Article Review #2: Cybercrime in Society: Prevention and Policy
Student Name: Jared Amonoo-Harrison
School of Cybersecurity, Old Dominion University
CYSE 201S: Cybersecurity and the Social Sciences
Instructor Name: Diwakar Yalpi
Date: April 16, 2026

Introduction
This article examines how spending on CyberTech affects bank stability. It finds a point
where more spending can hurt rather than having stability. The study concludes that even though
CyberTech is needed strategically, spending too much leads to fewer benefits and more risks for
banks worldwide.

Relation/Connection to Social Science Principles
The article connects to social science principles by exploring the mix of technology,
economics, and human behavior within the banking sector. It talks about how technological
advancements influence social structures and institutional responses, especially in the context of
financial stability and risk-taking behaviors within banks. The discussion on human interactions
with technology and the potential for cheating if controls aren’t present also highlights a social
science perspective on operational risk. The study’s view of financial inclusion and digital
disparities affecting cybersecurity behavior among individuals, particularly in developing
nations, reflects social levels and its impact on technological adoption and safety.

Research Question / Hypothesis / Independent Variable / Dependent Variable
Research Question: The study investigates whether the law of diminishing marginal returns from
overspending on CyberTech affects bank stability. It also explores if an extra dollar spent on
CyberTech provides a marginal benefit for stability.
Hypothesis: The proposed hypothesis (HA) is that a marginal increase in CyberTech spending
above what is necessary adversely affects the financial stability of a bank.
Independent Variable: The independent variables are CyberTech spending, measured in two
ways: the natural log of total CyberTech spending and total CyberTech spending as a percentage
of non-interest operating expenses. These variables also include their squared values to test non-
linear relationships.
Dependent Variable: The dependent variable is bank stability, which is proxied by the Z-score.
The Z-score is calculated as ROA + (Equity/Assets)/ROA and indicates a lower probability of
insolvency with a higher score.

Types of Research Methods Used
The study employs a quantitative research approach, analyzing a global sample of banks.
The data on CyberTech spending was manually collected from the financial statements of banks
from 43 countries for the period 2008–2017. The remaining data, such as bank-level and
country-level control variables, were gathered from the Bloomberg database.

Types of Data Analysis Used
OLS Estimation: Ordinary Least Squares (OLS) models were used, correcting standard errors
for country and year clustering.
Dynamic System GMM: Dynamic system GMM (Generalized Method of Moments) models
were applied, including a lag dependent variable to address potential endogeneity issues and
provide more consistent parameter estimates.
Fixed Effect Panel Regressions: Fixed effect panel regression models were employed to
account for omitted variable bias.
Data Visualization: Scatter plots and polynomial regression splines were used to visually
illustrate the relationship between CyberTech spending and bank stability.
Robustness Checks: The study conducted robustness checks using an alternative Z-score
(before taxes) and by splitting samples based on high and low CyberTech spending levels.

Connections to Other Course Concepts
The study highlights diminishing returns, showing that overinvestment in CyberTech can
reduce bank stability. It also connects to organizational decision-making, technological change,
and how FinTech and regulation influence traditional banking models and risk behavior.

Overall Societal Contributions of the Study/Conclusion
The study shows that excessive CyberTech investment can reduce bank stability,
reinforcing diminishing returns. It helps policymakers and bank managers make better
investment decisions and highlights differences between developed and developing countries.
Overall, it improves understanding of cybersecurity’s impact on financial systems and society.