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btp-trial-content-test (btp-trial-content) - 2025-07-18T14:06:43.457Z

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Machine Learning Scenario - Jupyter Notebooks

Machine Learning Scenario - Pipelines

We are going to perform Credit Risk Analysis to determine creditworthiness i.e. looking at the customer's attributes like credit history, income, loan amount, age etc. to decide on loan application approval. The dataset for the loan applications will originate from two different Source systems (MS SQL Database - for Loan Attributes and a SAP HANA system - for Applicant Attributes).

Credit Risk Analysis with SAP Data Intelligence Cloud

As a part of financial risk mitigation strategies, businesses need to perform Credit risk analysis to determine creditworthiness of their customers. This involves analyzing customer’s credit history, income, loan amount, age, etc. to decide on loan application approval. However, without a comprehensive predictive analysis based on historical data, an accurate automated prediction of credit risk score is still a major challenge.

This workshop addresses the business challenge with the help of Machine Learning capabilities of SAP Data Intelligence. You will learn how to integrate the business data from disparate data sources like S3, MS-SQL, HANA; build ML Models in Python and HANA Cloud APL. You will learn how to build productive deployment or Inference pipelines to consume the ML models. Finally, you will learn using the ML model in an SAP AI Chatbot.

Credit Risk Analysis assessment with SAP Data Intelligence

As a part of financial risk mitigation strategies, businesses need to perform Credit risk analysis to determine creditworthiness of their customers. This involves analyzing customer’s credit history, income, loan amount, age, etc. to decide on loan application approval. However, without a comprehensive predictive analysis based on historical data, an accurate automated prediction of credit risk score is still a major challenge.  This workshop addresses the business challenge with the help of Machine Learning capabilities of SAP Data Intelligence. You will learn how to integrate the business data from disparate data sources like S3, MS-SQL, HANA; build ML Models in Python and HANA Cloud APL. You will learn how to build productive deployment or Inference pipelines to consume the ML models. Finally, you will learn using the ML model in an SAP AI Chatbot.