| 000 | 02482nam a22002177a 4500 | ||
|---|---|---|---|
| 008 | 240110b2022 |||||||| |||| 00| 0 eng d | ||
| 020 | _a9781484284056 | ||
| 082 | _a657.0285 SEK-M | ||
| 100 | _aSekar, Maris | ||
| 245 |
_aMachine learning for auditors : _bautomating fraud investigations through artificial intelligence / _cMaris Sekar |
||
| 260 |
_aIndia _bApress _c2022 |
||
| 300 | _a242 p. | ||
| 365 |
_aINR _b829.00 |
||
| 500 | _aUse artificial intelligence (AI) techniques to build tools for auditing your organization. This is a practical book with implementation recipes that demystify AI, ML, and data science and their roles as applied to auditing. You will learn about data analysis techniques that will help you gain insights into your data and become a better data storyteller. The guidance in this book around applying artificial intelligence in support of audit investigations helps you gain credibility and trust with your internal and external clients. A systematic process to verify your findings is also discussed to ensure the accuracy of your findings. Machine Learning for Auditors provides an emphasis on domain knowledge over complex data science know how that enables you to think like a data scientist. The book helps you achieve the objectives of safeguarding the confidentiality, integrity, and availability of your organizational assets. Data science does not need to be an intimidating concept for audit managers and directors. With the knowledge in this book, you can leverage simple concepts that are beyond mere buzz words to practice innovation in your team. You can build your credibility and trust with your internal and external clients by understanding the data that drives your organization. What You Will Learn * Understand the role of auditors as trusted advisors * Perform exploratory data analysis to gain a deeper understanding of your organization * Build machine learning predictive models that detect fraudulent vendor payments and expenses * Integrate data analytics with existing and new technologies * Leverage storytelling to communicate and validate your findings effectively * Apply practical implementation use cases within your organization | ||
| 650 | _aMachine learning | ||
| 650 | _aAuditing, Internal--Data processing | ||
| 650 | _aCorporations--Accounting--Data processing | ||
| 650 | _aFraud--Prevention | ||
| 650 | _aArtificial intelligence--Data processing | ||
| 650 | _aBusiness--Data processing | ||
| 999 |
_c91495 _d91495 |
||