Audit Analytics In The Financial Industry
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Audit Analytics in the Financial Industry
Split into six parts, contributors explore ways to integrate Audit Analytics techniques into existing audit programs for the financial industry. Chapters include topics such as fraud risks in the credit card sector, clustering techniques, fraud and anomaly detection, and using Audit Analytics to assess risk in the lawsuit and payment processes.
Culture Audit in Financial Services
In the next wave of conduct regulation in financial markets, from 2021 conduct regulators in the UK and elsewhere expect firms to produce evidence on how they are improving behaviour and culture. Facing this, many practitioners are anxious that their current reporting and management information (MI) are irrelevant to meeting as-yet unclear regulatory expectations. This book provides the insights and tools firms need to report on culture, securing both enhanced business value and the regulator's approval. Culture is now seen as a key contributor to good governance, feeding into existing discourse on environmental, social and governance (ESG) factors and the emerging dialogue on 'non-financial (mis)conduct', but conventional measures of business quality are unfit for the new reporting agenda. Culture Audit in Financial Services follows the arc of 'behavioural regulation' to examine what the regulator really wants, before offering guidance on how culture audit differs from conventional auditing, how to put the latest pure-research findings to work, and the key features of well-designed conduct and culture reports. Written by an impartial author and a variety of contributors with extensive experience working with practitioners, regulators, and many of the world's finest academic initiatives, this book is filled with practical, grounded advice on how best to approach this new challenge and avoid infractions.
Audit Analytics
Author: J. Christopher Westland
language: en
Publisher: Springer Nature
Release Date: 2024-04-04
This book, using R and RStudio, demonstrates how to render an audit opinion that is legally and statistically defensible; analyze, extract, and manipulate accounting data; build a risk assessment matrix to inform the conduct of a cost-effective audit program; and more. Today, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control. Additionally, a firm’s data—particularly in the case of finance, software, insurance and biotech firms—comprises most of the audited value of the firm. Financial audits are critical mechanisms for ensuring the integrity of information systems and the reporting of organizational finances. They help avoid the abuses that led to passage of legislation such as the Foreign Corrupt Practices Act (1977), and the Sarbanes-Oxley Act (2002). Audit effectiveness has declined over the past two decades, as auditor skillsets have failed to keep up with advances in information technology. Information and communication technology lie at the core of commerce today and are integrated in business processes around the world. This book is designed to meet the increasing need of audit professionals to understand information technology and the controls required to manage it. This 2nd edition includes updated code and test. Machine learning, AI, and SEC’s EDGAR data are also, improved and updated. The material included focuses on the requirements for annual Securities and Exchange Commission audits (10-K) for listed corporations. These represent the benchmark auditing procedures for specialized audits, such as internal, governmental, and attestation audits. Many examples reflect the focus of the 2024 CPA exam, and the data analytics-machine learning approach will be central to the AICPA’s programs, in the near future.