Machine learning applications in risk management: Trends and research agenda
F1000Research,
Journal Year:
2025,
Volume and Issue:
14, P. 233 - 233
Published: April 7, 2025
Abstract
Risk
management
has
become
a
foundational
aspect
in
numerous
industries,
propelling
the
implementation
of
machine
learning
technologies
for
impact
assessment,
prevention,
and
decision-making
processes.
Nevertheless,
lacunae
extant
literature
persist,
particularly
with
regard
to
identification
emergent
trends
transversal
applications.
This
study
addresses
this
limitation
through
bibliometric
analysis
scientific
production
Scopus
Web
Science,
adhering
PRISMA-2020
declaration.
The
findings
reveal
substantial
growth
publications
on
applied
risk
management,
an
increase
98.99%
between
2018
2023.
China,
South
Korea,
United
States
are
identified
as
primary
research-producing
countries.
also
identifies
emerging
trends,
such
application
evaluation
urban
trees
risks
associated
pandemic
severe
acute
respiratory
syndrome
(SARS-CoV-2).
Key
terms
include
random
forest,
support
vector
machines
(SVM),
credit
while
prediction,
postpartum
depression,
big
data,
security
emerge
new
areas
study.
Furthermore,
there
is
transition
from
traditional
approaches
stacking
advanced
deep
feature
selection
techniques,
reflecting
evolution
discipline.
Language: Английский