Dataiku Case Studies Malakoff Humanis: Improving Customer Relations With the Power of NLP

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	Malakoff Humanis: Improving Customer Relations With the Power of NLP Dataiku

Malakoff Humanis: Improving Customer Relations With the Power of NLP

Dataiku

Technology Category	Analytics & Modeling - Natural Language Processing (NLP)
Applicable Industries	Healthcare & Hospitals
Services	Data Science Services
Challenge	Malakoff Humanis, the leading non-profit group health insurer in France, was facing growing challenges in keeping up with customer demands and providing quality customer service. The company offers supplementary health, welfare, and pension contracts to companies, employees, self-employed individuals, and single-payer individuals. It covers healthcare reimbursements in addition to the French social security and guides clients in their choice of care establishments. The company has a dedicated data science and analytics department led by a Chief Data Officer. The data department is comprised of four main branches, each in charge of Data Science and Analytics, Data Governance, Data Architecture and Cloud, and AI and Data Visualization. However, the company was struggling to effectively manage customer claims and improve telephone customer assistance. Read More
About Customer	Malakoff Humanis is the leading non-profit group health insurer in France. It offers supplementary health, welfare, and pension contracts to companies, employees, self-employed individuals, and single-payer individuals. As a complementary health insurance, the mutual fund covers healthcare reimbursements in addition to the French social security, and guides clients in their choice of care establishments. The company has 11,000 collaborators, 426,000 client enterprises, and €6.5 billion in equity. It has a dedicated data science and analytics department led by a Chief Data Officer. The data department is comprised of four main branches, each in charge of Data Science and Analytics, Data Governance, Data Architecture and Cloud, and AI and Data Visualization. Read More
Solution	To address their challenges, Malakoff Humanis turned to Dataiku’s Deep Belief program, which provides consulting services to tackle ambitious AI projects. Through this program, Malakoff Humanis collaborated with Dataiku’s data scientists on two advanced natural language processing (NLP) projects. The first project was an AI-based solution that helps understand the topic of online claims through NLP classification algorithms and automatically dispatch the claim to the appropriate customer service team. The second project was to analyze the content of customer calls (themes and tone) in order to identify areas for improvement of telephone assistance. The main goals of the project were improved management of telephone assistance, shorter calls and fewer re-calls, less pressure on customer support teams, and improved customer satisfaction. The sentiment analysis NLP model built to assess the tone of telephone calls generates predictions for the overall tone, the tone of separate sentences in the conversation, and the sentiment at the beginning and the end of the conversation. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Natural Language Processing (NLP)

Applicable Industries

Healthcare & Hospitals

Services

Data Science Services

Challenge

Malakoff Humanis, the leading non-profit group health insurer in France, was facing growing challenges in keeping up with customer demands and providing quality customer service. The company offers supplementary health, welfare, and pension contracts to companies, employees, self-employed individuals, and single-payer individuals. It covers healthcare reimbursements in addition to the French social security and guides clients in their choice of care establishments. The company has a dedicated data science and analytics department led by a Chief Data Officer. The data department is comprised of four main branches, each in charge of Data Science and Analytics, Data Governance, Data Architecture and Cloud, and AI and Data Visualization. However, the company was struggling to effectively manage customer claims and improve telephone customer assistance.

About Customer

Malakoff Humanis is the leading non-profit group health insurer in France. It offers supplementary health, welfare, and pension contracts to companies, employees, self-employed individuals, and single-payer individuals. As a complementary health insurance, the mutual fund covers healthcare reimbursements in addition to the French social security, and guides clients in their choice of care establishments. The company has 11,000 collaborators, 426,000 client enterprises, and €6.5 billion in equity. It has a dedicated data science and analytics department led by a Chief Data Officer. The data department is comprised of four main branches, each in charge of Data Science and Analytics, Data Governance, Data Architecture and Cloud, and AI and Data Visualization.

Solution

To address their challenges, Malakoff Humanis turned to Dataiku’s Deep Belief program, which provides consulting services to tackle ambitious AI projects. Through this program, Malakoff Humanis collaborated with Dataiku’s data scientists on two advanced natural language processing (NLP) projects. The first project was an AI-based solution that helps understand the topic of online claims through NLP classification algorithms and automatically dispatch the claim to the appropriate customer service team. The second project was to analyze the content of customer calls (themes and tone) in order to identify areas for improvement of telephone assistance. The main goals of the project were improved management of telephone assistance, shorter calls and fewer re-calls, less pressure on customer support teams, and improved customer satisfaction. The sentiment analysis NLP model built to assess the tone of telephone calls generates predictions for the overall tone, the tone of separate sentences in the conversation, and the sentiment at the beginning and the end of the conversation.

Impact #1	The project made it possible to create a processing chain which takes transcriptions of telephone calls as input and analyses and classifies the tone as well as the topic of conversations.
Impact #2	Despite the relatively low number of labeled transcriptions, the information obtained allows to analyze and monitor the overall content and sentiment of calls, and classify them accurately into the main call categories.
Impact #3	Dataiku’s Deep Belief program allowed to identify and operationalize a new advanced NLP use case for the Malakoffff Humanis AI team in a secure and scalable way that empowers users to be autonomous, continue monitoring the models in production, and potentially reuse it for other text classification problems.

Impact #1

The project made it possible to create a processing chain which takes transcriptions of telephone calls as input and analyses and classifies the tone as well as the topic of conversations.

Impact #2

Despite the relatively low number of labeled transcriptions, the information obtained allows to analyze and monitor the overall content and sentiment of calls, and classify them accurately into the main call categories.

Impact #3

Dataiku’s Deep Belief program allowed to identify and operationalize a new advanced NLP use case for the Malakoffff Humanis AI team in a secure and scalable way that empowers users to be autonomous, continue monitoring the models in production, and potentially reuse it for other text classification problems.

Benefit #1	Improved management of telephone assistance
Benefit #2	Shorter calls and fewer re-calls
Benefit #3	Less pressure on customer support teams

Benefit #1

Improved management of telephone assistance

Benefit #2

Shorter calls and fewer re-calls

Benefit #3

Less pressure on customer support teams

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Overview

Malakoff Humanis: Improving Customer Relations With the Power of NLP

Operational Impact

Quantitative Benefit