rating (CR)
Firm’s creditworthiness
score
Rating agencies' classifications
Agusto & Co., and
A.M. Best
Return on Assets
(ROA)
Profitability indicator
Net income / Total assets
Company financial
reports
Return on Equity
(ROE)
Shareholder returns
Net income / Shareholder
equity
Annual reports,
NGX
Tobin’s Q
Market value vs asset
replacement cost
Market capitalization / Total
assets
NGX, company
filings
Firm Size (FS)
Scale of company
operations
Natural log of total assets
Annual reports
Estimation Method and Diagnostic Tests
Panel least squares regression with both firm and period fixed effects is employed as the primary
estimation method. The inclusion of firm fixed effects controls for unobserved, time-invariant characteristics
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
29
specific to each insurance company (e.g., corporate culture, management quality, historical reputation). The
inclusion of period fixed effects controls for common macroeconomic shocks or regulatory changes affecting
all insurers in a given year (e.g., economic recession, policy reforms, and pandemic effects).
Despite the relatively small sample size (N=30), fixed effects estimation is justified because it
addresses potential omitted variable bias arising from unobserved firm-specific and tiSAXZme-specific
factors that could confound the relationship between credit ratings and performance. The within-firm
variation over time provides sufficient information for estimating the effects of interest.
Some diagnostic tests were conducted to ensure the validity of the regression results:
1. Multicollinearity: Variance Inflation Factors (VIF) were computed to check for multicollinearity
among independent variables. VIF values below 10 indicate acceptable levels of collinearity.
2. Heteroskedasticity: The Breusch-Pagan test was conducted to detect heteroskedasticity in the
residuals. If detected, robust standard errors (White's heteroskedasticity-consistent standard errors) were
applied to ensure valid inference.
3. Serial Correlation: The Durbin-Watson statistic was examined to detect first-order
autocorrelation in the residuals. Values close to 2 suggest no significant autocorrelation.
Limitations
It is important to acknowledge potential endogeneity concerns. Credit ratings may be influenced by
firm performance (reverse causality), as rating agencies consider financial metrics when assigning ratings.
Additionally, unobserved factors (e.g., management quality, strategic initiatives) may simultaneously affect
both credit ratings and performance (omitted variable bias). While fixed effects partially mitigate this
concern by controlling for time-invariant unobserved heterogeneity, they do not fully resolve reverse
causality or time-varying omitted variables. Given these limitations and the observational nature of the data,
the results of this study should be interpreted as associations rather than definitive causal effects. The findings
indicate whether credit ratings are correlated with performance and firm value after controlling for firm size
and fixed effects, but they do not establish that changes in credit ratings causally drive changes in
performance. Future research employing instrumental variable approaches, natural experiments, or quasi-
experimental designs would be valuable for establishing causal relationships.
RESULTS AND DISCUSSIONS
Descriptive Statistics
Table 3. Descriptive Statistics
CR
FIRMSIZE
ROA
ROE
TOBIN_SQ
Mean
1.966667
10.51048
0.074175
0.177616
0.182796
Median
2.000000
10.69538
0.061385
0.154268
0.146662
Maximum
4.000000
11.61949
0.235371
0.446836
0.655633
Minimum
1.000000
0.180448
0.010910
0.023114
0.001286
Std. Dev.
0.889918
2.006121
0.046325
0.096798
0.160838
Skewness
0.363165
-4.750177
1.696835
1.188513
1.233529
Kurtosis
2.037275
25.09718
6.430552
4.168608
4.051128
Jarque-Bera
1.817995
723.1779
29.10711
8.769873
8.989060
Probability
0.402928
0.000000
0.000000
0.012464
0.011170
Sum
59.00000
315.3144
2.225265
5.328494
5.483894
Sum Sq. Dev.
22.96667
116.7111
0.062234
0.271724
0.750195
Observations
30
30
30
30
30
Source: E views Output version 11 (2025)
The mean credit rating of 1.967 (approximately 2.0) indicates that, on average, the sampled insurance
companies hold ratings around the "A" grade level on the numerical scale. The standard deviation of 0.890
suggests moderate variability in credit ratings across firms and over time. Ratings range from a minimum of
1 (BBB or below) to a maximum of 4 (AAA), reflecting heterogeneity in creditworthiness among the sampled
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
30
insurers. The near-normal distribution (skewness = 0.363, kurtosis = 2.037, Jarque-Bera p-value = 0.403)
suggests that credit ratings are approximately symmetrically distributed without extreme outliers.
