Date of Publication
8-2023
Document Type
Master's Thesis
Degree Name
Master of Information Technology
Subject Categories
Databases and Information Systems
College
College of Computer Studies
Department/Unit
Information Technology
Thesis Advisor
Marivic S. Tangkeko
Defense Panel Chair
Oliver A. Malabanan
Defense Panel Member
Michelle Renee D. Ching
Lissa Andrea K. Magpantay
Abstract/Summary
The impacts and consequences of COVID-19 pandemic significantly changed the strategic direction of many industries globally. In the financial services industry operational resiliency of many financial institutions were challenged driving the shift from the traditional risk management approach into the implementation of risk intelligence solutions. Risk experts recognized the importance of using emerging technologies to build the capability to learn from external sources to supplement internal risk management processes as an important factor to support operational resiliency.
The purpose of the study is to develop an analytics system that will provide operational risk intelligence from a reliable external source useful for financial institutions to gather external insights and support operational resiliency. It involved stimulation of business need for an analytics system in a selected financial institution to validate insights derived from the system and impact to the operational risk management process. The methodology used is the Knowledge Discovery in Databases (KDD) Process Model appropriate for discovering external risk intelligence. Multiple iterations of system development and evaluation were performed to identify business relevant insights that primarily relate to the business, product, cause, and event types.
The overall result of the descriptive analytics revealed new operational risk intelligences that can be presented to various risk management discussions confirmed by the risk experts and focus group discussion participants. Therefore, the stimulation activity of the study helped recognize the need for an analytics system to augment the internal risk management process in the selected financial institution.
Key words: data analytics, operational risk management, descriptive analytics, risk intelligence, financial services
Abstract Format
html
Language
English
Format
Electronic
Physical Description
98 leaves
Keywords
Financial services industry--Risk management; Financial services industry--Information technology
Recommended Citation
Villaraza, J. R. (2023). Descriptive analytics for operational risk intelligence in financial services. Retrieved from https://animorepository.dlsu.edu.ph/etdm_infotech/16
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Embargo Period
8-11-2024
