Effects of financial risk management...

WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-OCTOBER 2013 EDITION

Journal of Economics & Finance (JEF)

October 2013 VOL.1, No.8

Effects of Financial Risk Management on the Financial Performance
of Kenya Power: Emphasis on Credit Risk
Joseph N. Amambia (Corresponding author), Aquilars Kalio, Josephat Kwasira
Jomo Kenyatta University of Agriculture and Technology, Nakuru Town Campus, Kenya.
Postal address: Box 12019 – 00400 Tom Mboya, Nairobi, Kenya
Accepted 17 October 2013
Abstarct
Over time, the auditing process has evolved from a bloodhound approach to a risk based approach. Whereas in
the first approach organisations would look at a risk after its occurrence, the risk based approach aims to contain
and control risks thereby preventing their occurrence. This case study examined the effects of financial risk
management on the financial performance of Kenya Power, with special emphasis on credit risk. The study
adopted descriptive and inferential research designs to establish whether there’s a link between credit risk
management as an offshoot of financial risk management and an organisations financial performance. It
considered a population of 150 management staff of Kenya Power finance division, to whom 108 online survey
questionnaires were mailed out, with feedback being obtained from 87 respondents in helping to capture the
depth of credit risk management practice and its effects on the organization’s financial performance. Data was
then analysed using frequencies, percentages, mean, analysis of variance and spearman’s correlation coefficients
in determining how independent and dependent variables related. The study revealed that credit risk management
has a significant effect on the profitability of Kenya Power and also that credit risk management has a significant
effect on the liquidity position of Kenya Power. This case study of Kenya Power therefore concluded that the
practice of credit risk management as part of financial risk management is essential for any organisation that
wishes to post a positive financial performance. In its recommendation, the study ended up underscoring the
importance of inculcating credit risk management practices in any organisation that aspires to have a sound
financial performance. A further recommendation is that Kenya Power needs to concentrate more effort on the
existing policies it has in place towards minimising or eradicating vandalism of its equipment if it is to realise
further growth in its financial performance.
Key Words: Credit Risk management, Financial Performance, Kenya Power
1. Introduction
D’arcy (2001) postulates that Risk management originated and was developed by two innovative insurance
professors in the 1950’s, i.e. Mehr and Hedges. Organisations started taking note of financial risk management
when their performance was adversely affected in the 1970’s, by an OPEC decision to reduce oil production in
order to increase prices. This caused instability in exchange rates and a surge of inflation rates, (D’Arcy 2001;
Skipper & Kwon 2007). It is in the 1990’s however, that organisations took serious cognisance of the need for
337


financial risk management. As managers started retrieving information on risk and risk management techniques,
the practice moved slowly away from hazard risk (insurance) to include financial risk, operational risk, and
strategic risk, (Skipper & Kwon 2007). The need for financial risk management practice became more
pronounced in the last decade following the serious corporate financial scandals witnessed in organisations like
Enron, World com, Polly peck and Parmalat, (Benson et al., 2003). This is when it dawned on organisations that
the implementation of risk management is not only a preserve of insurance or financial sectors but to all
organisations globally.
Learning to manage risk is a key component of any successful company, especially in uncertain economic
times. By understanding risk factors, managers can better allocate capital and other resources since business
executives are charged with making risk recommendations to the boards and investors. If handled well, financial
risk management can contribute to an organization’s ability to safeguard its assets, use its resources economically
and efficiently, and produce accurate and reliable financial information that is important in developing a
complete and accurate picture of organisational performance. One can analyse risk by comparing and contrasting
business and financial risks. (Guzman 2012) Business risk (more of systematic risk which affects every business
operating in the same market) involves a company’s strategic decisions other than finance. It measures the
dangers of operational choices, such as response to competition from other firms, entering a new product line or
business sector. A measure of internal efficiency as contributing to production meeting desired quotas is a key
determinant of business risk.
Financial risk (more of an unsystematic risk that depends on the day to day strategic, management and
investment decisions) management on the other hand examines how a company’s finances are structured.
Financial risk involves the use of corporate debt and stock issuance. It is this risk, specifically credit risk that is
therefore mostly shifted to shareholders who invest in a company’s debt or stocks. Billett et al., (2007) suggested
that the relationship between growth opportunities and leverage (debt) is negative because firms issue equity
when stock prices are high. Credit risk refers to the chance a business’s cash flows are not enough to pay
creditors and fulfil other financial responsibilities. The level of credit risk, therefore, relates less to the business
operations themselves and more to the amount of debt a business incurs to finance those operations. The more
debt a business owes, the more likely it is to default on its financial obligations. Taking on higher levels of debt
or financial liability therefore increases a business’s level of credit risk as is the case for Kenya Power. This study
sets out to test the theory that a business’s exposure to risk as is the case for Kenya Power, negatively relates to
its worth and that for a business to succeed and maximise its value, it must reduce and cut down on risks.
In early 2000’s, the Kenya Power experienced tremendous financial constraints that led to remedial
measures like staff retrenchment and cost cutting. This culminated in the hiring of an expatriate team of
Canadian managers from Manitoba Hydro Management in 2006 to try and turn around the organisation, (Kenya
Engineer 2007). Some corrective measures instituted to safeguard against future recurrence of these constraints
included a strong emphasis on the practice of credit risk management. It was then expected that Kenya Power’s
financial performance would change for the better. However some indicators in the recently published and
audited annual financial statements for the year ended 30th June 2012 show that the organization may not be on a
sound footing financially. This study provides an insight into the financial performance of Kenya Power and the
extent to which this is affected by management of credit risks. Findings of this study will go a long way in
informing the opinions and arguments fronted by finance practitioners. Kenya Power and other organisations on
the other hand, will gain knowledge and insight on the need to strengthen their credit risk management practices,
owing to their impact on financial performance. Similarly, credit reference bureaus may refer to this study in
rating the creditworthiness of prospective borrowers. Organisational stakeholders including shareholders,
338