The mean firm size is 10.510 (natural log of total assets), with a median of 10.695, indicating that
most firms have similar asset sizes. However, the minimum value of 0.180 is notably lower than the mean
and median, suggesting the presence of at least one observation with substantially smaller assets or a
potential data entry issue. The highly negative skewness (-4.750) and extremely high kurtosis (25.097)
indicate a left-skewed distribution with heavy tails, and the Jarque-Bera test strongly rejects normality (p <
0.001). This anomaly warrants further investigation. Upon review, the minimum value appears to be an
outlier, possibly resulting from a data recording error or a firm with exceptionally low assets in a particular
year. To ensure robustness, sensitivity analyses were conducted excluding this observation, and the main
results remained qualitatively similar (results available upon request).
The mean ROA is 0.074 (7.4%), indicating that, on average, sampled insurers generate approximately
7.4 cents of profit for every naira of assets. The median ROA of 0.061 (6.1%) is lower than the mean,
suggesting positive skewness (confirmed by skewness = 1.697). ROA ranges from a minimum of 0.011
(1.1%) to a maximum of 0.235 (23.5%), reflecting considerable variation in operational efficiency across
firms and time periods. The positive skewness and high kurtosis (6.431) indicate that most firms have
relatively low ROA, with a few firms achieving exceptionally high profitability. The Jarque-Bera test rejects
normality (p < 0.001), consistent with the observed skewness and kurtosis.
The mean ROE is 0.178 (17.8%), indicating that, on average, sampled insurers generate
approximately 17.8 cents of profit for every naira of shareholders' equity. The median ROE of 0.154 (15.4%)
is lower than the mean, again suggesting positive skewness (confirmed by skewness = 1.189). ROE ranges
from 0.023 (2.3%) to 0.447 (44.7%), reflecting substantial variation in returns to equity investors. The
distribution is positively skewed and leptokurtic (kurtosis = 4.169), and the Jarque-Bera test rejects normality
(p = 0.012).
The mean Tobin's Q is 0.183, indicating that, on average, the market values sampled insurers at
approximately 18.3% of their asset book value. This suggests that the market, on average, undervalues these
firms relative to their asset replacement costs (Tobin's Q < 1). The median of 0.147 is lower than the mean,
indicating positive skewness (confirmed by skewness = 1.234). Tobin's Q ranges from a minimum of 0.001
to a maximum of 0.656, reflecting wide variation in market valuations. The positive skewness and kurtosis
(4.051) indicate that most firms have low Tobin's Q values, with a few firms approaching higher valuations.
The Jarque-Bera test rejects normality (p = 0.011). The generally low Tobin's Q values (well below 1) suggest
that investors perceive limited growth prospects or assign low intangible value to Nigerian insurance firms,
possibly due to macroeconomic uncertainties, regulatory challenges, or sectorial underdevelopment.
Regression Analysis
Table 4. Model 1: Effect of Credit Rating on Return on Assets (ROA)
Dependent Variable: ROA
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-0.038775
0.033799
-1.147222
0.2663
CR
-0.002277
0.011725
-0.194244
0.8482
FIRMSIZE
0.011173
0.002392
4.671740
0.0002
Effects Specification
Cross-section fixed (dummy variables)
Period fixed (dummy variables)
R-squared
0.875531
Mean dependent var
0.074175
Adjusted R-squared
0.799466
S.D. dependent var
0.046325
S.E. of regression
0.020745
Akaike info criterion
-4.623878
Sum squared resid
0.007746
Schwarz criterion
-4.063399
Log likelihood
81.35816
Hannan-Quinn criter.
-4.444575
F-statistic
11.51038
Durbin-Watson stat
1.748909
Prob(F-statistic)
0.000005
Source: E-views Output version 11 (2025)
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
31
The result on Table 4 indicates that Credit Rating (CR) has a negative but statistically insignificant
association with ROA (β = -0.0023, p = 0.8482). The negative coefficient suggests that, holding firm size
constant, higher credit ratings are weakly associated with lower ROA, though this relationship is not
statistically distinguishable from zero at conventional significance levels (1%, 5%, or 10%). This finding is
counterintuitive from a theoretical perspective, as higher credit ratings are generally expected to signal lower
risk, reduce financing costs, and enhance operational performance. However, the insignificance of the
coefficient implies that credit ratings do not meaningfully explain variation in ROA within this sample.
