https://repository.maseno.ac.ke/handle/123456789/1937 Fri, 15 May 2026 15:55:20 GMT 2026-05-15T15:55:20Z https://repository.maseno.ac.ke/handle/123456789/5465 Application of Continous Time Model in Prediction of Loss Reserves in Credit Insurance for Asset-Based Lending Companies Etyang Isaac, Joshua Were Asset-based lending companies and other loan providers are exposed to risk of loan defaults by borrowers. To reduce this risk, these companies acquire credit insurance. Thus when the borrower defaults in payment, the insurance company covers a percentage of the outstanding balance which generates a way to lessen and spread credit risk that the lender incurs. Therefore there are a number of methods put in place such as frequency-severity and hazard rate models used to value credit insurance. Valuing of credit insurance for asset-based lending companies is a challenging task especially in Kenyan market, where in the case of a borrower’s default, the process for recovering of the collateral will last a longer period of more than a year and where data on the borrower’s behavior of payment is of poor quality or generally unavailable. The existing methods do not consider the time to repossession of the collateral in case of loan default. Our proposed model takes into account time to repossession of the collateral and can be used in emerging market economies where other available methods may be either unsuitable or are too complex to implement due to lack of enough data. Therefore, this paper incorporates a continuous time model to forecast loss reserves in credit insurance for asset-based lending companies. First, we establish a discrete-time model to describe delinquency of credits in loan insurance product. Martingale properties, Replicating of asset portfolio strategy and Itô’s calculus are used to obtain results on expected values of future losses of credit insurance products. Secondly, we used the Black-Scholes model to develop a continuous-time model to forecast future losses in credit insurances. This is constructed by linking the latter from the discrete-time (Binomial) model using the methods of stochastic calculus. We estimated the loss reserves by applying the Geometric Brownian Motion on data of outstanding balances of 30% of 100 loanees from car loan business with assets valued at between 1 million and 10 million, to predict the probability of default of the borrower. DOI: 10.4236/jmf.2022.123025 Sat, 01 Jan 2022 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/5465 2022-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/4976 Influence of Entrepreneur and Firm Characteristics in Accessing Bank finance Kili Muhindi Rop, Edgar Ouko Otumba,Peter Kibas and Bernard Kibeti Nassiuma SMEs are mostly guided by the owners’ characteristics which is an indicator of the level of decisions taken in the firm. Access to credit is a prerequisite for a high performance of an SME. The paper aimed at establishing the empirical link between entrepreneurs and firm characteristics and access to bank financing by SMEs in Eldoret town. Descriptive and explanatory research designs were employed in the study. A chi-square test of association was used to determine the relationship between study variables. The study findings indicated that gender and number of employees had a significant influence on access to bank financing. Male entrepreneurs are more likely to get bank financing compared to their female counterparts, while an increase in the number of employees increases the success rate of getting bank financing. However, age, education, business form, number of years of operation, stage of business and average turnover were found to be insignificant in obtaining funding. The study concluded that entrepreneur characteristics namely gender and relation to business and firm characteristics specifically structure of the business, economic sector and the average turnover determines the likelihood of banks financing SMEs. Entrepreneurial and firm characteristics were found to be important in access to bank financing. The study recommended that government and other service providers incorporate additional simplified components to their training packages to cover such areas as bookkeeping and development of business plans. Banks should develop lending policies which are friendly to Small and Medium Enterprise contexts. DOI: https://doi.org/10.53819/810181025027 Fri, 01 Jan 2021 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/4976 2021-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/4970 Modernizing pension fund contribution Calvine Odiwuor, Were Joshua The purpose of this research is to develop a pension model which uses mobile phone technology to facilitate contribution towards the user’s pension scheme. DOI: https://doi.org/10.47672/ajsas.844 Fri, 01 Jan 2021 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/4970 2021-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/4869 Approximations of Ruin Probabilities Under Financial Constraints C Odiwuor, F Onyango, R Simwa In this paper, we investigate the approximate ruin probabilities un der financial constraints (interest rate, inflation, and taxation). We formulate a risk process whose premium inflow is influenced by the economic effects of inflation and interest rate. Thereafter we invoke the Albrecher-Hipp loss-carried-forward tax scheme from which an ex act formula for the ruin probability for exponentially distributed claims is derived. Finally, an explicit asymptotic formula when the claims have sub-exponential distribution is also derived using the Pollaczek Khintchine formula. HIKARI Ltd, www.m-hikari.com https://doi.org/10.12988/ams.2020.914188 Fri, 01 Jan 2021 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/4869 2021-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/3471 Models for Variable Premiums Payable to Benevolent Funds Chora Damary Rehema, Fredrick Onyango, Joshua Were he application of multiple life actuarial calculations have been studied by many authours for instance Elizondo [5] studied the construction of multiple decrement models from associated single decrement experiences. He posits that it is convenient to use the survival functions for the projection of future obligations in cash flows. Bowers [2] studied the actuarial calculations which are common in estate and gift taxation. The actuarial calculation is also common in insurance where stipulated payment called the benefit, one party (the insurer) agrees to pay to the other (the policyholder or his designated beneficiary) a defined amount (the claim payment or benefit) upon the occurrence of a specific loss while the insured pays periodic payment called premium. SACCOs and institution provide benevolent in terms of insurance against some