CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Identifying Possible Financial Frauds using SQL Row Pattern Recognition

by Dušan Petković
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 35
Year of Publication: 2022
Authors: Dušan Petković
10.5120/ijca2022922446

Dušan Petković . Identifying Possible Financial Frauds using SQL Row Pattern Recognition. International Journal of Computer Applications. 184, 35 ( Nov 2022), 31-34. DOI=10.5120/ijca2022922446

@article{ 10.5120/ijca2022922446,
author = { Dušan Petković },
title = { Identifying Possible Financial Frauds using SQL Row Pattern Recognition },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2022 },
volume = { 184 },
number = { 35 },
month = { Nov },
year = { 2022 },
issn = { 0975-8887 },
pages = { 31-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number35/32542-2022922446/ },
doi = { 10.5120/ijca2022922446 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:23:13.172406+05:30
%A Dušan Petković
%T Identifying Possible Financial Frauds using SQL Row Pattern Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 35
%P 31-34
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In 2016, the SQL standardization committee finished the work concerning a feature called Row Pattern Recognition. The specification, which was published in the same year, describes the common search for patterns inside the tables’ rows as well as the search inside an existing window frame. In this paper we discuss how this feature can be used to identify suspicious transactions in relation to customers’ bank accounts. Several examples are usedto show the way how transfers to and from one account can be traced, and how possible irregularities can be detected. This paper has two main goals. First, to show strength and conciseness of the SQL specification of this feature. Second, to show a way how to implement complex problems in a particular business area.

References
  1. ISO/IEC TR 19075-5:2016 Information technology -- Database languages -- SQL Technical Reports -- Part 5: Row Pattern Recognition in SQL, https://standards.iteh.ai/catalog/standards/ iso/2521dd59-7047-4938-a25a-2617fde630df/iso-iec-tr-19075-5-2016, last access 2022/08/08.
  2. Ben-Gan, I. T-SQL Window Functions, McGraw-Hill, 2019, ASIN: B07Z5BB6W1.
  3. Petković, D. - Die Unterstützung von SQL/OLAP im SQL-Standard und in relationalen Datenbanksystemen – Teil 2 (in German) , Datenbank Spektrum, 2007, Vol. 7(1), p. 44-52.
  4. Michels, J.;Hare, K.; Kulkarni, K.; Liu. Z.H.– The New and Improved SQL:2016 Standard, SIGMOD Record, Vol. 47, No.2, 2018, http://dx.doi.org/10.1145/3299887.3299897.
  5. Petković, D. – Specification of Row Pattern Recognition in SQL Standard and its Implementation, Datenbank Spektrum, 2022, Vol. 22, p.163-74.
  6. Oracle 12c, MATCH_RECOGNIZE, https://docs.oracle.com/cd/E28280_01/apirefs.1111/e12048/pattern_recog.htm#CQLLR1531, last access 2022/09/01.
Index Terms

Computer Science
Information Sciences

Keywords

SQL Row Pattern Recognition financial frauds MATCH_RECOGNIZE

Powered by PhDFocusTM