Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk

George Daniel Brown Swankie, Daniel Broby

Research output: Working paper

1 Downloads (Pure)

Abstract

This paper examines the relationship between Artificial Intelligence (AI) and banking risk management. The global financial crisis highlighted their importance and now banks are subject to more stringent regulation regarding their capital adequacy. Meanwhile, advances in technology are driving changes in the way banks operate. AI is at the core of this and has the potential to revolutionise financial services. It is comprised of several techniques that allow computers to mimic human behavior and analyse vast quantities of data in seconds. These techniques include machine learning, deep learning, speech recognition, natural language processing and visual recognition. We investigate the extent to which each of these techniques can be implemented in the context of financial services. In this respect, we look at credit, operational, liquidity and reputational risk, all of which can have a negative impact on the earnings of an organisation. AI has the potential to help mitigate these risks in banks and address some of the highlighted management issues. We conclude that the application of AI can add significant economic value to banking operations.
Original languageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Pages1-8
Number of pages18
Publication statusPublished - 28 Nov 2019

Fingerprint

Artificial intelligence
Banking risk
Evaluation
Financial services
Global financial crisis
Operational risk
Human behavior
Capital adequacy
Banking
Speech recognition
Deep learning
Reputational risk
Risk management
Natural language processing
Economic value
Liquidity risk
Issue management
Credit risk
Machine learning

Keywords

  • banking
  • regtech
  • fintech
  • regulatory models
  • financial services
  • disruption
  • artificial intelligence
  • AI
  • risk
  • regulation reporting

Cite this

Swankie, G. D. B., & Broby, D. (2019). Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk. (pp. 1-8). Glasgow: University of Strathclyde.
Swankie, George Daniel Brown ; Broby, Daniel. / Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk. Glasgow : University of Strathclyde, 2019. pp. 1-8
@techreport{59864cba5cc944478173224a8dddd38c,
title = "Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk",
abstract = "This paper examines the relationship between Artificial Intelligence (AI) and banking risk management. The global financial crisis highlighted their importance and now banks are subject to more stringent regulation regarding their capital adequacy. Meanwhile, advances in technology are driving changes in the way banks operate. AI is at the core of this and has the potential to revolutionise financial services. It is comprised of several techniques that allow computers to mimic human behavior and analyse vast quantities of data in seconds. These techniques include machine learning, deep learning, speech recognition, natural language processing and visual recognition. We investigate the extent to which each of these techniques can be implemented in the context of financial services. In this respect, we look at credit, operational, liquidity and reputational risk, all of which can have a negative impact on the earnings of an organisation. AI has the potential to help mitigate these risks in banks and address some of the highlighted management issues. We conclude that the application of AI can add significant economic value to banking operations.",
keywords = "banking, regtech, fintech, regulatory models, financial services, disruption, artificial intelligence, AI, risk, regulation reporting",
author = "Swankie, {George Daniel Brown} and Daniel Broby",
year = "2019",
month = "11",
day = "28",
language = "English",
pages = "1--8",
publisher = "University of Strathclyde",
type = "WorkingPaper",
institution = "University of Strathclyde",

}

Swankie, GDB & Broby, D 2019 'Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk' University of Strathclyde, Glasgow, pp. 1-8.

Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk. / Swankie, George Daniel Brown; Broby, Daniel.

Glasgow : University of Strathclyde, 2019. p. 1-8.

Research output: Working paper

TY - UNPB

T1 - Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk

AU - Swankie, George Daniel Brown

AU - Broby, Daniel

PY - 2019/11/28

Y1 - 2019/11/28

N2 - This paper examines the relationship between Artificial Intelligence (AI) and banking risk management. The global financial crisis highlighted their importance and now banks are subject to more stringent regulation regarding their capital adequacy. Meanwhile, advances in technology are driving changes in the way banks operate. AI is at the core of this and has the potential to revolutionise financial services. It is comprised of several techniques that allow computers to mimic human behavior and analyse vast quantities of data in seconds. These techniques include machine learning, deep learning, speech recognition, natural language processing and visual recognition. We investigate the extent to which each of these techniques can be implemented in the context of financial services. In this respect, we look at credit, operational, liquidity and reputational risk, all of which can have a negative impact on the earnings of an organisation. AI has the potential to help mitigate these risks in banks and address some of the highlighted management issues. We conclude that the application of AI can add significant economic value to banking operations.

AB - This paper examines the relationship between Artificial Intelligence (AI) and banking risk management. The global financial crisis highlighted their importance and now banks are subject to more stringent regulation regarding their capital adequacy. Meanwhile, advances in technology are driving changes in the way banks operate. AI is at the core of this and has the potential to revolutionise financial services. It is comprised of several techniques that allow computers to mimic human behavior and analyse vast quantities of data in seconds. These techniques include machine learning, deep learning, speech recognition, natural language processing and visual recognition. We investigate the extent to which each of these techniques can be implemented in the context of financial services. In this respect, we look at credit, operational, liquidity and reputational risk, all of which can have a negative impact on the earnings of an organisation. AI has the potential to help mitigate these risks in banks and address some of the highlighted management issues. We conclude that the application of AI can add significant economic value to banking operations.

KW - banking

KW - regtech

KW - fintech

KW - regulatory models

KW - financial services

KW - disruption

KW - artificial intelligence

KW - AI

KW - risk

KW - regulation reporting

M3 - Working paper

SP - 1

EP - 8

BT - Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk

PB - University of Strathclyde

CY - Glasgow

ER -

Swankie GDB, Broby D. Examining the Impact of Artificial Intelligence on the Evaluation of Banking Risk. Glasgow: University of Strathclyde. 2019 Nov 28, p. 1-8.