Mark Lokanan

Mark Lokanan

Royal Roads University

H-index: 14

North America-Canada

About Mark Lokanan

Mark Lokanan, With an exceptional h-index of 14 and a recent h-index of 13 (since 2020), a distinguished researcher at Royal Roads University, specializes in the field of Fraud.

His recent articles reflect a diverse array of research interests and contributions to the field:

Exploring Resampling Techniques in Credit Card Default Prediction

The application of machine learning to study fraud in the accounting literature

Predicting money laundering using machine learning and artificial neural networks algorithms in banks

Analyzing public sentiments on the Cullen Commission inquiry into money laundering: harnessing deep learning in the AI of Things Era

Financial fraud detection: the use of visualization techniques in credit card fraud and money laundering domains

Tax avoidance in banking institutions: an analysis of the top seven Nigerian banks

Incorporating machine learning in dispute resolution and settlement process for financial fraud

Money laundering influence on financial institutions and ways to retaliate

Mark Lokanan Information

University

Position

___

Citations(all)

842

Citations(since 2020)

713

Cited By

318

hIndex(all)

14

hIndex(since 2020)

13

i10Index(all)

19

i10Index(since 2020)

16

Email

University Profile Page

Royal Roads University

Google Scholar

View Google Scholar Profile

Mark Lokanan Skills & Research Interests

Fraud

Top articles of Mark Lokanan

Title

Journal

Author(s)

Publication Date

Exploring Resampling Techniques in Credit Card Default Prediction

Mark Lokanan

2024/3/15

The application of machine learning to study fraud in the accounting literature

Sana Ramzan

Mark Lokanan

2024/3/5

Predicting money laundering using machine learning and artificial neural networks algorithms in banks

Journal of Applied Security Research

Mark E Lokanan

2024/1/2

Analyzing public sentiments on the Cullen Commission inquiry into money laundering: harnessing deep learning in the AI of Things Era

Frontiers in The Internet of Things

Mark Lokanan

2023/11/22

Financial fraud detection: the use of visualization techniques in credit card fraud and money laundering domains

Mark E Lokanan

2023/4/18

Tax avoidance in banking institutions: an analysis of the top seven Nigerian banks

Journal of Financial Crime

Dada Folorunso

Mark Eshwar Lokanan

2023/1/2

Incorporating machine learning in dispute resolution and settlement process for financial fraud

Journal of Computational Social Science

Mark E Lokanan

2023/10

Money laundering influence on financial institutions and ways to retaliate

Journal of Money Laundering Control

Darshan Kumar

Mark Eshwar Lokanan

2023/1/2

Predicting mobile money transaction fraud using machine learning algorithms

Applied AI Letters

Mark E Lokanan

2023/4

Revisiting the satyam fraud: a lesson in corporate governance

Mark E Lokanan

Rebecca Wilson-Mah

2023

Two Decades of Accounting Fraud Research: The Missing Meso-Level Analysis

SAGE Open

Mark E Lokanan

Prerna Sharma

2023/9

Financial Exploitation in Canada: A Predictive Model using ML and AI

Kishinchand Poornima Wasdani

Mark Lokanan

2023/3/23

From IDA to IIROC: Has self‐regulation in the Canadian investment industry evolved?

Canadian Public Administration

Mark Lokanan

Kush Sharma

2023/9

Predicting money laundering sanctions using machine learning algorithms and artificial neural networks

Applied Economics Letters

Mark E Lokanan

2023/2/17

The tinder swindler: Analyzing public sentiments of romance fraud using machine learning and artificial intelligence

Journal of Economic Criminology

Mark E Lokanan

2023/12/1

The morality and tax avoidance: A sentiment and position taking analysis

Plos one

Mark Lokanan

2023/7/17

Predicting Suspicious Money Laundering Transactions using Machine Learning Algorithms

Mark Lokanan

Vikas Maddhesia

2023/1/31

Supply chain fraud prediction with machine learning and artificial intelligence

Mark Lokanan

Vikas Maddhesia

2022/9/2

Proceedings of the 9th Global Conference on Business Management and Economics, September 2022–Vancouver, Canada Format: Electronic Book ISBN: 978-1-9990057-7-1

Proceedings of the 9th Global Conference on Business Management and Economics

Mark Lokanan

Sana Ramzan

HM Jahirul Haque

Hasan M Sami

Anne Mastamet Mason

...

2022/9

Fraud prediction using machine learning: The case of investment advisors in Canada

Machine Learning with Applications

Mark Eshwar Lokanan

Kush Sharma

2022/6/15

See List of Professors in Mark Lokanan University(Royal Roads University)