BBSA Research Projects (2021)

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http://hdl.handle.net/11071/12522

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An analysis on the adoption of IFRS 17 and the transparency of financial reporting in insurance companies in Kenya
(Strathmore University, 2021) Ndeda, Marie Anyango
This study was carried out to analyse the effect that the adoption of !FRS 1 7 by insurance companies in Kenya would have on financial reporting transparency. Insurers across the world and various scholars had raised concerns on the limitations of the current standard being used (!FRS 4) in insurance accounting. The data used in the analysis was obtained from the financial statements of 18 insurance companies in Kenya from 2010 to 2019. The dependent variable in the analysis was a transparency measure represented by R2 obtained from a regression involving eamings from the current and previous years. The independent variables were the Contractual Service Margin (CSM), Profit before tax (PBT) and the disclosure intensity measure. The Ordinary Least Squares (OLS) estimator was used in the analysis. Results from the analysis showed that CSM unlocked at varying rates and the disclosure intensity measure under !FRS 17 were statistically significant. All variables had positive coefficients apart from the disclosure intensity under !FRS 4. The conclusion therefore was, the adoption of !FRS 17 would enhance fmancial reporting transparency if, CSM was unlocked using varying interest rates, the building block approach was applied and if the disclosure requirements provided by !FRS 17 were followed
A comparative study of football prediction models
(Strathmore University, 2021) Rapando, Reginald Tabuche
This study investigates the effect of tiers on football prediction models. The tiers in this study are grouped according to the value of the teams. Many football prediction models do not take tiers as a factor when making predictions. The study used a Poisson Regression Model which assumes that the number of goals scored by a team follow a Poisson distribution. It also employed a Bayesian approach . The parameters used in the Poisson Regression Model are strength of attack, defensive strength, home advantage and club value (the tiers). From the study it was found that teams in a higher tier were given a higher probability of scoring more goals and winning games as compared to teams in a lower tier. This shows.that the value of a team has a significant effect on the predicted outcome in a football prediction model. From this, it was concluded that the value of a team is an important aspect that needs to be considered in football prediction models since it has a significant effect on the outcome of prediction.
Credit risk modelling in peer-to-peer lending: a comparative analysis of neural networks and XQboost
(Strathmore University, 2021) Wachira, Njomo
Consumer credit risk modelling involves coming up with the probability that a borrower default thus classifying borrowers as either defaulters or non-defaulters. This is important for lending firms because they are then able to lend out cash to borrowers who are most likely to repay on time. Tl1is protects their profits. This study aims to use machine learning techniques I in consumer credit risk modelling in a bid to find out which technique is more effective. In addition, the study aims at investigating the effect of new credit customers on default expenence.
The extent to which pension funds can be used to address the affordable housing gap in Kenya
(Strathmore University, 2021) Oluoch, Lucille Mujaw
The government of Kenya developed the Big Four Agenda in 2017, which is inclusive of affordable housing provision among the other three agendas. However, challenges with housing provision have led to an estimated 2 million-unit deficit. This study investigates how pension funds can address Kenya's affordable housing gap through constructing optimal hypothetical portfolios and evaluating the effectiveness of investments in private equity and real estate. The Shapiro-Wilk normality test was used to determine if asset class data follows a normal distribution to justify Mean-CVaR method optimisation in place of MVO. The asset classes were optimised and subsequently portfolios inclusive and exclusive of private equity and real estate asset classes were optimised, with performance compared. The returns of the optimal portfolio were used in a model to estimate the number of housing units the pension fund could purchase. The analysis showed that equity data alone follows a normal distribution hence justifying the use of Mean-CVaR optimisation for the multi-asset portfolio and that the traditional asset portfolio is the most profitable, rendering private equity and housing as ineffective investments. Further research is required on expanding pension portfolio asset class range and identification of better proxies for private equity and real estate data .
Forecasting exotic vegetable wholesale prices using time series analysis methods
(Strathmore University, 2021) Kate, Njoki Mbugua
Vegetables are known to be highly perishable and seasonal in nature. Forecasting prices of vegetables is important to the Government of Kenya, the buyers and particularly to farmers as they can use this information to help them maximise their profits and minimise their losses. T11erefore, accurate forecasting of their prices requires the use of models that take the seasonal nature of vegetables into account. In this research paper, the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Holt-Winter's Exponential Smoothing (HWES) models were used to forecast the wholesale prices of kales and cabbages in Nairobi, Kenya using monthly price data from January 2012 to December 2019. T11e Augmented Dickey Fuller (ADF) test showed that both the kales and cabbages price data were stationary hence no need for differencing. SARIMA(1,0,0)(1,1,1)12model was the best forecasting model for cabbages. This model was selected amongst other SARIMA models as it had the least Akaike Information Criterion (AIC) value. T11e Holt-Winter's Exponential Smoothing method was the best for kales. Mean Absolute Error (MAE), Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) were the forecast performance measures used to select the best forecasting model for kales and cabbages.
