Mba Bt Syllabus
SYSTEM SUPPORTING MONEY LAUNDERING & FRAUD DETECTION
Nithun Ajeeth.K & Senathipathi.R
Department of Banking Technology, Pondicherry University, India
ABSTRACT
Money laundering is the big problem which is getting even more complex than before. The designing the system for prevention of money laundering and fraud detection is a complex task since money launderers have kept pace with the changing times, becoming more technically adept than ever, making the existing systems more vulnerable to financial crimes. In the process of money laundering and fraud detection there exist s three important stages such as identification of the suspicious financial transactions, criminals, providing evidence for the crime committed, freezing of suspicious account and reporting the same to the financial intelligent units or regulators. Unfortunately most anti money laundering systems which are all exists today have no integration between the Know Your
Customer information ( KYC- data collected during opening of the account) & customer due diligence process and hidden network issues. There exists a separate solution for money laundering and fraud detection. To address these issues, novel system is proposed in this paper to enhancing effectiveness with anomaly detection, rules and link analysis, sequence matching, integration of KYC in customer due diligence process, integrating the regulatory compliance & fraud detection elements and a common solution for both money laundering and fraud detection with the help of data mining techniques. Overall the proposed system helps banks and other financial institution to identify the threat of money laundering & fraud in all stages of the process such as placement, layering and integration. Key words: Money laundering, suspicious activity reporting, customer due diligence, hidden network, KYC, anomaly detection, link analysis, sequence matching, data mining.
1. INTRODUCTION
Every year anti-money laundering (AML)
Nithun Ajeeth.K & Senathipathi.R
Department of Banking Technology, Pondicherry University, India
ABSTRACT
Money laundering is the big problem which is getting even more complex than before. The designing the system for prevention of money laundering and fraud detection is a complex task since money launderers have kept pace with the changing times, becoming more technically adept than ever, making the existing systems more vulnerable to financial crimes. In the process of money laundering and fraud detection there exist s three important stages such as identification of the suspicious financial transactions, criminals, providing evidence for the crime committed, freezing of suspicious account and reporting the same to the financial intelligent units or regulators. Unfortunately most anti money laundering systems which are all exists today have no integration between the Know Your
Customer information ( KYC- data collected during opening of the account) & customer due diligence process and hidden network issues. There exists a separate solution for money laundering and fraud detection. To address these issues, novel system is proposed in this paper to enhancing effectiveness with anomaly detection, rules and link analysis, sequence matching, integration of KYC in customer due diligence process, integrating the regulatory compliance & fraud detection elements and a common solution for both money laundering and fraud detection with the help of data mining techniques. Overall the proposed system helps banks and other financial institution to identify the threat of money laundering & fraud in all stages of the process such as placement, layering and integration. Key words: Money laundering, suspicious activity reporting, customer due diligence, hidden network, KYC, anomaly detection, link analysis, sequence matching, data mining.
1. INTRODUCTION
Every year anti-money laundering (AML)