Acta Scientific Computer Sciences

Review Article Volume 4 Issue 7

New Financial Risks Arising from Digital Finance: Disputes Over Automated Decision Systems and Algorithmic Assessments by ICT Forensic Expert Witnesses

Stephen Castell*

Chairman, CASTELL Consulting, UK

*Corresponding Author: Stephen Castell, Chairman, CASTELL Consulting, UK.

Received: April 15, 2022; Published: June 09, 2022


Use of Artificial Intelligence (AI) and Machine Learning in the deployment of Automated Decision Systems (ADS), with computer software-implemented algorithms, or ‘algos’, now spreading widely in financial trading and other systems, inevitably mean that new financial risks are arising from such increasing reliance on digital finance. Disputes over the use, and the damaging consequences, of ADS are therefore likely to escalate, and ICT Expert Witness Professionals will doubtless become involved in forensic assessments of such algorithmic disputes. This paper first presents a review of published work in regard to ADS and the use of ‘algos’, noting growing concern over specific ‘bias’ in, and, more generally, the ‘ethics’ of, algorithmic decision-making systems, with the use of ADS for Cybersecurity and Infrastructure Security a standout application area. In regard to digital finance, the author recently gave sworn testimony as expert witness in a USA Financial Industry Regulatory Authority (FINRA) Arbitration hearing, in a dispute over use of an ADS by a major US fund management corporation to close-out the investment trading position of a client, with heavy losses, and this paper sets out the anonymized substance of that testimony. The issues raised in that case will increasingly feature in the financial investment world, and also in society generally, and in government, industry, and commerce. Care should be taken professionally when issues of ‘bias’ or ‘ethics’ in algorithms are raised. Legal professionals must properly examine these subjective concepts within the processes of the humans who specified the Requirements for the algorithms, and not expect to find technical evidence thereof in the computer code itself. ICT professionals are furthermore increasingly concerned that a ubiquitously software-dependent, ADS-driven, society poses a real risk of financial collapse or other catastrophic consequences from software failure or disaster, on a national, or even international, scale. High-profile software-associated tragedies such as VW Dieselgate, Boeing 737 Max, and PO Horizon serve to illuminate the critical issues potentially arising from widescale ADS implementations. Expert investigations must guard against the incorrect ‘presumption of the reliability of computer evidence’ that has become routine in pleadings brought before some courts, and been accepted unchallenged by presiding judges. The IT Leaders Forum of the British Computer Society has initiated a Software Risk and Resilience Working Group to research, gather evidence, study, analyse and deliberate upon these matters, with a focus as much on ADS as on other software applications and systems deployed in the UK. All concerned professionals are welcome to engage with this Working Group.

Keywords: Artificial Intelligence (AI); Machine Learning; Automated Decision Systems; Digital; Finance; Risk; Economics; Management; ADS; Algorithm; Algos; Expert Witness; Forensic; Dispute; Litigation; Bias; Ethics; Cybersecurity; Infrastructure; Financial; Investment; Regulation; Testimony; Opinion; Lawyers; Courts; Software; Failure; Disaster; Dieselgate; Horizon; Reliability; Resilience; Applications; Systems; British Computer Society (BCS)


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Citation: Stephen Castell. “New Financial Risks Arising from Digital Finance: Disputes Over Automated Decision Systems and Algorithmic Assessments by ICT Forensic Expert Witnesses". Acta Scientific Computer Sciences 4.7 (2022): 24-36.


Copyright: © 2022 Stephen Castell. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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