Funding opportunities for affordable housing programme
(Strathmore University, 2021) Maina, Peter Wanyoike
The purpose of this research paper is to examine the funding opportunities available for the affordable housing program. The study looks at the current channels of funding, the challenges facing affordable housing, the role of the private and goverm11ent sector. Primary data used was collected through presenting questionnaires to respondents in different financial sectors and there was a 64% response rate. The basis used for data collection were looking for the current funding opportunities, the difference between the funding opportunities in affordable housing than in other housing development, the drawbacks in funding and how can the funding opportunities be optimized. The data collected was input into Ms Excel and expressed as pie chart to make more meaning. The results show that there is need for encouragement of saving and contribution towards home ownership by the general public as this will be a catalyst in achievement of affordable housing. We find that state contribution is the best funding source for the affordable housing program and that government funding will still go back to the individual tenants and private entities through the housing tax levy
A health economic model: Prediction of the prevention of mother-to-child transmission intervention cost in Central Kenya.
(Strathmore University, 2021) Natacia, Rutendo Magombo
The PMTCT intervention is the most successful HIV prevention measure (Plessis et al., 2014). The program is heavily funded in Kenya by donors such as PEPF AR and the Global fund, leaving the patients with only the direct non-medical costs to bear. The ongoing progressive fund cuts have left questions on sustainability of the intervention and cost shtdies can help the government make crucial financial decisions (Creese et al,.l994). A provider's perspective has been given in the government reports, what is missing is a cost analysis taking on a patient cost perspective.
The impact of accessibility of mobile loan applications on the level of savings among Strathmore university students.
(Strathmore University, 2021) Kimaku, Martha Wanjiru
This study looks into the impact of accessibility of mobile loan applications on the level of savings among Strathmore University students. The continuous borrowing culture introduced by mobile loan applications is discussed as being a key factor that inhibits saving efforts ofthe youth. The life cyc le hypothesis model coupled with the technology adoption model wilt give this study an insight into the saving and borrowing culture of the youth. How then does endless borrowing prevent the youth fi·om creating good saving habits? With regards to borrowing and saving amongst individuals differ as a result of behavior, knowledge and mindset. The study therefore intends to investigate how number of mobile loan apps on each Strathmore University student's phone influences the level or savings, how the existence of knowledge about the mobile loan applications influences the level or savings among Stratlunore University student and how the level of usage of mobile loan applications impacts the level of savings among Strathmore University students. A descriptive study design was used whereas the estimated sample size was 384 students but only 100 respondents took part in the survey. The study employed a voluntary sampling method by use of online survey which was clone by the Strathmore University students order to investigate the factors that correlate students' saving and borrowing patterns using mobile applications. A multiple linear regression model was applied using the STAT A software to execute the analysis. Results revealed that there was a very weak correlation between quantity, knowledge and fi-equency of access fi·om mobile loan applications and the level of savings among Stratlunore University students. In addition, the more a student wns equipped with the knowledge of loan apps decreased a chance for them to save.
Impact of longevity risk on pension systems
(Strathmore University, 2021) Nyambura, Malvin Gitau
According to the "2019 Revision of World Population Prospects" prepared by the Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, life expectancy has risen from 60.26 in 201 0 to 66.70 in 2019. This increase in life expectancy is attributed to improved healthcare facilities, proper education, diversification in agricultural production and an increase in living standards. The improvement in life expectancy is positive news but it results in increased longevity risk. Longevity risk is the risk that individuals will have longer lifetimes than expected. In pensions, this is the risk attached to the increasing life expectancy of pensioners and policyholders, which will result in higher pay-out ratios than expected for many pension funds. If gains in life expectancy could be forecasted and factored in retirement planning, then the effect of longevity risk could be minimal and thus negligible but improvement in life expectancy and mortality are uncertain. Thus, longevity risk is related to the uncertainty surrounding future mortality and life expectancy.
