Artificial Intelligence Fundamentals
Expert-defined terms from the Postgraduate Certificate in AI Applications in Auditing course at LearnUNI. Free to read, free to share, paired with a globally recognised certification pathway.
**Artificial Intelligence (AI)** #
**Artificial Intelligence (AI)**
Concept #
A field of computer science that focuses on creating intelligent machines that can think and learn like humans.
AI models can analyze large amounts of data, identify patterns and make decision… #
For example, AI can be used in auditing to analyze financial transactions and detect anomalies that may indicate fraud.
**Anomaly Detection** #
**Anomaly Detection**
Concept #
The process of identifying unusual data points or events in a dataset.
Anomaly detection can be used in auditing to identify fraudulent transactions or… #
For example, an unexpected increase in expense claims from a particular employee could be flagged as an anomaly for further investigation.
**Auditing** #
**Auditing**
Concept #
The process of examining an organization's financial records to ensure they are accurate and comply with regulations.
AI can be used in auditing to automate time #
consuming tasks, reduce errors and improve the accuracy of financial reporting. For example, AI algorithms can be used to analyze financial transactions and identify potential fraud or compliance issues.
**Deep Learning** #
**Deep Learning**
Concept #
A subset of machine learning that uses artificial neural networks to model and solve complex problems.
Deep learning algorithms can analyze large amounts of data and learn to recogniz… #
For example, deep learning can be used in auditing to analyze financial transactions and identify potential fraud or compliance issues.
**Feature Engineering** #
**Feature Engineering**
Concept #
The process of selecting and transforming variables or features in a dataset to improve the performance of machine learning algorithms.
Feature engineering is an important step in preparing data for machine learning #
By selecting and transforming relevant features, machine learning algorithms can better learn from the data and make more accurate predictions. For example, in auditing, feature engineering can be used to select relevant financial variables and transform them to improve the accuracy of fraud detection algorithms.
**Fraud Detection** #
**Fraud Detection**
Concept #
The process of identifying and preventing fraudulent activities.
AI can be used in fraud detection to analyze financial transactions and identify… #
For example, machine learning algorithms can be trained to recognize patterns of fraudulent behavior and flag suspicious transactions for further investigation.
**Machine Learning** #
**Machine Learning**
Concept #
A subset of AI that uses statistical techniques to enable machines to improve with experience.
Machine learning algorithms can analyze large amounts of data and learn to recog… #
For example, machine learning can be used in auditing to analyze financial transactions and identify potential fraud or compliance issues.
**Neural Networks** #
**Neural Networks**
Concept #
A computing system inspired by the human brain, designed to simulate the way humans learn and process information.
Neural networks can analyze large amounts of data and learn to recognize pattern… #
For example, neural networks can be used in auditing to analyze financial transactions and identify potential fraud or compliance issues.
**Natural Language Processing (NLP)** #
**Natural Language Processing (NLP)**
Concept #
A field of AI that focuses on the interaction between computers and human language.
NLP can be used in auditing to analyze text data, such as emails and chat logs,… #
For example, NLP algorithms can be trained to recognize patterns of inappropriate behavior, such as harassment or discrimination, and flag them for further investigation.
**Outlier Detection** #
**Outlier Detection**
Concept #
The process of identifying data points that are significantly different from other data points in a dataset.
Outlier detection can be used in auditing to identify fraudulent transactions or… #
For example, an unexpected increase in expense claims from a particular employee could be flagged as an outlier for further investigation.
**Predictive Analytics** #
**Predictive Analytics**
Concept #
The use of statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.
Predictive analytics can be used in auditing to identify potential fraud or comp… #
For example, predictive analytics algorithms can be trained to recognize patterns of fraudulent behavior and flag suspicious transactions for further investigation.
**Risk Management** #
**Risk Management**
Concept #
The process of identifying, assessing and prioritizing risks in an organization.
AI can be used in risk management to analyze financial transactions and identify… #
For example, machine learning algorithms can be trained to recognize patterns of fraudulent behavior and flag suspicious transactions for further investigation.
**Supervised Learning** #
**Supervised Learning**
Concept #
A type of machine learning in which the algorithm is trained on labeled data to make predictions on new, unseen data.
Supervised learning algorithms are commonly used in auditing to analyze financia… #
For example, a supervised learning algorithm can be trained to recognize patterns of fraudulent behavior in historical financial data and then used to analyze new financial transactions for potential fraud.
**Text Analytics** #
**Text Analytics**
Concept #
The process of transforming unstructured text data into structured data for analysis.
Text analytics can be used in auditing to analyze text data, such as emails and… #
For example, text analytics algorithms can be trained to recognize patterns of inappropriate behavior, such as harassment or discrimination, and flag them for further investigation.
**Unsupervised Learning** #
**Unsupervised Learning**
Concept #
A type of machine learning in which the algorithm is trained on unlabeled data to identify patterns and relationships in the data.
Unsupervised learning algorithms can be used in auditing to analyze financial tr… #
For example, an unsupervised learning algorithm can be used to identify unusual patterns in financial data that may indicate fraud or non-compliance.
**Validation** #
**Validation**
Concept #
The process of evaluating the performance of a machine learning model.
Validation is an important step in the machine learning process #
By evaluating the performance of a machine learning model, we can ensure that it is accurate and reliable. For example, in auditing, a machine learning model can be validated by testing it on a separate dataset to ensure that it can accurately identify potential fraud or compliance issues.
**Visualization** #
**Visualization**
Concept #
The process of representing data in a visual format.
Visualization can be used in auditing to represent financial data in a visual fo… #
For example, a visualization of financial transactions can be used to identify unusual patterns that may indicate fraud or non-compliance.
Note #
The above glossary terms are provided as a reference for the Postgraduate Certificate in AI Applications in Auditing. It is important to note that the field of AI is constantly evolving, and new terms and concepts are being developed regularly. As such, this glossary may not be comprehensive and may require updates as new technologies and techniques emerge.