Authors :
Norma Grinio-Nunez; Armando E. Abejuela; Romulo P. Soriao
Volume/Issue :
Volume 10 - 2025, Issue 11 - November
Google Scholar :
https://tinyurl.com/kke5hsfd
Scribd :
https://tinyurl.com/y9kjwc36
DOI :
https://doi.org/10.38124/ijisrt/25nov562
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
This study determined the compliance of Commercial Banks on the pillars of the Anti-Money Laundering (AML) and
their Know Your Customers (KYC) Practices in selected cities of the National Capital Region (NCR) with the end view of
ensuring the integrity of financial transactions.
The respondents are primarily younger professionals, with most aged between 25 and 35 years. The banking sector
represented by the study shows a gender imbalance, with a higher proportion of male respondents. The majority of
respondents are located in Quezon City, followed by Taguig City, reflecting the concentration of banking operations in these
urban areas. Most respondents have mid-level banking experience, with 5 to 10 years of service, indicating that the insights
gathered largely represent perspectives from professionals who are familiar with but not senior in the industry.
Commercial banks are seen as largely compliant across the major AML pillars. Banks are particularly effective in risk
assessment and customer due diligence, though there are some inconsistencies in verifying corporate ownership in the latter.
Transaction monitoring is generally practiced well, but there is a need for more consistent application in high-risk
transactions. Reporting and record-keeping are compliant, but some respondents suggested improvements in timely
reporting. Training and education efforts are adequate, though there is a recommendation for more practical scenario-based
training to strengthen AML awareness further.
Generally, there are no significant differences in the assessment of AML compliance based on age, location, years of
experience, or sex. However, a notable exception is customer due diligence, where male respondents rated the banks'
practices slightly higher than female respondents. Banks are seen as effective in implementing KYC practices, especially in
the areas of digital identity verification and ongoing monitoring. While address verification is practiced well.
There were no significant differences in the overall assessment of KYC effectiveness based on demographic factors.
The only significant correlation found was between risk assessment and identity verification.
Keywords :
Anti-Money Laundering (AML), Know Your Customers (KYC, and Commercial Banks.
References :
- Allen, Mike (2017). Triangulation, retrieved: https://methods.sagepub.com/reference/the-sage-encyclopedia-of-communication-research-methods/i14830.xml
- Andrew, Damon P.S, Pedersen, Paul M. and McEvoy, Chad D. (2013). Research Methods and Design in Sport Management, Human Kinetics: United Kingdom
- BSA (1970) Bank Secrecy Act
- Brownlee, Jason (2018, May 9). A Gentle Introduction to Nonparametric Statistics, retrieved: https://machinelearningmastery.com/a-gentle-introduction-to-nonparametric-statistics/
- Calmorin and Calmorin as cited by Gualin, (2021)
- Castillo, Romer (2016, January 26). Who is Slovin and where and how did the Slovin's Formula for determining the sample size for a survey research originated? retrieved from https://www.researchgate.net/post/Who-is-Slovin-and-where-and-how-did-the-Slovins-Formula-for-determining-the-sample-size-for-a-survey-research-originated
- Cherry, Kendra (2020, March 20). How to Identify and Calculate the Mean, Median, and Mode, retrieved: https://www.verywellmind.com/how-to-identify-and-calculate-the-mean-median-or-mode-2795785
- Chip Stapleton, (2023) What Methods Are Used to Launder Money?
- Crossman, Ashley (2017, March 2). Understanding Purposive Sampling, retrieved from https://www.thoughtco.com/purposive-sampling-3026727
- Detecting Digital Money Laundering (2021)
- Frankenfield, Jake (2023), What Is Personally Identifiable Information (PII)? Types and Examples
- Glen, Stephanie (2021, April 25). "Slovin’s Formula: What is it and When do I use it?" From StatisticsHowTo.com: Elementary Statistics for the rest of us! https://www.statisticshowto.com/how-to-use-slovins-formula/
- Hayes, Adam (2022) Regulatory Risk: Definition Vs. Compliance Risk, and Examples
- J.R. Brown (2023), How Money Laundering Works
- J. Chen, (2024) Know Your Client (KYC): What It Means, Compliance Requirements
- Kent State University (2021). SPSS Tutorials: Independent Samples t Test, retrieved: https://libguides.library.kent.edu/spss/independentttest
- Kenton, Will (2023) Anti Money Laundering (AML) Definition: Its History and How It Works
- Know Your Client (KYC): What It Means, Compliance Requirements (2024)
- La Trobe University (2020, May 13). Descriptive statistics: measures of variability, retrieved: https://latrobe.libguides.com/maths/measures-variability
- Lynn, Emily (2020, October 26). How to Calculate the Percentage of Something From a Data Set, retrieved: https://sciencing.com/calculate-percentage-something-set-data-10014589.html
- Marc L. Ross (2023), HSBC's Money Laundering Scandal
- Marc L. Ross (2023), What Role Do Regulators Play In Preventing Money Laundering at Large Banks?
- Money Laundering in the Digital Age (2023)
- Regents of the University of Michigan (2020). Pre-Experimental Designs, retrieved on December 16, 2020 from https://www.researchconnections.org/childcare/datamethods/preexperimental.jsp
- Stephanie, Glen (2021). "F Statistic / F Value: Simple Definition and Interpretation" From StatisticsHowTo.com: Elementary Statistics for the rest of us! https://www.statisticshowto.com/probability-and-statistics/f-statistic-value-test/
- The UN Convention Against Transnational Organized Crime in 2000-21.
- Trochim, William M.K. (2021). Correlation, retrieved: https://conjointly.com/kb/correlation-statistic/
- W. Kenton, (2022), What Is a Suspicious Activity Report (SAR)? Triggers and Filing
This study determined the compliance of Commercial Banks on the pillars of the Anti-Money Laundering (AML) and
their Know Your Customers (KYC) Practices in selected cities of the National Capital Region (NCR) with the end view of
ensuring the integrity of financial transactions.
The respondents are primarily younger professionals, with most aged between 25 and 35 years. The banking sector
represented by the study shows a gender imbalance, with a higher proportion of male respondents. The majority of
respondents are located in Quezon City, followed by Taguig City, reflecting the concentration of banking operations in these
urban areas. Most respondents have mid-level banking experience, with 5 to 10 years of service, indicating that the insights
gathered largely represent perspectives from professionals who are familiar with but not senior in the industry.
Commercial banks are seen as largely compliant across the major AML pillars. Banks are particularly effective in risk
assessment and customer due diligence, though there are some inconsistencies in verifying corporate ownership in the latter.
Transaction monitoring is generally practiced well, but there is a need for more consistent application in high-risk
transactions. Reporting and record-keeping are compliant, but some respondents suggested improvements in timely
reporting. Training and education efforts are adequate, though there is a recommendation for more practical scenario-based
training to strengthen AML awareness further.
Generally, there are no significant differences in the assessment of AML compliance based on age, location, years of
experience, or sex. However, a notable exception is customer due diligence, where male respondents rated the banks'
practices slightly higher than female respondents. Banks are seen as effective in implementing KYC practices, especially in
the areas of digital identity verification and ongoing monitoring. While address verification is practiced well.
There were no significant differences in the overall assessment of KYC effectiveness based on demographic factors.
The only significant correlation found was between risk assessment and identity verification.
Keywords :
Anti-Money Laundering (AML), Know Your Customers (KYC, and Commercial Banks.