Firm Size (FIRMSIZE) exhibits a positive and statistically significant association with ROA (β =
0.0112, p = 0.0002). This indicates that larger insurance companies, as measured by total assets, tend to
achieve higher ROA, consistent with economies of scale, operational efficiencies, and greater market power.
The coefficient suggests that a one-unit increase in log (total assets) is associated with an approximate 1.12
percentage point increase in ROA, holding credit rating constant. The model demonstrates strong overall
fit, with an R-squared of 0.8755 and an adjusted R-squared of 0.7995, indicating that the model (including
credit rating, firm size, and fixed effects) explains approximately 80% of the variation in ROA. The F-statistic
of 11.510 (p < 0.0001) confirms that the model is jointly significant, meaning that the explanatory variables
collectively have a statistically meaningful effect on ROA. The Durbin-Watson statistic of 1.749 is close to
2, suggesting no significant first-order autocorrelation in the residuals.
We therefore reject hypothesis H, suggesting a negative insignificant association between credit
ratings and ROA in this context.
Table 5. Model 2: Effect of Credit Rating on Return on Equity (ROE)
Dependent Variable: ROE
Method: Panel Least Squares
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-0.065637
0.069110
-0.949734
0.3548
CR
0.024287
0.023974
1.013072
0.3245
FIRMSIZE
0.018599
0.004890
3.803508
0.0013
Effects Specification
Cross-section fixed (dummy variables)
Period fixed (dummy variables)
R-squared
0.880813
Mean dependent var
0.177616
Adjusted R-squared
0.807976
S.D. dependent var
0.096798
S.E. of regression
0.042417
Akaike info criterion
-3.193351
Sum squared resid
0.032386
Schwarz criterion
-2.632872
Log likelihood
59.90027
Hannan-Quinn criter.
-3.014049
F-statistic
12.09301
Durbin-Watson stat
2.008893
Prob(F-statistic)
0.000004
Source: E views Output version 11 (2025)
The result on Table 5 reveals that Credit Rating (CR) has a positive but statistically insignificant
association with ROE (β = 0.0243, p = 0.3245). The positive coefficient suggests that higher credit ratings
are weakly associated with higher returns to equity, though this relationship is not statistically significant at
conventional levels. This finding is more aligned with theoretical expectations than the ROA result. Higher
credit ratings may enhance investor confidence, reduce equity risk premiums, and improve access to capital,
potentially leading to higher ROE. However, the lack of statistical significance suggests that these
mechanisms are not strongly operative within the Nigerian insurance sector during the study period.
Firm Size (FIRMSIZE) again shows a positive and statistically significant association with ROE (β
= 0.0186, p = 0.0013). This suggests that larger insurance companies achieve higher returns on equity,
potentially due to greater capital efficiency, diversification benefits, or market power. The coefficient
indicates that a one-unit increase in log(total assets) is associated with an approximate 1.86 percentage point
increase in ROE, holding credit rating constant. The model exhibits excellent fit, with an R-squared of
0.8808 and an adjusted R-squared of 0.8080, indicating that approximately 81% of the variation in ROE is
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
32
explained by the model. The F-statistic of 12.093 (p < 0.0001) confirms the model's joint significance. The
Durbin-Watson statistic of 2.009 is very close to 2, suggesting no significant autocorrelation.
Given the positive but insignificant coefficient on credit rating, we reject hypothesis H. While the
direction of the relationship is consistent with theoretical predictions (positive association between credit
ratings and ROE), the lack of statistical significance means we cannot confirm that credit rating has positive
association with return on equity of listed insurance companies in Nigeria.
Table 6. Model 3: Effect of Credit Rating on Firm’s Value (Tobin-Q)
Dependent Variable: TOBIN_SQ
Method: Panel Least Squares
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-0.111344
0.093940
-1.185262
0.2513
CR
-0.064868
0.032587
-1.990581
0.0619
FIRMSIZE
0.040123
0.006647
6.036354
0.0000
Effects Specification
Cross-section fixed (dummy variables)
Period fixed (dummy variables)
R-squared
0.920237
Mean dependent var
0.182796
Adjusted R-squared
0.871494
S.D. dependent var
0.160838
S.E. of regression
0.057657
Akaike info criterion
-2.579442
Sum squared resid
0.059838
Schwarz criterion
-2.018963
Log likelihood
50.69163
Hannan-Quinn criter.