creditors, bankers, management, staff, and prospective investors among others, will also find this study useful,
since it might help them in gauging the performance of organisations. Lastly, findings of this study will help in
filling in a gap in the field of finance by adding onto the existing knowledge on credit risk management as
impacting on an organisation’s financial performance. It may also open up the area to scholars and academicians
for further research.
1. Objectives of the Study
The general aim of this study is to determine the effects of credit risk management as a branch of financial
risk management on the financial performance of Kenya Power.
2. Research Hypotheses
H01: Kenya Power revenue collection is not affected by credit risk management policies.
H11: Kenya Power revenue collection is affected by credit risk management policies.
2. Literature Review
2.1 Financial Performance of Kenya Power
Kenya Power is an organisation in the service industry in Kenya, undertaking the core business of
transmission, distribution and retail of electricity purchased in bulk from KENGEN, IPP’s, UETCL and
TANESCO. At the centre of its operations, it aims to adequately supply reliable electricity to its customers,
improve on customer service, accelerate electricity access to the public, and create value for its shareholders
(Kenya Power Annual Report and Financial Statements 2012). The organisation is guided by eight key strategic
pillars as per its annual report and Financial Statements (2012). Electricity infrastructure, adequate and secure
sources of power, provision of efficient customer service and strategic marketing, development and maximisation
of human capital, financial sustainability, innovation, diversification and business sustainability and corporate
governance.
In the year 2012 Kenya Power connected a record 307 000 new customers to grow its customer base to 2
million. This was characterised by an increase in Revenue to Kshs. 45 008 million in 2012 compared to Kshs. 42
485 in 2011 and Kshs. 39 107 in 2010. It’s power purchase costs increased to Kshs. 21 080 million in 2012
compared to Kshs. 20 214 in year 2011 and Kshs. 20 516 in 2010. Owing to the expansion of the electricity
network, increased demand and efforts to improve on quality, transmission and distribution costs for KP in the
year 2012 grew to Kshs. 19 680 million compared to Kshs. 17 695 in year 2011 and Kshs. 14 911 in 2010. The
company was therefore able to post a net profit after tax of Kshs. 4 617 million (dividend Kshs. 0.50 per share)
in the year 2012, compared to Kshs. 4 219 (dividend Kshs. 0.45 per share) in 2011 and Kshs. 3 716 (dividend
Kshs. 0.36 per share) in 2010. Indeed, intensive investment to meet customer growth over the years for the
organization has grown the asset base from Kshs. 21 088 million in the year 2005 to the current Kshs. 105 973
million in year 2012. Other interesting features of Kenya Power’s financial performance include the decline of
cash at hand and in bank from Kshs. 8.2 billion in the year 2011 to Kshs. 294 million in the year 2012 with an
overdraft moving from Kshs. 0 to Kshs. 1.7 billion over the same period. The cash flow statement over the same
period also highlights the decline of cash and cash equivalents from a positive of Kshs. 7 billion to a negative of
Kshs. 8.9 billion.
Whether an organisation is operating successfully or otherwise can be considered or gauged based on
predetermined performance indicators, which vary from industry to industry / organisation to organisation
(Fitz-Gibbon 1990). Choosing a good and representative indicator is reliant upon having a good understanding of
what is important to the organization and depends to a large extent on the department measuring the performance
so that indicators chosen by a finance officer will greatly differ from indicators chosen by say a marketing officer
or an IT&T officer. The minimum financial information for any business should be periodic financial statements
339


