Michael de Toldi – BNP Paribas Cardif

October 2015

2

What governance for Data Analytics?

3

What do we want as clients?

Personalised offers

Adapted services

Quick answers

Great prices

Contextual offers

Expected contacts

Value for loyalty

Privacy

4

Some people think that we should…

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But this, is the reality!

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And it is better to know more than one model…

All models are wrong

but some are useful“

“George E. P. Box

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“Data Science” vs “Data Mining” culture

Statistics

SQL, Flat files, Web scrapping, web

logs, Cookies, Text, Images, .json,

.xml, …

High abstraction programming

Open Source soft & libraries

MOOCs

Blogs, Tutorials, Forums,

KAGGLE competitions

Statistics,

Computer science : memory

optimization, parallelization

Data Format

Tools

Training

Skills

SQL

Flat files

Low level programming

frameworks

Proprietary software

Books

Diploma

1990 2015Data Mining Data Science

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Toolbox

Objective

Strategy

Generalizing

Validation

Computation

Experience

The Data Modelling Culture The Machine Learning Culture

OLS

GLMs

GAMs

Cox

X Y

Regularized GLMs

Random Forests

Gradient Boosting

Neural Nets

Blending/Stacking

yX

Understand model nature Look for best accuracy

Design manually model structure Hyperparameters to control

model complexity

Combat overfitting with expertise Automated strategies to combat

overfitting

« Goodness of fit » statistical tests Measured by predictive accuracy

Model simplicity Parallelizing strategies

• Provide more insight about how nature is associating

the response variables to the input variables.

• Works well for small datasets

• But, if the model is a poor emulation of nature, the

conclusions based on this insight may be wrong !

• Sometimes considered as black box (unfairly

for some techniques)

• They often produce higher predictive power

with less modelling efforts because of

automated strategies

“Machine Learning” vs “Data Modelling” culture

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1st conviction for Data Analytics

Data Science should be

understood and internalised“

“Michaël de Toldi

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What about data in insurance companies?

Actuarial Data

Marketing Data

Commercial Data

Finance Data

Client Management

Data

Fraud Data

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What about data in insurance companies?

Actuarial

Marketing

Finance

CommercialClient

Management

Fraud

INT / EXT

DATA

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2nd conviction for Data Analytics

Internal & external Data

should be freed, shared,

controlled and secured

“

“Michaël de Toldi

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Data Science & IT are deeply linked

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Data Science innovation relies on Open Source

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3rd conviction for Data Analytics

IT framework should be

Data Science friendly“

“Michaël de Toldi

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Data Analytics governance in a nutshell…

Data Science should be understood and internalised

Internal & external Data should be freed, shared, controlled and secured

IT framework should be Data Science friendly

Don’t wait too much to

understand what is at stake!

THANK YOU!BNP PARIBAS CARDIF8, rue du Port

92 728 Nanterre Cedex

Tel.: +33 (0)1 41 42 83 00

bnpparibascardif.com