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Same Tactics, Different Scripts: What Contact Center Fraud Sounds Like in the Age of Coronavirus

pindrop

With verified account numbers and some basic information, a fraudster has all they need to execute fraud through the phone channel using convincing scripts involving the current crisis to socially engineer contact center agents and individuals. . The New Fraud Scripts. Travel-Related Inconveniences and Emergencies .

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Everything You Need to Know About Auto Attendant

Hodusoft

In this blog post, we will discuss everything about auto attendants starting from what they are, how they work, the pros and cons of using auto attendants, how to set up an auto attendant, and how to include scripts. Pros of Using Auto Attendant Cons of Auto Attendant Auto Attendant Scripts – What to Record? Read on to know more.

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Five Keys to Growing and Optimizing Your Customer Service Team

CSM Magazine

Victor Obando, VP of Customer Solutions, ActivTrak Earlier this year the World Bank predicted the global economy would slow for a third straight year in 2024. Tools powered by AI technology like ChatGPT can help speed case resolution by identifying familiar types of inquiries and responding with automated emails and/or scripts.

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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

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Build custom code libraries for your Amazon SageMaker Data Wrangler Flows using AWS Code Commit

AWS Machine Learning

It contains over 300 built-in data transformation steps to aid with feature engineering, normalization, and cleansing to transform your data without having to write any code. For this post, we use the bank-full.csv data from the University of California Irving Machine Learning Repository to demonstrate these functionalities.

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Build and train ML models using a data mesh architecture on AWS: Part 2

AWS Machine Learning

The data scientists in this team use Amazon SageMaker to build and train a credit risk prediction model using the shared credit risk data product from the consumer banking LoB. Now that you have a subset of the data as a dataframe, you can start exploring the data and see what feature engineering updates are needed for model training.

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Définir l'IA générative : de quoi s'agit-il et comment l'utiliser en toute sécurité ?

Inbenta

For example, if a bank or fiduciary were to provide misleading information via a LLM chatbot, lawsuits and penalties would surely follow. Improve the accuracy of AI-generated content by tapping into Inbenta’s NLP’s engine. Regulators in the U.S. Combine the benefits of Conversational AI and Generative AI.