Effectiveness of Technology in Assisting the UK Private Banks - Research Proposal Example

Tein Pei Lee (0921832) THE EFFECTIVENESS OF TECHNOLOGY IN ASSISTING UK PRIVATE BANKS IN ANTI-MONEY LAUNDERING Problem mentFrom the beginning of this decade, banks have used the most sophisticated tools and techniques to ensure that signs of money laundering relating to any account are detected and appropriate actions are taken. However, in practice, it is not really clear if the technology and software used so far has been able to meet the objective of preventing Anti-Money Laundering in UK. Main Research Question This research therefore addresses the question; how effective are the technological tools in the detection of money laundering in UK Private Banks? Rationale for the Study ““Money laundering" is the process whereby the proceeds of criminal activities are "laundered" or “cleaned” via a series of transactions through the financial system with the aim of concealing the true source of the proceeds.” (Lee Sieu, 2011). Money-Laundering refers to the practice of presenting criminal activities as legitimate. In most cases, laundered money ends up in the banks. In order to ensure that banks play a whistleblowing role, they are required to use the most sophisticated technology to ensure this. This therefore means that banks need to put together the most effective tools to ensure this. The research will therefore seek to use techniques of empirical research to assess technology used by banks in UK to evaluate and control the threat of money laundering. Objectives The aim of the research is to examine, assess and evaluate how effectively the existing software and related tools used by UK private banks have been able to detect and combat money laundering. This aim translates into the following objectives: 1. Identification of the risks of money laundering that private banks face in UK 2. Evaluation of the various software used by private banks to identify and control money laundering. 3. Critical assessment of the effectiveness of the various software in detecting and controlling money laundering. 4. Identification of aspects of money laundering risk that is not duly covered by existing technology in UK banks. Research Procedures and Methodology Data Type The research will be a deductive qualitative research. As such it will utilise elements of primary data, the research will therefore be based on information collected from the various banks and activities found in the research. From this, there will be a deduction of trends and activities to find out whether the technology in use is effective or not. Data Collection Method Sampling is necessary where the researcher cannot conduct a study of all the elements of the universal population under study. In the case of UK, there is a vast range of banks that operate in this country. It is therefore going to be difficult to study all the banks. Thus for the gathering information purpose, the author has decided to divide the banks into three major classes: 1. Major international commercial banks. 2. Smaller Retail banks 3. Other financial institutions with banking functions. The research will therefore take one to five banks in each category, depending on present conditions. This will enable the researcher to get a fair idea of the systems of these banks for appropriate decisions to be taken. There will be two main forms of data collection in the research. This will be done through interviews and surveys. The various forms of risks, inherent, transactional, behavioural and analytical will be assessed in each bank through interviews with staff members, particularly managerial staff who have in-depth knowledge about these ideas and how it affects them in their peculiar setting. This interview will also gather information about the information system used by the bank and the software they use. From there, a questionnaire will be developed, using ordinal variables to assess the effectiveness of the technology and information system used. Ordinal variables are variables that present elements for ranking (Kothari, 2005). The broad elements of the desirable elements of anti-money laundering technology will be put into questionnaires to inquire about the effectiveness of each component of the money laundering technology in operation in the bank. The respondents will be managers, IT staff and actual compliance officers of the bank. The questionnaire will categorize the efficiency and effectiveness elements of ideal anti-money laundering tools in a range from 1 to 5. Respondents will be required to judge the efficiency and effectiveness elements as they have experienced it in the use of the tools in question. This will entail between 15 and 30 questions and would vary per the category of respondents. At the end of the questionnaires, respondents will have the opportunity to pass open ended comments on the efficiency and effectiveness of the system they use. The next step will be to conduct interviews with top-level management and IT staff to find out what the bank does to check money laundering through its internet banking and ATM transactions. This will give an understanding of how technology is expanded to cover the grey areas of money laundering in banks. Data Analysis Method Since the research will aim at collecting data and information, there will be the need to define variables in the research to support the testing process. Nominal variables as “the most basic level of measurement” in a research. Thus the