consisting of at least a balance sheet and profit and loss statement. Dunn (2004) distinguishes financial indicators
under various user groups that apply a series of accounting ratios to interpret and appraise organisational
financial performance. These ratios cover a number of concepts and can be grouped as: Profitability, Liquidity,
Utilisation, Financial structure, Investment – shareholder ratios. For this study, we limited our organizational
financial performance indicators to the first two, Profitability and Liquidity.
2.2 Profitability and Liquidity
Profitability and liquidity are the most prominent measures of organizational financial performance. Their
importance is derived from the fact that liquidity and profitability goals are contradictory to each other (at
extreme ends of a continuum) in most decisions which the finance manager takes and are thus good
representatives of the wide range of organizational performance indicators. For example, the firm by following a
lenient credit policy may be in a position to increase its sales and profitability, but its liquidity will tend to
worsen. According to Smith (1980) profitability and liquidity are the salient goals of working capital
management. The ultimate goal of any firm is to maximize profitability. It’s worth noting however, that too much
attention on profitability may lead the firm into a pitfall by diluting the liquidity position of the organization
(Smith 1980).
Liquidity is of major importance to analysts of organizational performance because of its inherent
relationship with the day to day operations of a business (Bhunia 2010). Liquidity ratios measure a business'
ability to meet the payment obligations by comparing the cash and near-cash with the payment obligations. If the
coverage of the latter by the former is insufficient, it indicates that the business might face difficulties in meeting
its immediate financial obligations. This can in turn, affect the company's business operations and profitability. A
weak liquidity position poses a threat to the solvency as well as profitability of a firm and makes its performance
to be uncertain. Potential investors on the other hand are interested in dividends and appreciation in market price
of stock, so they pay more attention on the profitability ratios as an indicator of organisational performance.
Therefore, firms should always strive to maintain a balance between the conflicting objectives of liquidity and
profitability. According to Eljelly (2004), efficient liquidity management involves planning and controlling
current assets and current liabilities in an efficient manner, so as to eliminate the risk of non-payment of dues for
short term requirements while also avoiding excessive investment in these assets.
Firms with fewer current assets have problems in continuing their operations, while those with excessive
current assets have a return on investment that is not in perfect condition. Economics and Finance literature
analyse four possible reasons for firms to hold liquid assets; the transaction motive (Miller & Orr 1966), the
precautionary motive (Opler, Pinkowitz, Stulz, & Williamson 1999), the tax motive (Foley, Hartzell, Titman, &
Twite 2007) and finally the agency motive (Jensen 1986). To make judgements about a firm, analysts use
liquidity ratios such as; Current Ratio = current assets/ current liabilities, Acid test ratio or Quick ratio = current
assets-inventories/ current liabilities, Liquid ratio = cash+ investments/ current liabilities. A dilemma in liquidity
management is to achieve desired trade-off between liquidity and profitability (Raheman et al., 2007). Referring
to theory of risk and return, investment with more risk will result to more return. Thus, firms with high liquidity
of working capital may have low risk and thus low profitability. Conversely, a firm that has low liquidity of
working capital faces high risks resulting in high profitability.
2.3 Credit Risk and its Management
Kenya Power monitors and manages its credit risks by grouping its customers according to their
characteristics e.g. Industrial, Government Ministries, Local Authorities, Parastatals, Commercial and Domestic
Consumers. Electricity supply agreements are then entered into with all customers, where they pay a deposit two
times their monthly consumption as cash security or bank guarantee for industrial and commercial customers, to
340


