Company Overview

1

Using data to drive business performances

10+ yearsInnovative SME

Research CenterMIUR

ISO 9001:2015Design and development of predictive

models

Experience in Data Science & AI

100+ projects 30+ clients, mostly recurrent

3

Company Profile

DATA DIGITALISATION ALLOWS COMPANIES TO GAIN A LOT OF VALUABLE INFORMATION.

HARVESTING THE RIGHT INFORMATION FROM DATA IS ONE OF THE BEST ARROW TO ACHIEVE BUSINESS GOALS

A SPECIFIC KNOW-HOW IN DATA MINING, PREDICTIVE MODELING AND

MACHINE LEARNING IS NEEDED

Pangea Formazione offers cutting-edge data science solutions supporting many business processes: from marketing to customer care, from production to inventory management and logistics

DATA

IDEAS

ACTIONS

Bayes approach allows, by observing an effect, to identify the reasons it would probably cause it. It allows to deal with complex problems, where many variables are influencing each others and with high level of uncertainty, being able to properly weight all key factors. Advantages are:§ evaluate and embed experts’ knowledge in the model;

§ calculate the probability of each factor to cause a given event, disclosing the hidden patterns in the data;

§ properly quantify the possible occurrence of each event in terms of probability, given the actual information.

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Data Science: the Bayesian Approach value

extrapolation

BAYESIAN INFERENCE

MODELDATA

FORECAST

HISTORICAL

DATAEXPERTISE

EXTERNAL

INFLUENCE

Since 2009, the Bayesian approach is the solution chosen by NASA for risk assessment procedures.

Nowadays it is widely adopted by the new business leaders.

Pangea Formazione is expert in Data Science in order to support a proper, scientific Decision Making

The Bayesian approach is the ideal solution to quantify uncertainties, a

key aspect in Decision Making

5

Expertise

KNOW-HOW

LEADERSHIP&

VALUE

A STRONG

CONNECTION

WITH RESEARCH

Since 2009 Pangea Formazione supports Italian companies bringing innovation and improving their internal processes.

Pangea Formazione is the Data Science company leader in Italy in applying Bayesian approach to business problems.We develop software and web applications based on advanced statistical and mathematical models that allows to produce detailed reports and perform predictive analysis.

Pangea Formazione has key partnerships with Research Institutes and Universities.About 80% of Pangea Formazione’s team has a Ph.D. in quantitative subjects. Therefore we are expert in applying the most advanced scientific research techniques.

OUR expertise

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Data collection:Structured and unstructuredDB creation(SQL,noSQL)Web Scraping

Data analysis:CleaningWranglingIntegrationStatistical reportVariable selection

Algorithms and Methods:ClassificationRegressionClusteringDeep/Machine LearningImage RecognitionText Mining

Predictive Models:ForecastingOptimizationSimulation

Result:DashboardAPISoftware library

01

02

03

05Goal: give the client results obtained exploiting ML and AI

04

We develop ad hoc solutions on specific needs, we have no off the shelf products

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Our services

§ Harvesting, cleaning, arranging and aggregating data

§ Collecting and integrating Open data, social media data

IMPROVE

UNDERSTAND

Data VisualisationReportingMonitoring

Anomaly detectionMapping opportunities

Scenario analysis

Best StrategiesQuantifying

opportunitiesCost-Benefit analysis

§ Clustering and Profiling§ Machine Learning and

Predictive Models§ Deep Learning

§ Goal maximization § Action plans§ Sensitivity analysis

DATA

IDEAS

ACTIONS

DISCOVER

8

Our Activities

Software Development

Data Science ad hoc Solution

SaaS

(Big Data)Consulting

Mentorship

Group leading

Software Development

Advanced Training

Quantitative decision making

Data science & Machine Learning

R&D

Research & Development

Publishing

National and European Grants

Internal R&D

§ We develop Business Intelligence solutions for data organisation: collecting, accessing, cleaning, arranging and pre-processing in house data and open data.

