UNIVERSITY OF NAIROBI

COLLEGE OF BIOLOGICAL AND PHYSICAL SCIENCES

SCHOOL OF COMPUTING AND INFORMATICS

DIGITAL LENDING: STRENGTHENING TECHNOLOGY

RISK MANAGEMENT IN MOBILE MONEY LENDING

GEOFREY NYAMARI OGOTI

REG NO: P54/6142/2017

SUPERVISOR: CHRISTOPHER A. MOTURI

A Research Project Submitted in Partial Fulfilment of the Requirement for the Award of the

Degree of Master of Science in Information Technology Management,

School of Computing and Informatics, University of Nairobi

June 2019

11

2.8.1 The Risk Governance Perspective in the Technology Lending

The risk governance perspective focuses on key areas of ICT risk, these are tolerance,

awareness and communication, appetite, accountability and culture. (ISACA, 2009).

In this study, it is recognized that an organization’s technologies are key assets as they set the

rate at which change and adaptability in a firm can happen (Zhu et al. 2006). In light of this,

proper risk governance of all the resources an organization has are key to ensure adaptability

in a competitive environment that does not allow for error. The resources can be linked to

people, process or technology.

In review of literature, a well-managed risk governance structure ensures that all innovation

gaps within a firm are filled to influence greater rate of growth. (Dwivedi, Nripendra, Anand,

Clement, & Williams, 2017)

Figure 1: Proposed Framework. Source: (ISACA, 2009)

13

Figure 2: Conceptual framework

Hypothesis 1 – IT risk governance has a significant influence on the adequacy of technology

risk management.

Hypothesis 2 – IT risk evaluation has an influence on the adequacy of technology risk

management.

Hypothesis 3 – IT risk response mechanisms have an effect on the adequacy of technology risk

management.

Hypothesis 4 – Whether a firm is regulated or not has an effect on its adequacy of technology

risk management

15

Table 1: Sampled Mobile Lenders

Bank Number of Loan

Accounts (in Millions)

% of the

Market

1 KCB Bank Kenya Ltd 1.263 17.70%

2 Co - operative Bank of Kenya Ltd 0.62 8.70%

3 Equity Bank Kenya Ltd 0.67 9.40%

4 Standard Chartered Bank (K) Ltd 0.05 0.70%

5 Diamond Trust Bank 0.015 0.20%

6 Barclays Bank of Kenya Ltd 0.222 3.10%

7 Commercial Bank of Africa 3.92 54.80%

8 Stanbic Bank Kenya Ltd 0.032 0.40%

Total 6.792 94.90%

3.3 Sampling Frame and Technique

Purposive sampling was employed in this research as it enables a researcher to select

information that is relevant and rich in content to the issues under study (Kombo & Tromp,

2006). In this case, purposive sampling is applied to only the institutions that are offering

mobile money lending.

A sample size of 30 and above was deemed acceptable (Oates, 2006). The research required

input from respondents at various levels involved in the technology risk management and

digital lending process e.g. top management, supervisors and junior staff; as well employees in

different areas of specialization e.g. technology, credit, finance, systems audit, financial audit.

From each of these stratums, simple random sampling was used to select respondents from

whom information was obtained.

Table 2: Sampling Frame for Questionnaires

Department Function Sample

Technology Systems Design, Maintenance and Development 10

Audit Systems Audit 10

Credit Lending Management 10

Risk Risk Management 10

Information Security Cyber and information security management 10

17

Figure 3: Interpretation of Cronbach's Alpha

Validity is the accuracy of inferences based on research results (Mugenda, 2008).

To establish the validity of the questionnaire, three experts were provided with the

questionnaire. One expert was an information systems auditor, another was a financial analyst

while the last one was a credit rating professional. Each of the experts scored items each item

on a scale and gave recommendations. The recommendations helped to improve the

questionnaire wording and placement.

The content validity index (CVI) was calculated as:

Content Validity Index = 𝐴𝑔𝑟𝑒𝑒𝑑 𝐼𝑡𝑒𝑚𝑠 𝑏𝑦 𝐸𝑥𝑝𝑒𝑟𝑡𝑠 𝑎𝑠 𝑆𝑢𝑖𝑡𝑎𝑏𝑙𝑒 𝑎𝑛𝑑 𝑉𝑎𝑙𝑖𝑑

𝑇𝑜𝑡𝑎𝑙 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐼𝑡𝑒𝑚𝑠

Table 3: Content Validity Index Measurement

Relevant Not Relevant Total

Information Systems Auditor (Expert 1) 30 3 33

Credit Risk Analyst (Expert 2) 28 5 33

Financial Analyst (Expert 3) 31 2 33

Total 89 10 99

The CVI value obtained of 0.8989 enabled the questionnaire to pass the validity test. A pilot

test was conducted after establishing the reliability and validity.

48

The variables were mapped for regression analysis as illustrated below:

Figure 4: Mapping of Variables for Regression Analysis

The results based on the data and analysis done in R is as below:

Figure 5: Regression Analysis - Test of Hypothesis

51

The detailed R output is shown below:

Figure 6: Correlation Analysis

The results show that the independent variables are strongly and positively correlated to the

dependent variable with statistically significant p-values.

53

Figure 7: Comparison of Risk Governance Performance

Regulated entities outperform their unregulated competitors. In assessing the adequacy of

technology risk management in regulated and unregulated digital lending environments, a

review was done on evaluation and response mechanisms.

The results shown below show that for regulated entities, there is a thorough understanding of

technological threats and the actions in response of the harm they are likely to cause.

For unregulated entities there is opportunity for growth and development in this area. Gaps

were identified that expose weaknesses in evaluation of technology risks and responses in a

timely manner. These gaps could be exploited and expose the firms to loss of revenue and

reputation.

Figure 8: IT Risk Evaluation and Response Comparison

59

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