cushion against default. The alternative is to disconnect supply where bills remain unpaid beyond 21 days after
billing. A majority of organisations incur huge losses due to the inability of customers to meet their obligations
related to lending, trading, settlement and other financial transactions. Otherwise referred to as default risk, it is
associated with a borrower going into default by not making payments as agreed or promised, leading to
organisational losses. Credit risk also comes in the context of economic exposure, through opportunity costs,
transaction costs and expenses associated with non-performing assets. Swarens (1990) suggested that the most
pervasive area of risk is an overly aggressive credit practice, where credit is extended beyond the useful life of
corresponding collateral. Giving out credit to borrowers who are already overloaded with debt or have a poor
credit rating is a sure way of facing default and thus credit risk.
Sanford (1985) recommends diversification as a sure way of reducing credit risks, while Bloomquist (1984)
reckons that a credit portfolio risk can be reduced by an effective credit review of the applicant and selective
asset backing. Where creditors have extensive rights to repossess collateral assets, credit risks will be minimised
since borrowers will be willing to pay up in order to secure their assets. Wesley (1993) describes the important
elements of managing credit risks as a credit culture, a credit criteria, diversification, proper training of personnel,
tracking results, setting standards and rewarding compliance. Credit risk management enables an organization to
mop up all its dues in a good and timely manner thereby assuring it of continued profitability and liquidity.
2.4 Research Gaps
From the literature reviewed above, it is clear that a gap exists in how the independent variables affect the
dependent variable. Whereas research has been conducted into the different types of risk management including
credit risk management, little has been done in attempting to determine their effect on an organisation’s financial
performance, which this study set out to achieve.
3. Research Methodology
3.1 Research Design
This case study applied a descriptive and inferential research approaches in describing and analysing the
elements of the different variables being explored. This helped in determining the effects of financial risk
management on an organisation’s financial performance by attempting to relate both the dependent and
independent variables. Data was collected by use of an online survey questionnaire, to capture the depth of risk
management practice within the organisation. The study combined the use of primary data through the survey
questionnaires, and secondary data obtained from Kenya Power’s annual audited financial reports, and periodic
organisational publications. The survey questionnaires had four parts, with Part I touching on general bio data,
Part II, touching on current status of financial risk management, Part III touching on effects of financial risk
management on Kenya Power’s financial performance and Part IV touching on challenges and strategies of
enhancing financial risk management. A 5 point likert scale where 1 represents the least important response and 5
represents the most important response were employed, to help minimise on errors, delays and bias, with a few
open ended questions allowing respondents personal opinion. Online survey questionnaires were preferred
because of the wide geographical distribution of finance staff at Kenya Power, and also since the study delved
into the perception and opinion of employees on the depth of effects of financial risk management practice on the
financial performance of Kenya Power.
3.2 Response Rate
The study distributed 108 online survey questionnaires to the five regions of Kenya Power out of which 87
were successfully filled and returned, giving a response rate of 80.6%. Response rate per region is shown on
Table 6.1 below.