-2.400140
F-statistic
18.87906
Durbin-Watson stat
1.734954
Prob(F-statistic)
0.000000
Source: E views Output version 11 (2025)
Table 6 presents the result for the effect of Credit Rating on firm value, measured by Tobin’s Q. The
results reveal that Credit Rating (CR) has a negative and marginally significant association with Tobin's Q
(β = -0.0649, p = 0.0619). However, at 10% significance level, this coefficient is statistically significant,
indicating a weak inverse relationship between credit ratings and firm value. Specifically, a one-unit increase
in credit rating (e.g., moving from A to AA) is associated with an approximate 6.49 percentage point
decrease in Tobin's Q, holding firm size constant. This finding is highly counterintuitive and challenges
theoretical expectations derived from Signalling Theory and Tobin's Q Theory. According to these theories,
higher credit ratings should signal lower risk and better financial health, thereby increasing investor
confidence and elevating market valuations. The observed negative relationship suggests that, within the
Nigerian context, credit ratings may not function as effective positive signals to equity investors, or that other
factors dominate market valuation decisions.
Firm Size (FIRMSIZE) exhibits a strong positive and statistically significant association with Tobin's
Q (β = 0.0401, p < 0.0001). This indicates that larger insurance firms enjoy higher market valuations relative
to their assets, likely due to greater stability, brand reputation, diversification, and investor confidence. The
coefficient suggests that a one-unit increase in log (total assets) is associated with an approximate 4.01
percentage point increase in Tobin's Q, holding credit rating constant. The model demonstrates excellent
overall fit, with an R-squared of 0.9202 and an adjusted R-squared of 0.8715, indicating that approximately
87% of the variation in Tobin's Q is explained by the model. The F-statistic of 18.879 (p < 0.0001) confirms
the model's strong joint significance. The Durbin-Watson statistic of 1.735 suggests no significant
autocorrelation.
Given the negative and marginally significant coefficient on credit rating (at the 10% level), we reject
hypothesis H. Not only is the relationship statistically significant (albeit marginally), but it is in the opposite
direction to that predicted by theory. Instead of credit ratings having a positive effect on firm value, the
evidence suggests a negative association. This counterintuitive finding directly contradicts the predictions of
Signalling Theory and Tobin's Q Theory, and warrants careful interpretation in light of Nigeria's institutional
and market context.
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
33
Discussion of Findings
This study set out to investigate whether credit ratings have positive association with financial
performance and market value of listed insurance companies in Nigeria, anchored on Default Risk Theory
and Signalling Theory. These theories predict that higher credit ratings should positively influence firm
performance and market valuation by signalling lower risk, reducing financing costs, and enhancing
stakeholder confidence. However, the empirical evidence from this study does not support these theoretical
predictions and vice versa.
The regression results show a negative but statistically insignificant association between credit ratings
and ROA, leading to the rejection of H (which predicted a significant positive effect). This indicates that
variations in firms' creditworthiness, as assessed by rating agencies, do not significantly explain differences
in operational efficiency, and certainly not in the positive direction predicted by theory. The negative sign,
though not statistically significant, may reflect the costs associated with obtaining and maintaining credit
ratings, including fees paid to agencies, compliance costs, and governance investments required to achieve
higher ratings. These costs may offset any operational benefits in the short to medium term, particularly in
a market where credit ratings do not strongly influence customer acquisition, pricing power, or competitive
positioning. From the perspective of Default Risk Theory and Signalling Theory, which posit that positive
signals (such as favourable credit ratings) should encourage stakeholder confidence and improve
performance, this finding is counterintuitive. However, it reflects structural characteristics of the Nigerian
insurance sector, including low insurance penetration, regulatory rigidity, weak financial intermediation,
and limited integration with capital markets. These factors may dilute the signalling power of credit ratings,
preventing them from translating into tangible operational improvements.
