Dataiku Case Studies Improving Fraud Detection by Evangelizing Data Science

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	Improving Fraud Detection by Evangelizing Data Science Dataiku

Improving Fraud Detection by Evangelizing Data Science

Dataiku

Technology Category	Analytics & Modeling - Machine Learning
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation
Use Cases	Fraud Detection
Services	Data Science Services
Challenge	BGL BNP Paribas, one of the largest banks in Luxembourg, had a machine learning model in place for advanced fraud detection. However, the model remained largely static due to limited visibility and limited data science resources. The business team was keen on updating the model but faced challenges due to lack of access to data projects and the data team. The challenge was to harness a data-driven approach across all parts of the organization. The bank needed a solution that would democratize access to and use of data throughout the company, without compromising data governance standards. Read More
About Customer	BGL BNP Paribas is one of the largest banks in Luxembourg and part of the BNP Paribas Group. It offers an especially wide range of financial products and bancassurance solutions to individuals, professionals, private banking clients, and businesses. In 2017, the international magazine Euromoney named BGL BNP Paribas “Best Bank in Luxembourg” for the second year in a row. The bank was already using a machine learning model for advanced fraud detection, but it was largely static due to limited visibility and data science resources. Read More
Solution	BGL BNP Paribas chose Dataiku Data Science Studio (DSS) to democratize access to and use of data throughout the company. In just eight weeks, BGL BNP Paribas was able to use Dataiku to create a new fraud detection prototype. The project involved data analytics and business users from the fraud department as well as data scientists from BGL BNP Paribas’ data lab and from Dataiku. The collaborative nature of Dataiku and involvement of teams throughout the company allowed for the optimal combination of knowledge to produce an accurate model delivering clear business value. Dataiku’s production features allowed for a smooth transition in BGL BNP Paribas’ production environment, enabling the new fraud prediction project to show results very soon after the start of the project. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Use Cases

Fraud Detection

Services

Data Science Services

Challenge

BGL BNP Paribas, one of the largest banks in Luxembourg, had a machine learning model in place for advanced fraud detection. However, the model remained largely static due to limited visibility and limited data science resources. The business team was keen on updating the model but faced challenges due to lack of access to data projects and the data team. The challenge was to harness a data-driven approach across all parts of the organization. The bank needed a solution that would democratize access to and use of data throughout the company, without compromising data governance standards.

About Customer

BGL BNP Paribas is one of the largest banks in Luxembourg and part of the BNP Paribas Group. It offers an especially wide range of financial products and bancassurance solutions to individuals, professionals, private banking clients, and businesses. In 2017, the international magazine Euromoney named BGL BNP Paribas “Best Bank in Luxembourg” for the second year in a row. The bank was already using a machine learning model for advanced fraud detection, but it was largely static due to limited visibility and data science resources.

Solution

BGL BNP Paribas chose Dataiku Data Science Studio (DSS) to democratize access to and use of data throughout the company. In just eight weeks, BGL BNP Paribas was able to use Dataiku to create a new fraud detection prototype. The project involved data analytics and business users from the fraud department as well as data scientists from BGL BNP Paribas’ data lab and from Dataiku. The collaborative nature of Dataiku and involvement of teams throughout the company allowed for the optimal combination of knowledge to produce an accurate model delivering clear business value. Dataiku’s production features allowed for a smooth transition in BGL BNP Paribas’ production environment, enabling the new fraud prediction project to show results very soon after the start of the project.

Impact #1	The new fraud detection prototype was created in just eight weeks.
Impact #2	The collaborative nature of Dataiku and involvement of teams throughout the company allowed for the optimal combination of knowledge to produce an accurate model delivering clear business value.
Impact #3	Dataiku’s production features allowed for a smooth transition in BGL BNP Paribas’ production environment, enabling the new fraud prediction project to show results very soon after the start of the project.

Impact #1

The new fraud detection prototype was created in just eight weeks.

Impact #2

The collaborative nature of Dataiku and involvement of teams throughout the company allowed for the optimal combination of knowledge to produce an accurate model delivering clear business value.

Impact #3

Dataiku’s production features allowed for a smooth transition in BGL BNP Paribas’ production environment, enabling the new fraud prediction project to show results very soon after the start of the project.

Benefit #1	Created a new fraud detection prototype in just eight weeks.
Benefit #2	Enabled the new fraud prediction project to show results very soon after the start of the project.
Benefit #3	BGL BNP Paribas has already begun three additional data projects following the first fraud detection prototype and plans to continue to release new data products regularly to stay at the cutting-edge of the financial industry.

Benefit #1

Created a new fraud detection prototype in just eight weeks.

Benefit #2

Enabled the new fraud prediction project to show results very soon after the start of the project.

Benefit #3

BGL BNP Paribas has already begun three additional data projects following the first fraud detection prototype and plans to continue to release new data products regularly to stay at the cutting-edge of the financial industry.

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Overview

Improving Fraud Detection by Evangelizing Data Science

Operational Impact

Quantitative Benefit