DataRobot Case Studies MAPFRE Accelerates Time to Business Value by 20% with AI

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	MAPFRE Accelerates Time to Business Value by 20% with AI DataRobot

MAPFRE Accelerates Time to Business Value by 20% with AI

DataRobot

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Real Time Analytics Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Demand Planning & Forecasting Fraud Detection Predictive Maintenance
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	MAPFRE, a Spanish insurance company, operates in over 100 countries, generating €27.3 billion annually. The company's analytics team is responsible for providing advanced analytics to help make decisions on pricing, sales, retention, underwriting, and more. However, given the demand for data insights, the team found it challenging to keep pace with the many incoming requests and deliver value quickly. The team needed to expedite its time to market in tackling new business challenges. Read More
About Customer	MAPFRE is the largest Spanish-owned insurer in the world, the largest multinational insurance company in Latin America, and one of the 15 largest European groups in terms of premium volume. The company operates in more than 100 countries across five continents, generating €27.3 billion annually. More than 34,000 employees of 80 nationalities serve 26 million people around the world. The company's business lines rely on advanced analytics to help make decisions on pricing, sales, retention, underwriting, and more. Read More
Solution	To address this challenge, MAPFRE ESPAÑA chose the DataRobot AI Platform to automate analytics and expand productivity in meeting business needs. The company integrated DataRobot APIs with Amazon Web Services, Microsoft Azure, and Amazon SageMaker, and linked to the company’s data lake using an Athena driver. Models were then deployed to Tableau and Microsoft Power BI for easy use by line-of-business employees. The DataRobot platform eliminated the need to hand-code models, expediting the time to explore and find promising new use cases. MLOps simplified deployment and offered a single spot to monitor models in production. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Real Time Analytics

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Demand Planning & Forecasting

Fraud Detection

Predictive Maintenance

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

MAPFRE, a Spanish insurance company, operates in over 100 countries, generating €27.3 billion annually. The company's analytics team is responsible for providing advanced analytics to help make decisions on pricing, sales, retention, underwriting, and more. However, given the demand for data insights, the team found it challenging to keep pace with the many incoming requests and deliver value quickly. The team needed to expedite its time to market in tackling new business challenges.

About Customer

MAPFRE is the largest Spanish-owned insurer in the world, the largest multinational insurance company in Latin America, and one of the 15 largest European groups in terms of premium volume. The company operates in more than 100 countries across five continents, generating €27.3 billion annually. More than 34,000 employees of 80 nationalities serve 26 million people around the world. The company's business lines rely on advanced analytics to help make decisions on pricing, sales, retention, underwriting, and more.

Solution

To address this challenge, MAPFRE ESPAÑA chose the DataRobot AI Platform to automate analytics and expand productivity in meeting business needs. The company integrated DataRobot APIs with Amazon Web Services, Microsoft Azure, and Amazon SageMaker, and linked to the company’s data lake using an Athena driver. Models were then deployed to Tableau and Microsoft Power BI for easy use by line-of-business employees. The DataRobot platform eliminated the need to hand-code models, expediting the time to explore and find promising new use cases. MLOps simplified deployment and offered a single spot to monitor models in production.

Impact #1	The DataRobot platform expedites experimentation and boosts organizations’ ability to find viable use cases by 20%.
Impact #2	The platform powers the price quoting engine for new policies, producing 20 models to help determine personalized premiums for each customer.
Impact #3	For a cross-selling model, DataRobot cuts the time to retrain models – a frequent requirement given changing economic conditions, new data, and data drift.

Impact #1

The DataRobot platform expedites experimentation and boosts organizations’ ability to find viable use cases by 20%.

Impact #2

The platform powers the price quoting engine for new policies, producing 20 models to help determine personalized premiums for each customer.

Impact #3

For a cross-selling model, DataRobot cuts the time to retrain models – a frequent requirement given changing economic conditions, new data, and data drift.

Benefit #1	20% increase in the ability to find viable use cases.
Benefit #2	20 models produced to help determine personalized premiums for each customer.
Benefit #3	Reduced time to retrain models for cross-selling.

Benefit #1

20% increase in the ability to find viable use cases.

Benefit #2

20 models produced to help determine personalized premiums for each customer.

Benefit #3

Reduced time to retrain models for cross-selling.

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Overview

MAPFRE Accelerates Time to Business Value by 20% with AI

Operational Impact

Quantitative Benefit