TY - GEN
T1 - Bank Account Classification for Gambling Transactions
AU - Catherine,
AU - Denny,
AU - Shihab, Muhammad Rifki
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/9
Y1 - 2021/4/9
N2 - Financial services provided by banks are often misused for money laundering. Gambling is a criminal offense in the jurisdiction of the Republic of Indonesia. The increase in the number of customers is a challenge for the Bank to supervise the financial transactions. Based on the previous research, classification in machine learning often used to identify money laundering in the banking industry. However, there are no studies about identifying misuse of accounts in gambling activities using machine learning. This research used real financial transaction data using the SLR, experimental, and semi structured interviews with several Subject Matter Expertise. The results of this study indicate the classification with ensemble algorithms such as LightGBM can identify gambling accounts. Based on the evaluation results of classification performance with LightGBM, this model has the best performance compared to other ensemble models at a precision of 97.26%. These findings can be used as a basis for automatic reporting of suspicious financial transactions to financial regulatory.
AB - Financial services provided by banks are often misused for money laundering. Gambling is a criminal offense in the jurisdiction of the Republic of Indonesia. The increase in the number of customers is a challenge for the Bank to supervise the financial transactions. Based on the previous research, classification in machine learning often used to identify money laundering in the banking industry. However, there are no studies about identifying misuse of accounts in gambling activities using machine learning. This research used real financial transaction data using the SLR, experimental, and semi structured interviews with several Subject Matter Expertise. The results of this study indicate the classification with ensemble algorithms such as LightGBM can identify gambling accounts. Based on the evaluation results of classification performance with LightGBM, this model has the best performance compared to other ensemble models at a precision of 97.26%. These findings can be used as a basis for automatic reporting of suspicious financial transactions to financial regulatory.
KW - classification
KW - gambling
KW - machine learning
KW - money laundering
UR - http://www.scopus.com/inward/record.url?scp=85107312303&partnerID=8YFLogxK
U2 - 10.1109/EIConCIT50028.2021.9431874
DO - 10.1109/EIConCIT50028.2021.9431874
M3 - Conference contribution
AN - SCOPUS:85107312303
T3 - 3rd 2021 East Indonesia Conference on Computer and Information Technology, EIConCIT 2021
SP - 302
EP - 308
BT - 3rd 2021 East Indonesia Conference on Computer and Information Technology, EIConCIT 2021
A2 - Alfred, Rayner
A2 - Haviluddin, Haviluddin
A2 - Wibawa, Aji Prasetya
A2 - Santoso, Joan
A2 - Kurniawan, Fachrul
A2 - Junaedi, Hartarto
A2 - Purnawansyah, Purnawansyah
A2 - Setyati, Endang
A2 - Saurik, Herman Thuan To
A2 - Setiawan, Esther Irawati
A2 - Setyaningsih, Eka Rahayu
A2 - Pramana, Edwin
A2 - Kristian, Yosi
A2 - Kelvin, Kelvin
A2 - Purwanto, Devi Dwi
A2 - Kardinata, Eunike
A2 - Anugrah, Prananda
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd East Indonesia Conference on Computer and Information Technology, EIConCIT 2021
Y2 - 9 April 2021 through 11 April 2021
ER -