Credit ratings exhibit a positive but statistically insignificant association with ROE. Theoretically,
creditworthy firms should benefit from lower financing costs, enhanced investor trust, and improved access
to capital, which could boost returns to shareholders. The positive sign is consistent with this expectation,
but the lack of statistical significance indicates that this mechanism is weak or inconsistent within the
Nigerian context. Several factors may explain this finding. First, the Nigerian equity market for insurance
firms is relatively underdeveloped, with low trading volumes, limited institutional investor participation,
and weak integration with international capital markets. Second, many Nigerian insurance companies
remain closely held or family-owned, with concentrated equity structures that limit the role of public equity
markets in capital allocation and valuation. Third, weak corporate governance, limited disclosure
transparency, and low investor sophistication may reduce the credibility and influence of credit ratings on
equity returns. According to Oduware and Owoputi (2021), the Nigerian capital market has yet to fully
internalize credit ratings in pricing equity risk or allocating capital, especially in the insurance sub-sector.
The most striking finding is the negative and marginally significant association between credit ratings
and Tobin's Q. This result directly challenges theoretical predictions from Signalling Theory and Tobin's Q
Theory, which suggest that higher credit ratings should elevate market valuations by conveying positive
information about creditworthiness and future prospects. Several explanations may account for this
paradoxical finding. Nigeria's equity market for insurance firms is characterized by thin trading, low
liquidity, limited analyst coverage, and weak price discovery mechanisms. In such an environment, credit
ratings may not be efficiently incorporated into stock prices, or they may even be misinterpreted by
unsophisticated investors. Firms with higher credit ratings may be subject to stricter governance standards,
more conservative financial policies, and higher capital requirements imposed by regulators or rating
agencies. While these measures enhance financial stability, they may constrain growth, limit risk-taking, and
reduce short-term profitability, thereby depressing market valuations.
Firms experiencing low market valuations may proactively seek higher credit ratings as a
compensatory mechanism to signal stability and attract investment. This reverse relationship could generate
a spurious negative correlation between ratings and Tobin's Q. Persistent macroeconomic instability
(inflation, exchange rate volatility, political uncertainty) and weak institutional quality (poor contract
enforcement, regulatory unpredictability) may dominate investor perceptions, overshadowing credit rating
signals and reducing their influence on valuations. Empirical evidence suggests that Nigerian investors, both
retail and institutional, may have limited awareness, understanding, or trust in credit ratings. As noted by
Ezeribe and Mgbenwelu (2023), transparency challenges and perceived conflicts of interest in rating
practices further erode confidence in ratings.
Across all three models, firm size emerges as a consistently strong and positive predictor of financial
performance and firm value. Larger insurance companies enjoy higher ROA, higher ROE, and higher
Tobin's Q, likely due to economies of scale, diversification benefits, enhanced market power, better access
to capital, and greater brand credibility. This finding is consistent with prior empirical literature such as
Attard, Gatt and Grech 2021) and underscores the importance of scale in driving competitive advantage in
Nigeria's insurance sector.
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
34
Overall, the findings suggest that the Nigerian insurance sector operates in a financial environment
where credit ratings function more as regulatory compliance tools or external certifications rather than as
strategic instruments that meaningfully influence operational performance or market valuations. These
findings are consistent with broader evidence from emerging markets, where credit ratings often exhibit
weaker associations with firm performance and valuations compared to developed markets (Rashid, Amin
and Khan 2021; Oduware and Owoputi 2021).
CONCLUSION AND RECOMMENDATIONS
This study examined the association between credit ratings and financial performance (measured by
ROA and ROE) and firm value (measured by Tobin's Q) of six listed insurance companies in Nigeria over
the period 2020-2024. Grounded in Default Risk Theory and Signalling Theory, the study hypothesized that
credit ratings would serve as credible signals of creditworthiness, thereby positively influencing performance
and market valuations. However, the empirical findings provide limited support for these theoretical
predictions. The results reveal that credit ratings have a negative but statistically insignificant association
with ROA (β = -0.0023, p = 0.8482), a positive but statistically insignificant association with ROE (β =
0.0243, p = 0.3245), and a marginally significant negative association with Tobin's Q (β = -0.0649, p =
0.0619 at the 10% level). In contrast, firm size consistently demonstrates strong positive and significant
relationships with all three performance indicators, highlighting the importance of scale in Nigeria's
insurance sector. These findings suggest that credit ratings do not function as effective strategic tools for
enhancing financial performance or market value within Nigeria's insurance sector during the study period.
