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By Vishal Chahal, Smruthi Raj Mohan | Published September 18, 2018
Knowing your client is an essential best practice because it is the foundation for all succeeding steps in the credit risk management process. To be successful, you must operate on pertinent, accurate, and timely information. However, client network information is scattered across various sources. This pattern provides real-time information regarding a client, known as a client-network, all collated in a single place. It’s targeted at relationship managers at banks who handle customer investments.
Relationship managers at banks handle client investments. And one of the most important considerations in investing client money for a financial advisor is trying to assess the client’s risk due to certain changes in their environment. In addition, investments are affected by happenings in the ecosystem or client network with events such as Management Change, Management Default, Share Price Deviations, Credit Rating, Strike, and more.
This pattern provides real-time information regarding a client, known as a client-network, all collated in a single place. This information is in compliance with the most important events impacting any organization. It takes real-time information from popular news sites and extracts the clients affected by it with the help of Watson Natural Language Understanding. The application demonstrates a methodology to derive insights about customer insights with IBM Cloud, Watson services, Python Flask and Python NLTK.
Get the detailed instructions in the README file. These steps show you how to:
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