東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Using Financial Technology To Build ...

Thompson-Hidalgo, Janice.

Linked to FindBook

Google Book

Amazon

博客來

Using Financial Technology To Build A Dynamic Customer Profile To Track Changes in Customer Expected Transactional Behavior Accurately.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using Financial Technology To Build A Dynamic Customer Profile To Track Changes in Customer Expected Transactional Behavior Accurately./
Author:	Thompson-Hidalgo, Janice.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	53 p.
Notes:	Source: Masters Abstracts International, Volume: 80-07.
Contained By:	Masters Abstracts International80-07.
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13423212
ISBN:	9780438754119

Using Financial Technology To Build A Dynamic Customer Profile To Track Changes in Customer Expected Transactional Behavior Accurately.
Thompson-Hidalgo, Janice.

Using Financial Technology To Build A Dynamic Customer Profile To Track Changes in Customer Expected Transactional Behavior Accurately. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 53 p.

Source: Masters Abstracts International, Volume: 80-07.

Thesis (M.S.)--Utica College, 2018.

This item must not be added to any third party search indexes.

Anti-money laundering solutions are used by financial institutions to manage risks of money laundering, terrorist financing, and other illegal activity. However, with the ongoing evolution of technology, illicit activity is becoming more complex thereby making it increasingly challenging to manage these risks. Critical components in appropriately monitoring suspicious activity include a thorough understanding of each customer, their business, projected transactional activity, and related potential risk exposure. Customer Due Diligence (CDD) plays an essential role in an effective AML program. The lack of accurate CDD information obtained as part of ongoing monitoring results in financial institutions being unable to effectively monitor transactional activity, resulting in higher regulatory scrutiny, increased monetary fines, poor publicity, and a larger increase in fixed costs associated with operating an adequate AML compliance infrastructure. This paper proposes a methodology that can enhance CDD monitoring by making the AML program more predictive of suspicious activity while reducing false positive alerts and the time required for investigation. Automating expected customer behavior in alignment with customer profile information and customer transactional activity can lead to the construction of a dynamic customer profile that results in an accurate representation of expected transactional behavior. To achieve this goal, the proposed solution will use a combination of two intelligent agents to predict expected customer behavior through the use of dynamic profiling while building a comprehensive customer risk profile.

ISBN: 9780438754119Subjects--Topical Terms:

1030799
Information Technology.

Using Financial Technology To Build A Dynamic Customer Profile To Track Changes in Customer Expected Transactional Behavior Accurately.
LDR:02810nmm a2200337 4500 001 2206714
005 20190906082735.5
008 201008s2018 ||||||||||||||||| ||eng d
020 $a 9780438754119
035 $a (MiAaPQ)AAI13423212
035 $a (MiAaPQ)utica:11354
035 $a AAI13423212
040 $a MiAaPQ $c MiAaPQ
100 1 $a Thompson-Hidalgo, Janice. $3 3433631
245 1 0 $a Using Financial Technology To Build A Dynamic Customer Profile To Track Changes in Customer Expected Transactional Behavior Accurately.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 53 p.
500 $a Source: Masters Abstracts International, Volume: 80-07.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Choo, Kyungseok.
502 $a Thesis (M.S.)--Utica College, 2018.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a Anti-money laundering solutions are used by financial institutions to manage risks of money laundering, terrorist financing, and other illegal activity. However, with the ongoing evolution of technology, illicit activity is becoming more complex thereby making it increasingly challenging to manage these risks. Critical components in appropriately monitoring suspicious activity include a thorough understanding of each customer, their business, projected transactional activity, and related potential risk exposure. Customer Due Diligence (CDD) plays an essential role in an effective AML program. The lack of accurate CDD information obtained as part of ongoing monitoring results in financial institutions being unable to effectively monitor transactional activity, resulting in higher regulatory scrutiny, increased monetary fines, poor publicity, and a larger increase in fixed costs associated with operating an adequate AML compliance infrastructure. This paper proposes a methodology that can enhance CDD monitoring by making the AML program more predictive of suspicious activity while reducing false positive alerts and the time required for investigation. Automating expected customer behavior in alignment with customer profile information and customer transactional activity can lead to the construction of a dynamic customer profile that results in an accurate representation of expected transactional behavior. To achieve this goal, the proposed solution will use a combination of two intelligent agents to predict expected customer behavior through the use of dynamic profiling while building a comprehensive customer risk profile.
590 $a School code: 1754.
650 4 $a Information Technology. $3 1030799
650 4 $a Criminology. $3 533274
690 $a 0489
690 $a 0627
710 2 $a Utica College. $b Economic Crime Management. $3 2098214
773 0 $t Masters Abstracts International $g 80-07.
790 $a 1754
791 $a M.S.
792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13423212