Instead, credit ratings appear to serve primarily as regulatory compliance mechanisms or external
certifications, with limited influence on operational outcomes or investor perceptions.
In enhancing the place of credit ratings on the financial performance of listed insurance companies in
Nigeria, regulatory bodies such as the National Insurance Commission (NAICOM) and the Securities and
Exchange Commission (SEC) must move beyond mere compliance. Equally, there is need for better
understanding of the markets and higher levels of investor education with regard to the role and importance
of credit ratings. Professional associations such as the Nigerian Insurers Association (NIA) and the
Chartered Insurance Institute of Nigeria (CIIN) should be in the forefront in organising awareness
programmes, workshops and briefing sessions in the industry to help in chipping up the investor confidence
in the results of credit rating. A stable macroeconomic environment will enhance the predictive power of
ratings and allow them to be more useful to market participants attempting to make investment and financial
decisions.
Acknowledgments
Authors acknowledge the support of Agusto & Co. for providing credit rating data for the research
Funding
This research received no funding from any source
Data Available Statement
The data that support the findings of this study are available from the corresponding author [Oluwamayowa
Olalekan Iredele] upon request.
Conflict of interest
The authors declare no conflict of interest.
AI Tools Statement
AI-based language editing tools were used to improve grammar and clarity. All intellectual content,
interpretation, and conclusions are solely the responsibility of the authors.
Author contribution
• Conceptualization: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Methodology: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Software: Haroon Haliyah Ayomide
• Validation: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Formal analysis: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Investigation: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Resources: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Data curation: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Writing – original draft: Haroon Haliyah Ayomide
• Writing – review & editing: Oluwamayowa Olalekan Iredele and Haroon Haliyah Ayomide
• Visualization: Haroon Haliyah Ayomide
• Supervision: Oluwamayowa Olalekan Iredele
• Project administration: Oluwamayowa Olalekan Iredele
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
35
• Funding acquisition: N/A
REFERENCES
Abass, O., and O. Ojikutu. 2019. Risk management and financial performance of insurance firms in Nigeria.
Journal of Finance and Accounting Research, 11(2): 55–68.
Adams, M., B. Burton, and P. Hardwick. 2003. Factors influencing credit ratings in the UK insurance sector,
(Working Paper No. 19). Bournemouth University, School of Finance & Law.
Attard, M., W. Gatt, and A. Grech. 2021. Financial performance drivers of insurance companies in
emerging markets, International Journal of Financial Studies. 9(4): 1–18.
https://doi.org/10.3390/ijfs9040066
Bala, U., A. Usman, and A. Sani. 2022. Enterprise risk management and financial performance of listed
insurance companies in Nigeria. Journal of Contemporary Research in Business and Social Sciences, 6(3):
25–38.
Campbell, J. Y., J. Hilscher, and J. Szilagyi. 2008. In search of distress risk. The Journal of Finance, 63(6):
2899–2939. https://doi.org/10.1111/j.1540-6261.2008.01416.x
Chava, S., and A. Purnanandam. 2010. Is default risk negatively related to stock returns? The Review of
Financial Studies, 23(6): 2523–2559. https://doi.org/10.1093/rfs/hhq024
Chu, Y., G. Tian, and J. Wu. 2013. Credit ratings and default risk: Evidence from China. China Journal of
Accounting Research, 6(1): 1–15. https://doi.org/10.1016/j.cjar.2012.10.001
Claußen, C., S. Hirth, and J.F. Jäckel. 2017. The distress puzzle: Evidence from the German stock market.
Journal of Banking & Finance, 78: 42–57. https://doi.org/10.1016/j.jbankfin.2017.01.004
Deekor, E. 2024. Insurance and economic development in emerging markets. Journal of Business and Economic
Development, 12(1): 15–28.
Dichev, I. D. 1998. Is the risk of bankruptcy a systematic risk? The Journal of Finance, 53(3): 1131–1147.
https://doi.org/10.1111/0022-1082.00046
Duniya, A., S. Jimoh, and M. Bature. 2024. Risk exposure and financial sustainability of insurance firms in
Nigeria. African Journal of Accounting, Auditing and Finance, 13(2): 201–220.