losses, especially death. Unfortunately such organizations determine their premiums arbitrarily, thus one cannot tell whether such products are degenerating or not, this is because in such bodies benevolent funds and the mainstream operation fund are usually confounded. In this paper we develop models for variable premiums for Saccos and Institutions providing benevolent funds, that is premiums is dependent on the number of beneficiaries. We will use models of joint life, last life and multiple decrements to develop this model. Wed, 01 Jan 2020 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/3471 2020-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/3003 OPEN EDUCATIONAL RESOURCES FOR STATISTICS TEACHING James Musyoka, Roger Stern, David Stern A series of papers at this conference have built on the African Data Initiative (ADI) which was started to improve statistical literacy and understanding. One immediate deliverables of this initiative has been new statistical software which is free, easy-to-use, open source and which encourages good statistical practice. Here we show how this software together with other open educational resources can be used to improve statistics teaching. This is demonstrated using an undergraduate course which was offered to about 300 students at Maseno University, Kenya. The resources include those from an e-learning course, called e-SMS (Statistics Made Simple) and an electronic statistics book called Computer Assisted Statistics Textbook (CAST). The course also made extensive use of Moodle to enable a “blended” approach to be undertaken. Sun, 01 Jan 2017 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/3003 2017-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/3001 Envisioning Change in the Statistics-Education Climate. David Stern, Roger Stern, Danny Parsons, James Musyoka, Francis Torgbor, Zach Mbasu The African Data Initiative started as a crowd-sourced campaign to improve the teaching of statistics in African universities. The analysis of climate data provides one suitable context to illustrate ideas that lead to a radical new form of teaching. The problem within the context comes first, the technicalities are largely reduced–mathematics is supported by meta knowledge and backed up by modelling; calculations are reduced by user-friendly software that is also used by experts. The problems are treated similarly to research questions and the results are often easier to interpret, making sense as potential answers in their context. The criteria of this approach are compared to the framework proposed by WG Cobb to reform statistics education in the light of the latest developments in statistics, driven by the huge increase of data. Implementation details are presented around three components: case studies, data, and the … Sat, 01 Feb 2020 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/3001 2020-02-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/3000 BUILDING STRENGTH FROM COMPROMISE; A CASE STUDY OF FIVE YEAR COLLABORATION BETWEEN THE STATISTICAL SERVICES CENTRE OF THE UNIVERSITY OF READING, UK AND MASENO UNIVERSITY, KENYA James Musyoka, David Stern, Roger Stern Statistics teaching and practice at Maseno University has benefited immensely from its collaboration with the Statistical Services Centre (SSC) at the University of Reading. The SSC, a self-sustaining entity providing statistical consultancy to a wide range of clients in Africa, has also found a trusted pair of hands to help with its work in the developing world. The success of this collaboration is due to the long-standing working relationship between staff at these two institutions which this paper describes from both points’ of view. This collaboration is not without challenges and this paper also discusses the compromises made by both parties to make this collaboration work. Wed, 01 Jan 2014 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/3000 2014-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/2998 Exploring the Role of Extra Curricula Maths Camps and Clubs in Kenya and Beyond Emily Fleming, Zachariah Mbasu, David Stern, Danny Parsons, Mildred Ayere, Franca Hoffmann, James Musyoka, Thomas Mawora, Chris Clarke, Santiago Borio, Michael Obiero For the last four years Maseno University, Kenya, has been running a maths camp bringing together both international and local, lecturers and teachers to engage secondary students in the subject through puzzles, games, technology and extra-curricula mathematics. This paper presents the core values that are behind the success of the camps as well as how the initiative has evolved to scale out to more students through school maths clubs. A case will be made that there are changes happening in Kenyan education which have created a window of opportunity for such initiatives to prosper, where traditional teacher training has not been a success. Finally it will be mentioned how the camps have already spread to Ethiopia, Ghana and the UK, illustrating the potential for innovation in such low resource environments to have global impact. Thu, 01 Jan 2015 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/2998 2015-01-01T00:00:00Z https://repository.maseno.ac.ke/handle/123456789/2997 Envisioning Change in the Statistics-Education Climate. David Stern, Roger Stern, Danny Parsons, James Musyoka, Francis Torgbor, Zach Mbasu The African Data Initiative started as a crowd-sourced campaign to improve the teaching of statistics in African universities. The analysis of climate data provides one suitable context to illustrate ideas that lead to a radical new form of teaching. The problem within the context comes first, the technicalities are largely reduced – mathematics is supported by meta knowledge and backed up by modelling; calculations are reduced by user-friendly software that is also used by experts. The problems are treated similarly to research questions and the results are often easier to interpret, making sense as potential answers in their context. The criteria of this approach are compared to the framework proposed by W. G. Cobb to reform statistics education in the light of the latest developments in statistics, driven by the huge increase of data. Implementation details are presented around three components: case studies, data, and the required skills. Together, these three components describe an alternative education pathway centred around statistical problem solving. The focus on interpretations of results within a real context enables software, mathematical thinking and modelling to play a supportive role, which flattens the prerequisites of complex methods and encourages their use across all levels of education. Sat, 01 Feb 2020 00:00:00 GMT https://repository.maseno.ac.ke/handle/123456789/2997 2020-02-01T00:00:00Z