effects of financial risk management

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

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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

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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,


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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


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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


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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.


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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


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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

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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 df

Mean Square F Sig.


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a) Regional profits before tax Between Groups 3.053 4 0.763 1.323 0.268

Within Groups 47.292 82 0.577

Total 50.345 86

b) Regional operating expenses

Between Groups 2.397 4 0.599 0.689 0.602


Total 73.747 86

c) Regional revenues Between Groups .507 4 0.127 0.211 0.932


Total 49.302 85

d) Adequacy of cash at bank for pay office requirements and payment of suppliers

Between Groups 7.429 4 1.857 2.100 0.088


Total 79.954 86

e) Ease of capital expenditure

Between Groups 2.038 4 0.509 0.771 0.547


Total 54.894 84

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.


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

Regional profits before

tax

Regional operating expenses

Regional revenues Liquidity

Ease of capital expenditure

a)Prompt dispatch, accuracy and consistency of billings

Correlation Coefficient

.095 -.241* .120 .309** .157

Sig. (2-tailed) .382 .025 .274 .004 .154

N 86 86 85 86 84

b) Prompt disconnection for delayed payment of electricity bill


.162 .172 .046 .289** .141

Sig. (2-tailed) .139 .116 .681 .007 .202

N 85 85 84 85 84

c) Adequate deterrent measures on theft of electricity


.161 .157 .207 .179 .025

Sig. (2-tailed) .140 .151 .059 .101 .822

N 85 85 84 85 83

d) Adequate electricity deposit in case of customer default


.167 .206 .228* .218* .105

Sig. (2-tailed) .136 .065 .042 .051 .356

N 81 81 80 81 79

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


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Revenue collection 21 days after billing electricity customers

Spearman's rho

Credit risk management


0.550*

Sig. (2-tailed) 0.037

N 83

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

effects of financial risk management

Economy & Finance