Impact of mobile loan credit during the covid-19 pandemic in Kenya
(Strathmore University, 2021) Oduor, Sandra Odera
This study sought to investigate the impact of mobile loan credit during the Covid-19 Pandemic in Kenya. The specific objectives included investigating factors fuelling mobile loan uptake during the pandemic and investigating the effects of the pandemic on loan repayment. A total of 352 participants from Buruburu were randomly selected to form the sample of the study. The response rate was 100% with majority of respondents falling in the age groups of 30 and below (53.41 %). A descriptive cross-sectional research design was adopted. The data was collected by using pretested, structured interview based questionnaires and analysed using SPSS version 20. The study established that employment amongst the youths is still a problem as the youths were the most borrowers with a percentage of more than 53.41%. The COVID 19 pandemic has made more Kenyans to borrow mobile loans as 42.90% of the respondents had never borrowed before the pandemic. This study recommends that the government should create more employment opportunities for the youths by investing in and promoting Jua Kali sector. This will reduce the dependence rate on mobile loans amongst the youths and negative CRB listing.
Insurance policies for fertility treatments
(Strathmore University, 2021) Kipkorir, Ivy Chebet
In Kenya there are over 3 million people who suffer from infertility. According to the Nairobi IVF fertility center, fertility treatments can range anywhere from Ksh 10,000 to Ksh 480,000 per cycle. This is expensive for the average Kenyan and as a result it denies deserving couples the opportunity to bear a child. Various studies have also shown that infertility also affects the mental health of many couples with one study even claiming that infertility has the same psychological effects with cancer patients. Insurance companies however have the ability to assist these couples in offsetting some of the costs of seeking treatments for infertility treatments. This study therefore focuses on pricing an insurance policy for fertility treatments. When pricing the policy, the method used involved calculating the standard risk premium followed by getting the office premium. This study goes on to find the premium based on various demographic factors that may affect infertility such as age, education, occupation and marital status
Insurance pricing using geographical ratings
(Strathmore University, 2021) Ivy, Eva Wambui Kinyua
With time, insurance industries are expected to improve their pricing models, enabling them to respond to changes and become more efficient. Like any other industry experiencing losses, the Kenyan insurance industry has been on a journey to find solutions to reduce the losses they incur. This research tries to help the Kenyan insurance industry by suggesting the use of geographical ratings as a risk factor in the calculation of premiums.
Kenya insurance companies' financial performance determinants
(Strathmore University, 2021) Wanjohi, Laura Muthoni
The insurance firm is an integral aspect of Kenya's financial system, which is vital to the economy. With the growing need to be insured against various risks and the Emergence of different technological products, the insurance companies still have a low contribution to the GDP. For this study, we are establishing the factors that determine the financial performance of insurance companies across the general line,the life and combined line of business. The internal factors such as leverage, liquidity, loss ratio, underwriting risk, retention ratio and size of the firm were regressed against Return on Assets. The study shows that the loss ratio and leverage are important factors in the financial performance of general insurance firms, and they should improve on the leverage and reduce the loss ratio. The retention ratio,underwriting risk and firm size all have a role in life insurance bv.sinesses' financial performance which should be enhanced, and loss ratio decreased. The liquidity and loss ratio have a substantial impact on the profitability of insurance companies with both lines of business. In companies that have both lines of business, they should reduce the loss ratio and increase the liquidity.
Loss distributions for motor insurance claim severity in Kenya
(Strathmore University, 2021) Nyairo -, Frankline Okindo
The insurance industry is one of the oldest industries. Insurance companies exist to provide indemnity and make profits since insurance is a business like any other. The advancement of the insurance market is compelled by the prevailing interest of the public for cover against different forms of risks of tmacceptable arbitrary incidents with a considerable financial effect (Omari et al., 2018). A policyholder is supposed to pay a premium and make a claim when a certain event occurs witllin a given period as per the policy. The insurer is tl1en obliged to settle the claim, and this is referred to as loss. Insurers are keen with the results oftl1e random outcome of claims instead of the existence of the claims. They are concerned with the loss rather than the circumstances that give rise to the loss (Achieng, 2010). The aggregate amount of claims in a given dmation is a measure that is vital to the operations of an insurance company.
Measuring the impact of universal health care on longevity risk
(Strathmore University, 2021) Mbau, Lorna
Longevity remains to be a complex risk that is ever evolving and requ1res great understanding. Improved healthcare through the roll out of Universal Health Care is also seen to enhance this risk through improved mortality rates. This leaves individuals, governments and benefit providers at risk because they can not appropriately make financial plans leading to major losses or inadequate funds and reserves. This study expounds on longevity risk and its impact on the interested pmties
Mobile money and macroeconomic outcomes in East Africa
(Strathmore University, 2021) Kimere, Christine Muthoni
This study examined the outcomes of mobile money use on money supply, inflation and national output. Data was taken from East African countries that have adopted mobile money services, namely Kenya, Tanzania, Uganda and Rwanda. A Panel Vector Autoregression was fitted to the data, and subsequently a Forecast Error Variance Decomposition and Orthogonalized Impulse Response Function were generated to examine the dynamics between the variables. The findings indicate that mobile money transactions have modest negative effects on inflation and money supply in the medium-term. Indicating that mobile money substitutes for the transactional function of money to some extent, and enhances output and efficiency of production.