Ekstedt, E. and H. Hammarstrand. 2019. The effect of credit rating announcements on financial markets: A
comparative study between the US and European markets”. Lund University Student Papers, 17(1): 1–
40. Available at: Lund University
Ezeribe, C., and C. Mgbenwelu. 2023. Transparency challenges in credit rating practices of Nigerian
insurers”. Nigerian Journal of Management Studies, 39(1): 73–90.
Fadun, O. S., and O. Shoyemi, O. 2018. Risk management and performance of insurance companies in
Nigeria”. International Journal of Business and Finance Management Research, 6: 47–55.
Fashagba, M. (2018). Insurance penetration and economic growth in Nigeria. Journal of Economics and
Finance, 9(2): 11–19.
Fitch Ratings. 2023. Insurance rating criteria, Fitch Ratings. https://www.fitchratings.com
Friewald, N., C. Wagner, and J. Zechner. 2014. The cross-section of credit risk premia and equity returns.
The Journal of Finance, 69(6): 2419–2469. https://doi.org/10.1111/jofi.12143
Gatzlaff, K. M., W. Jiang, W., J. Li. 2019. Credit ratings and firm performance: International evidence.
Journal of International Financial Markets, Institutions and Money, 63: 101136.
https://doi.org/10.1016/j.intfin.2019.101136
Geyikci, U. B. 2023. Credit ratings and information asymmetry in financial markets”. Journal of Risk and
Financial Management, 16(2): 105–119. https://doi.org/10.3390/jrfm16020105
Horvey, K., E. Adjei, and P. Boateng. 2024. Insurance sector contribution to economic resilience in West
Africa. West African Journal of Financial Studies, 8(1): 65–80.
Joseph, O., E. Akpan, E., and S. Umoh. 2021. Credit ratings and investment decision-making in Nigeria’s
insurance industry. Journal of Insurance and Risk Management, 16(3): 88–104.
Kenourgios, D., Z. Umar, and P. Lemonidi. 2020. On the effect of credit rating announcements on sovereign
bonds: International evidence. International Economics, 162: 28–42. doi: 10.1016/j.inteco.2019.11.002
Kjendalen, S. and O. K. Torsnes. 2022. Impact of credit rating changes: An empirical study of the stock
market reaction to credit rating change announcements in the European insurance market. NHH
Working Papers. Available at: NHH Open Access
Oduware, A., and J. Owoputi. 2021. Credit ratings and equity risk pricing in emerging markets: Evidence
from Nigeria. Journal of African Financial Studies, 5(2): 145–160.
Ogunsola, O. 2024. Risk governance and profitability of insurance firms in Nigeria. Nigerian Journal of
Business Administration, 24(1): 100–115.
Rashid, A., S. Amin, and S. Khan. 2021. Credit ratings and firm value: Evidence from emerging economies.
O. O. Iredele and H.H. Ayomide/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026.
36
Cogent Economics & Finance, 9(1): 1912537. https://doi.org/10.1080/23322039.2021.1912537
S&P Global. 2024. Understanding credit ratings, S&P Global Ratings. https://www.spglobal.com
Shaheen, S., and A. Y. Javid. 2014. Impact of credit ratings on firm performance: Evidence from Pakistan.
Pakistan Development Review, 53(2): 179–202.
Sharma, A., R. Sharma, and S. Mehta. 2018. Credit ratings and financial stability: A review of literature.
Global Business Review, 19(6): 1525–1544. https://doi.org/10.1177/0972150918788745
Tamegawa, K. 2016. Life insurance and household savings: Evidence from Japan. Journal of Risk and
Insurance, 83(2): 361–388. https://doi.org/10.1111/jori.12059
Usman, A. and A. Yahaya. 2023. The relationship between corporate governance and credit ratings in
Nigerian firms: An empirical analysis. Journal of Emerging Market Finance, 22(1): 55–77. doi:
10.1177/09726527231122890
Wang, S., and J. Carson. 2014. Rating agencies and the financial stability of insurers. Journal of Insurance
Regulation, 33(3): 1–27.
Zega, E., J.D.D Massie, and H. H. D. Tasik. 2017. The effect of credit rating announcements on market
reaction: Evidence from Indonesia Investment Grade rating. Economic Management and Business
Accounting Journal, 5(3): 89–105. doi: 10.35794/emba.5.3.2017.18254