341


4. Research Findings and Discussions
4.1 Financial Performance of Kenya Power for the Past 5 Years
The company’s performance over the past 5 years was measured by rating opinions’ on the profits, operating
expenses, revenues, cash availability and ease of capital expenditure as presented in table 7.1 below. These
were measured on a five point scale as 1 – Declining growth, 2 – Zero growth, 3 – Moderate growth, 4 – High
growth, 5 – Very high growth. Adequacy of cash to meet office and payment of supplier requirements was ranked
as the highest parameter with a mean of 3.63, followed by regional operating expenses at 3.42, regional revenues
at 3.39, regional profits before tax at 3.29 and ease of capital expenditure at 3.00 respectively. Further, an
analysis of variance was carried out as captured in table 7.2 below to compare variation in performance within
the regions and the findings were as explained therein.
4.2 Credit Risk Management Practices
Findings on the credit risk management practices adopted by Kenya Power are shown on Table 7.3. Level of
application of these strategies was measured on the scale 5- 1 where 5 was most applied while 1 was least
applied. Ranking in order of intensity in which these strategies are applied, prompt disconnection for delayed
payment of electricity bill was the most applied strategy rated at a mean of 3.941, followed by the prompt
dispatch, accuracy and consistency of billings at a mean of 3.465, ensuring adequate electricity deposit in case of
customer default was third at a mean of 3.086, and putting adequate deterrent measures on theft of electricity was
the least applied strategy at a mean of 2.965. Further, a spearman’s correlation test was conducted on the
variables under credit risk management and the financial performance of Kenya Power with results as indicated
therein.
4.3 Hypotheses Testing
This study sought for an answer to the hypotheses: Kenya Power Revenue collection is not affected by
credit risk management policies. This was tested by finding the relationship between the credit risk management
practices in place and the rating on revenue collection within 21 days after billing to customers. The resultant
tabulation indicated that the credit risk management practices in place at Kenya Power affected revenue
collection where, as credit risk reduced, revenue collection improved. Hence the null hypothesis H01 was rejected
and alternative hypothesis H11adopted.
5. Summary
Kenya Power adopted various strategies in managing credit related risks which when ranked in order of
intensity of application revealed the following: Prompt disconnection for delayed payment of electricity bill was
the most applied strategy rated at a mean of 3.942, the second most applied strategy was dispatch, accuracy
and consistency of billings rated at a mean of 3.136, the third was ensuring adequate electricity deposit in case of
customer default at a mean of 3.356, while putting adequate deterrent measures on theft of electricity was the
least applied strategy. As a result of the above strategies, there was a significant correlation between prompt
dispatch, accuracy and consistence of billings and regional operating expenses rs = - 0.241, p < 0.05, and branch
liquidity rs = 0.309, p < 0.05. There was also a significant relationship between prompt disconnection for delayed
payment of electricity bill and branch liquidity rs = 0.289, p < 0.05. However, there was no significant
relationship observed between adequate deterrent measures on theft of electricity performance. A significant
relationship was also observed between increased electricity deposit in case of customer default and regional
revenues rs = 0.228 p < 0.05, and liquidity rs = 0.218 p < 0.05. Overall, the results indicated that there was a
significant relationship between credit risk management practices and revenue collection.
6. Research Limitations
The researcher encountered various limitations that may have contributed to the conclusions arrived at in
342


the study. The main limitation was the limited time period available for the study. A comparative analysis on
performance of different utility organizations may have provided a better pointer as to the financial performance
of Kenya Power. The other limitation encountered was in deciding which financial indicators to use in gauging
the financial performance of Kenya Power. Whereas the decision to use Liquidity and Profitability was informed
by the fact that the two lie in the extreme ends of a continuum of financial indicators, their use may have missed
some critical indicators in between, particularly those that touch on the financial performance of a heavily geared
company like the Kenya Power. Lack of adequate prior research was also noted to have been a limitation in that
not much literature review was available on the given topic thus making it difficult to lay a foundation for a clear
understanding of the research problem under investigation.
7. Conclusions
The study sought an answer to the following hypothesis: Kenya Power Revenue collection is not affected
by credit risk management policies. Based on the findings, the study concludes that the credit risk management
practices in place at Kenya Power were effective and contributed a lot in ensuring effective revenue collections.
This was mainly achieved through: prompt electricity disconnection for delayed payment, prompt dispatch,
accuracy and consistency in the billing systems and raising electricity deposit to clients who default in paying
bills.
References
Benson, G., Bromwich, M., Ritan, R. E., & Wagenhofer, A. (2003). Following the money: The Enron Failure and
the State of Corporate Disclosure. AEI-Brookings joint centre for regulatory studies.
Bhunia, A. (2010). A Trend Analysis of Liquid Management Efficiency in Selected Private Sectors in Indian
Steel Industry. International Journal of Research in Commerce and Management. Vol. 1, Issue 5, pp. 9 – 21.
Bloomquist, R. (1984). Managing Loan Portfolio Risk. The Journal of Commercial Bank. A Preliminary Study
on Credit Risk Management Studies, pp. 63 – 64.
D’Arcy, S. P. (2001). Enterprise Risk Management. Journal of Risk Management of Korea, 12 (1), 207 – 228.
Dunn, W. (2004). Public Policy Analysis. 3rd Ed. Englewood Cliffs, NJ: Prentice Hall.
Fitz-Gibbon, C. T. (1990). Performance Indicators. Bera Dialogues.
Foley, C., Hartzell, J., Titman, S. & Twite, G. (2007). Why do firms hold so much cash? A tax based explanation.
Journal of Financial Economics. 86, 579 -607.
Guzman, O. (2012). Differences between Business Risk and Financial Risk. The Houston Chronicles. Retrieved
from http://smallbusiness.chron.com/ difference-between-business-risk-financial-risk.
IFRS (2006). International Financial Reporting Standards.
Jensen, M. (1986). Agency costs of free cash flow, corporate finance, and takeovers. American Economic Review.
76, 323 – 329.
Kenya Engineer (2007). Canadian Management team for KPLC. Journal of the institute of Engineers of Kenya.
Kenya Power (2012). Annual Financial Reports.
Miller, M. H. & Orr, D. (1966). A model of the demand for money by firms. Quarterly Journal of Economics. 80,
413 – 435.
Opler, T., Pinkowitz, L., Stulz, R. and Williamson R. (1999). The determinants and implications of corporate
cash holdings. Journal of Financial Economics. 52: 3 – 46.
Raheman A. and Nasir M. (2007). “Working Capital Management and Profitability: Case of Pakistan Firms”,
International Journal of Business Research Papers, Vol. 3, No. 1, pp. 279-300.
Sanford, C.(1985). Regulation and Risk: The Hidden Costs of Limiting Competition. The Journal of Commercial
343