Modelling of insurance penetration contribution to the economy.
(Strathmore University, 2021) Muriithi, Susan Waithera
The study was set to understand the relationship between the economy of the country and insurance penetration. The relationship between the two would be important to understand the contributions of insurance penetration to the economy as well as recognize what causes the low insurance penetration rate. The availability of already published information on these factors was reliable and due to this reason, the use of primary data was not obtained. The data was available from the Insurance Regulatory Authority as well as the Central Bureau of Statistics and sigma-explorer. The target population was the already registered number of insurance companies and a cover period of the past five years which was key since the penetration rate in the country has been dropping ever since 2013 when it was at its highest. The model used was a regression analysis which combined the major determinants of insurance penetration the variables to be used in the regression. This include assets, investments and investment income and the Gross Premium Income. Fromthe analysis the Gross Premium Income was seen to be the leading factor in the insurance industry to be contributing to the national economy. The insurance sector is the major contributor to insurance penetration by the decision they make in everything from the distribution channel, promotion methods, pricing, benefits provided, technology used, and everything in general and still maintaining a competitive advantage. Every decision they make is a contribution towards the economy. Due to their major role in all this the study examines what is done and how this affects the penetration rate and what can be done to change ad improve this.
Modelling risk adjustment under IFRS 17
(Strathmore University, 2021) Musyoka, Nisa Wairimu
The IFRS 17 accounting standard for measuring Insurance profits is effective for periods starting on or after 1 January 2022 and critical to its measurement is the Risk Adjustment factor. The Risk Adjustment measure is the compensation the entity requires for uncertainty about timing and amount of non-financial risks. The issue however is that there is no prescribed calculation to this measure hence entities must derive the calculation that best suits them if they adhere to the IFRS 17 requirements. This study aims to determine the best risk adjustment measure calculation given the Kenyan Insurance market. The study goes into rigorous detail as to the suggested approaches, mainly the discounted cash flow approach and the cost of capital approach and gives an analysis of how to develop the respective models and the outcome of which one worked best in the context of the Kenyan market. Data was obtained from the Insurance Regulatory Authority for the years 2015 - 2019 mainly focused on short term claim statistics. The study established that the Proportional Hazard Transform under the discounted approach would be best suited to the Kenyan market since it explains the significance of the effects of premium on risk. It also satisfies all conditions under the IFRS 17 requirements and is a coherent risk measure.
Modelling the effectiveness of Covid-19 intervention measures for different demographics
(Strathmore University, 2021) Annah Mwende Musomba
The study aims to discuss on how differences in timing and duration of implementation of an intervention measure would affect the results from intervention. It also seeks to find how effectiveness of an intervention would differ if put in different countries with different demographic characteristics. A Susceptible- Infected- Recovered (SIR) model is developed to provide a theoretical framework for the study. The model uses the SIR model but accounts for different demographics and how intervention (school closure) affects the rate at which individuals move form susceptible to infected. Using data of confirmed cases of different countries and the interventions put in place, the study deduces the importance of timing and duration in implementation of an intervention. The study deduces that for an intervention to be greatly effective considerations must be done on the timing and duration of the intervention. Demography of a region should be considered when picking out an intervention.
Pay-as-you-drive as a pricing alternative in motor insurance
(Strathmore University, 2021) Waithera, Jasmine
A Pay-As-You-Drive (PAYD) pricing method simulating the replacement of the fixed costs of vehicle ownership and operation, with variable costs. The objective was to estimate the pricin effect of each strategy and deduce 'Yhether P A YD pricing can be employed as an alternativepricing method. The pricing effect is the focus of this paper. Consumers should be able to choose among various pricing structures. With a per-unit-of-distance alternative pricing scheme, drivers would be able to save money on car insurance by driving less and might even decide that some of the extra kilometers driven are not worth the cost. The data incorporated in this study is mileage data from private passenger vehicle data in the Commonwealth of Massachusetts. The data analyses over one million data points. The results showed that the traditional Generalised Linear Model (GLM) method of pricing was still more efficient. Even so, for insurers with the largest portfolios in the market, that have considerable participation in relation to the total, the Pay-As- You-Drive pricing method can be a simple and effective alternative pricing technique. The decision as to which pricing technique to employ is thus best left to the strategy of each insurer and should be analyzed in relation to the cost of each and how much this will impact positively to the result of the portfolio.

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