Designing an AI Solution for Time-Series Data Analysis and Fraud Detection

Identifying Deviations from Normal Behavior Using Cognitive Services

Question

You are working on designing an AI solution to perform analysis on time-series data in batches and prevent fraud detection by identifying deviations from the normal behavior.

Which cognitive service would you use?

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D.

Correct Answer: C.

Option A is INCORRECT.

Personalizer is not a tool for anomaly detection, as required in this scenario.

The personalizer helps the application learn from real-time behavior and present the best experience to customers.

Option B is INCORRECT.

Text Analytics performs majorly below natural language functions over raw text.

-sentiment analysis

-key-phrase extraction

-named entity recognition, and

-language detection.

Option C is CORRECT.

Anomaly Detector helps in monitoring time-series data and anomaly detection with machine learning.

Option D is INCORRECT.

Ink Recognizer is a service that is set to retire.

Ink Recognizer helps with certain activities related to digital ink recognition.

References:

The cognitive service that would be best suited for analyzing time-series data and detecting anomalies is the Anomaly Detector service.

The Anomaly Detector service uses machine learning algorithms to identify anomalies or outliers in time-series data by analyzing patterns and trends over time. This service can be used for a variety of applications, including fraud detection, predictive maintenance, and quality control.

In the case of fraud detection, the Anomaly Detector service can be trained on historical data to identify patterns of behavior that are considered normal. Once the model has been trained, it can be used to analyze new data in real-time and identify any deviations from the expected behavior.

Personalizer is a cognitive service that uses reinforcement learning to deliver personalized content recommendations. This service is typically used for applications such as e-commerce, advertising, and personalized news feeds.

Text Analytics is a cognitive service that can be used to extract insights from unstructured text data, such as customer feedback or social media posts. This service can be used for a variety of applications, including sentiment analysis, entity recognition, and language detection.

Ink Recognizer is a cognitive service that can be used to recognize handwriting in digital ink input. This service can be used for applications such as digital note-taking or signature verification.

Overall, the Anomaly Detector service would be the best choice for analyzing time-series data and detecting anomalies for fraud detection.