Bank Lending. 67 (5): pp. 8 – 18.
Skipper, H. D. & Kwon, W. (2007). Risk Management and Insurance: Perspective in a Global Economy.
Blackwell Publishing.
Smith, K. (1980). Profitability versus Liquidity Trade-offs in Working Capital Management. St. Paul, West
Publishing Company, USA.
Swarens, R. (1990). Managing Risk in Consumer Loan Portfolio. The Journal of Commercial Bank Lending. 72
(4): pp. 4 – 8.
Wesley, D. H., (1993). Credit Risk Management: Lessons for Success. Journal of commercial Lending, 75, pp.
32-38.

Table 6.17: Response Rate per Region
Region

Frequency

Percent

Coast

15

17.2

Nairobi

6

6.9

West

24

27.6

Head office

30

34.5

Mount Kenya

12

13.8

Total

87

100.0

Head office had the highest response rate at 34.5% feedback.
Table 7. 1: Kenya Power Financial Performance for the Past 5 Years
Performance Indicators per Region

5

4

3

2

1

Mean

Regional profits before tax

3.4%

20.7%

67.8%

2.3%

5.7%

3.29

Regional operating expenses

12.6%

37.9%

39.1%

6.9%

3.4%

3.42

Regional revenues

8.1%

20.9%

62.8%

7.0%

1.2%

3.39

Adequacy of cash to meet office and
payment of supplier requirements

11.5%

32.2%

40.2%

12.6%

3.4%

3.63

Ease of capital expenditure

3.5%

18.8%

60.0%

12.9%

4.7%

3.00

Regional profits before tax was rated moderate by majority of 67.8% of the respondents, while 20.7% rated it
high. Regional operating expenses were rated high by 37.9% and moderate by 39.1%. Regional revenues were
moderate according to majority 62.8%, while 20.9% rated them high. Adequacy of cash to meet office expenses,
40.2% rated it moderate while 32.2% rated it high. Majority 60.0% identified that they had ease in finances for
capital expenditure.
Table 7.2: Performance Measures Across Regions - ANOVA
ANOVA
Sum of
Squares
344

df

Mean
Square

F

Sig.


a) Regional profits before tax Between Groups

4

0.763

Within Groups

47.292

82

0.577

Total

50.345

86

2.397

4

0.599

Within Groups

71.350

82

0.870

Total

73.747

86

.507

4

0.127

Within Groups

48.795

81

0.602

Total

49.302

85

7.429

4

1.857

72.525

82

0.884

79.954

86

2.038

4

0.509

Within Groups

52.856

80

0.661

Total

b)
Regional
expenses

3.053

54.894

84

operating Between Groups

c) Regional revenues

Between Groups

d) Adequacy of cash at bank Between Groups
for pay office requirements Within Groups
and payment of suppliers
Total
e)
Ease
expenditure

of

capital Between Groups

1.323

0.268

0.689

0.602

0.211

0.932

2.100

0.088

0.771

0.547

ANOVA test for variance in performance between branches revealed that there was no significant variation
performance across regions in all performance measurements applied in the study, implying that the management
standards were applied uniformly in all regions and the performance trends were similar.
Table 7.3: Credit Risk Management Strategies
Credit Risk Management

