Abstract
This study addresses the problem that Zambia lacks empirical behavioural data on
depositors’ Financial Risk Tolerance (FRT), overconfidence, and bank trust, despite
ongoing efforts to implement a Deposit Insurance System (DIS) following repeated bank
failures. This study aims to support the implementation of a Deposit Insurance System
(DIS) in Zambia, following the enactment of the Zambian Depositor Protection Act in
2011. Zambia has experienced two bank insolvencies: Intermarket Bank in 2016 and
Investrust Bank in 2024, highlighting the necessity of the DIS. The financial biases of
bank depositors are crucial to the implementation process of the DIS. Previous studies
(Afandi and Habibov, 2017; Ansari et al., 2023; Bayar et al., 2020; Chong et al.,2021;
Mishra and Metilda, 2015; Moramarco and Palmisano, 2023) have explored socio-demographic
factors influencing these financial biases, but there is no consensus, and
many studies have limitations, such as homogeneous samples and reliance on secondary
data. This study addresses these limitations in its investigation on how socio- demographic factors
influence financial biases among Zambian bank depositors. It
employs a mixed-method approach to triangulate quantitative data on financial biases
with qualitative insights from industry practitioners (bank managers).
In the quantitative method, where 502 respondents from online and physical surveys were
sampled, 40 Binary Logistic Models (BLMs) were employed to analyse the relationship
between seven socio-demographic factors (age, gender, education, marital status,
number of dependents, home ownership, and Income Source) and three financial biases
(Financial Risk Tolerance, overconfidence, and bank trust). The models estimated the
odds ratio for each respondent about the average for each bias, revealing how each
socio-demographic factor influenced the financial biases.
FRT was measured using the Survey of Consumer Finances (SCF) and the Grable-Lytton
Risk Tolerance Scale (GL-RTS), both of which were strong predictors in the Binary
Logistic Models (statistically significant with p < 0.05). This study fills the Global South
evidence gap of SCF and GL-RTS studies and test the reliability of these instruments
through the Cronbach Alpha test for developing countries. Both SCF and GL-RTS
identified gender, marital status, and financial dependents as significant socio-demographic factors.
GL-RTS also found the Level of Education to be significant showing
an increase in education increase one’s financial risk tolerance. The odd ratios revealed
that for SCF being male increases one’s odds of having above average SCF by 92.2%
while for GL-RTS 68.8%. For SCF being married reduced one’s FRT by 43.3% while for
GL-RTS by 52.9%. A surprising divergent finding for SCF was that having five or more
financial dependents increases one’s FRT by 97.5% while GL-RTS by 107%.
These findings can forecast depositors’ future behaviour, guide policy decisions for
implementing the Deposit Insurance System (DIS), and aid finance industry practitioners,
such as investment advisors, in making client asset allocation decisions.
The Pompian 2012 bias question, intended to measure overconfidence, was found to be
a weak predictor in the Binary Logistic Model (BLM). Conversely, the World Values
Survey (WVS) bank trust question proved to be a strong predictor (p < 0.05), with
education level and financial dependents recognised as significant socio-demographic
factors. These findings are crucial for advocating the Deposit Insurance System (DIS) to
protect depositors, stabilise the financial system, and ultimately enhance savings and
economic growth in Zambia.
For the qualitative method, semi-structured interviews with 5 bank managers provided
data which was analysed using Braun and Clarke’s thematic analysis. While socio-demographic factors
(gender, home ownership, and Income Source) were critical in determining financial risk tolerance, bank managers
prioritise credit risk mitigation tools such as customer income, collateral, and transaction history.
The lack of DIS knowledge among bank managers is a gap that needs to be addressed as DIS implementation is
undertaken. Bank managers utilise both objective and subjective measures to profile
customers. This holistic approach by practitioners highlights the shortcomings of objective
quantitative approaches in accurately profiling depositors. These findings not only inform
DIS policy but also contribute to the understanding of financial decision-making processes
in Zambia. Policy implications include using socio-demographic predictors to design a
targeted DIS communication strategy, strengthening financial stability by identifying
vulnerable depositor groups, and improving risk-profiling tools used by regulators and
banks.