primary research will focus on identifying and operationalizing elements of these two areas. Tentatively, the following elements define the various variables identified. Menon & Kumar (2011) identify four main risks in controlling money laundering. They are: 1. Inherent Risks of clients 2. Transaction risks 3. Behavioural risks and 4. Analytical risks Inherent risks in clients entail opening an account for a Politically Exposed Person (PEP). This opens the bank to risks because of the likelihood of such a person using the bank as a vehicle for money laundering. Such clients should be identified and reported for prompt action or monitored to a high degree. Transaction risks entail the chance of each and every transaction being linked to some form of money laundering whilst behavioral risks refers to certain consistent actions that imply an intent for money laundering. Above all, the bank needs to have a way of getting an overall analysis of activities and people in the bank to get clues of money laundering and take appropriate action where necessary. Failure to do so presents an analytical risk. These variables will be operationalized by being put in a practical form that will be matched against the elements of technology actually used by the banks. The desirable elements that will be emphasised are KYC solutions, Name Analysis, Peer Group Analysis, Transaction analysis, Time sequence scoring and Risk scoring. Information from the initial interview will be matched against the data collected from the surveys. This way, the areas that technology is effectively identifying and controlling money laundering risks will be noted whilst areas of weakness will also be identified. Also, efforts made to control the grey areas will be identified and noted appropriately. Interpretation & Validity Since the research is a deductive research, the paper will conclude by making inferences on the strengths and weaknesses of the technological systems used by private banks in combating money laundering in the UK. These theories will be based on generalisations that can be conveniently made from the findings. Also, a section from the finding will focus on what banks are doing to catch up with money-laundering detection and control in the two grey areas. Planning Horizon The first week will entail the design of the research. This will involve the structures and basic design of interview questions and questionnaires. In the second week, the operationalization of the research will be completed. From week 3 to week 5, interviews will be conducted. The findings will lead to the upgrade of the initial questionnaires. In Week 6 to 8, surveys will be conducted to identify facts and figures relating to technology and how effective they are. In Week 9, there will be the collation of findings and in Week 10, the final research will be written and completed. Usefulness Basically, the research analyses trends in AML control through technology in banks in the UK using empirical and scientific methods. The research can give the management and IT professionals of bank an insight into how effectively their technology is performing in practice. It will also lay the foundation for future research into the effectiveness of technology in banks. This is because information about the findings is not readily available on the market. Also, the gathering of information on the subject is likely to prompt the need for change and improvement, particularly in grey areas relating to the use of technology to cover AML like ATMs and Internet Banking. It is hoped that the research will give way for innovative methods for the improvement of technology in these areas not controlled by technology in the fight against money laundering. Limitations The research is limited by the fact that the samples might not reflect all the systems and technologies used to prevent money laundering. This is because there are a countless number of software options that can be used by various banks in UK at every given time (Financial Security Net, 2011). Also, the research does not take into account current and emerging research into anti-money laundering. This can prove problematic since there is continuous research into the subject at different points in time. This makes the area of research very volatile and prone to change. Ethical Issues/ Considerations The main ethical issue is about confidentiality. Banks might find it a bit inappropriate to release information about how they operate and monitor money-laundering matters since it is sensitive to their operations. To curb this, before the research commence, consent letters will sent to various levels of managements of the banks that have chosen in order to seek permission. The letters will state clearly that the data collected will follow the relevant data protection act of UK and also avoid issues relating to the leakage of information to third parties. Words count :1601 List of References Financial Security Net (2011): What is Anti-Money Laundering Software [on-line]. Available at: [accessed 02 July 2011]. Kothari, C. R. (2005) Research Methodology New Delhi: New Age Publishing. Pp.59 Lee Seiu, Kin (2011) “Cross Border Statutes and Other Measures to Curb Money-Laundering in Singapore” [on-line]. Available at: [accessed 02 July 2011]. Menon, Rajesh & Kumar, Sanjaya (2011) Understanding The Role of Technology in Anti-Money Laundering Compliance – A Strategic Model for Financial Institutions. Infosys Technologies Ltd. White Paper Bangalore, India. Pp.2 Read More