1

2

3

4

5

Mean

Prompt dispatch, accuracy and
consistency of billings

3.5%

17.4%

34.9%

17.4%

26.7%

3.465

Prompt disconnection for delayed
payment of electricity bill

3.5%

20.0%

31.8%

27.1%

17.7%

3.941

Adequate deterrent measures on
theft of electricity

11.8%

20.0%

35.3%

25.9%

7.1%

2.965

Adequate electricity deposit in
case of customer default

12.3%

19.8%

27.2%

28.4%

12.3%

3.086

The findings on Table 7.3 above indicates that, 26.7% rated prompt dispatch, accuracy and consistency of
billings as most applied, while 17.4% rated it at moderately more applied 34.9% at averagely applied. Prompt
disconnection for delayed payment of electricity bill was rated at averagely applied by majority of 31.8% while
27.1% rated it at moderately more applied in application at Kenya Power. The use of deterrent measures on theft
of electricity was also applied, 35.3% rated it at averagely applied while 25.9% rated it at moderately more
applied. Ensuring adequate electricity deposit in case of customer default was rated at moderately more applied
by 28.4% and averagely applied by 27.2% of the finance staff as a measure used to manage credit risks.
345


Table 7.4: Spearman’s Correlation on Credit Risk Management and Financial Performance of Kenya Power

Regional

Region

Ease

of

profits Regional al

capital

before operating revenu

expenditur

tax
a)Prompt dispatch, accuracy Correlation
and consistency of billings

expenses es

Liquidity e

.095

-.241*

.120

.309**

.157

.382

.025

.274

.004

.154

86

86

85

86

84

.162

.172

.046

.289**

.141

.139

.116

.681

.007

.202

85

85

84

85

84

.161

.157

.207

.179

.025

.140

.151

.059

.101

.822

85

85

84

85

83

.167

.206

.228*

.218*

.105

.136

.065

.042

.051

.356

81

81

80

81

79

Coefficient
Sig. (2-tailed)
N

b) Prompt disconnection for Correlation
delayed payment of electricity Coefficient
bill

Sig. (2-tailed)
N

c)

Adequate

measures

on

deterrent Correlation
theft

electricity

of Coefficient
Sig. (2-tailed)
N

d) Adequate electricity deposit Correlation
in case of customer default

Coefficient
Sig. (2-tailed)
N

The test results indicated that there was a significant correlation between prompt dispatch, accuracy and
consistence of billings and regional operating expenses with rs = - 0.241, p < 0.05, and branch liquidity having rs
= 0.309, p < 0.05. However, there was no relationship between prompt dispatch, accuracy and consistency of
billings and profits before tax, regional revenues, and ease of capital expenditure. This means that prompt
dispatch, accuracy and consistency of billings reduce the level of regional operating expenses and also leads to
an increase in the liquidity levels in the organization.
There was also a significant relationship observed between prompt disconnection for delayed payment of
electricity bill and branch liquidity rs = 0.289, p < 0.05. However, this had no significant relationship with
regional profits before tax, regional operating expenses, regional revenues, ease of capital expenditure. This
means that prompt disconnection for delayed payment of electricity bills enhances liquidity by making customers
pay their bills on time. There was no significant relationship observed between adequate deterrent measures on
theft of electricity and all performance measures. A significance relationship was also observed between
increased electricity deposit in case of customer default and regional revenues rs = 0.228 p < 0.05, and liquidity rs
= 0.218 p < 0.05. However, this relationship did not exist with Regional profits before tax, regional operating
expenses, ease of capital expenditure.
Table 7.5: Credit Risk Management Practice and the Rating on Revenue Collection
346


Revenue collection 21 days after
billing electricity customers
Spearman's
rho

Credit risk
management

Correlation
Coefficient

0.550*

Sig. (2-tailed)

0.037

N

83

The results indicated that there was a significant relationship between these two variables.

347

Effects of financial risk management...

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Effects of financial risk management...

Similar to Effects of financial risk management... (20)

More from World-Academic Journal

More from World-Academic Journal (20)

Recently uploaded

Recently uploaded (20)

Effects of financial risk management...