§ We perform customized Data Analysis, Predictive Models, Real Time Analysis, Geolocalization Analysis

§ We support our customers with software tools that allows to easily explore results and future scenarios.

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Our services: outcomes software-by-design

Our solutions are developed in house and can be integrated in any IT environment by means of open source platform and codes.

Data mining

Algorithms development

Results visualization

10

Success Case

Key activities of Fraud Management departments are to prevent frauds as much as possible, finding the best trade-off between fraud risk and revenue losses.

Ø We developed a Bayesian based AI algorithm capable to learn correlations between variables and classify events. It enables to:

a) Identify and build categories and clusters, segment and label data, find hidden patterns;

b) Assign the likelihood for a given profile to have specific characteristics;

c) Define in which cases it is convenient to try corrective actions.

Ø The model is used to calculate the probability of a fraud starting from several available information: i.e. personal data, contract type and service, payment methods, credit check scoring.

OUR SOLUTION

§ The developed SW provides a ranking of customers sorted by fraud probability. It helps the investigation reducing costs and increasing efficacy.

§ In TIM, our tool led to a sensitive reduction in the back office workload to prevent frauds.

§ In Poste Mobile, it enabled a reduction of several percent for the «products» frauds and led to an increase in consolidated sales in the last 24 months.

RESULTS AND CREATED VALUE

FRAUD MANAGEMENT

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Success Case

Specific assets are subject to breakdowns and malfunctions. Maintenance contracts usually depend on their number and not by actual damages. Without a rational criterion, not optimal choices are possible.

Ø We developed a tool able to predict the remaining time before damages and malfunctions arise, by detecting and measuring specific parameters

Ø The probability of failure can be calculated from technical characteristics and breakdowns history of similar elements using a Bayesian network.

Ø The application is twofold:a) It is possible to identify assets with a low risk of failure

and decide to remove them from maintenance contracts, in order to save on maintenance costs.

b) It is possible to keep high levels of operational reliability by an effective replacement planning.

OUR SOLUTION

§ In TIM, the tool developed by Pangea Formazionehas as output the ranking of the assets probability of failure, allowing to considerably reduce the number of assets under maintenance

§ For MBDA, it has been developed a predictive tool, able to estimate failure probability of each component in order to schedule dynamically the stocks and guarantee a specific level of reliability.

§ We have demonstrated the advantages of using this tool for optimizing the maintenance of the DHL's hub sorter located in Bologna. The solution is able to both increase effective operating time and to greatly reduce the whole maintenance cost.

BUSINESS IMPACT

PREDICTIVE MAINTENANCE

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Success Case

Advanced profiling of the Customer Base represents an opportunity to improve product portfolio, to develop targeted marketing strategies and to enlarge the CB while increasing its loyalty.

Ø Build a single DB capable to serve as basis for on-demand reporting, fast query execution by means of integration of different internal databases from company DWs, including data from other societies of Gruppo PosteItaliane and Open Data

Ø Develop an Bayesian Network able to detect the Next Best Product to propose. Perform CRM analysis (retention, survival, churn, journey) thanks to single customer advanced profiling

Ø Implement a new effective marketing strategy by combining the reworked DB with an ad hoc artificial intelligence algorithm allowing to: rapid simulation of different scenarios, optimal target identification, potential markets sizing, client profiling and behaviour forecasting

OUR SOLUTION

§ Increase of up-selling results§ Increase of cross-selling among

Postevita brands and among Postevita& PosteItaliane products

§ Enlargement of the Customer Base

§ Greater redemption of sales campaigns

BUSINESS IMPACT

MARKETING

Paolo AgnoliPARTNER

13

Cinzia Di PortoPh.D PhysicsSTRATEGY

Lorenzo RiggioPh.D. Physics

Nicola FarinaPh.D. Physics

DIRECTOR

Filippo OrioPh.D Physics

INNOVATION

Fabio PriuliPh.D MathTRAINING

Andrea RomualdiMs. Physics

Francesco PiccoloPARTNER

AU

Martina TuccinardiMs. Math

Desirée GentiliniPh.D Engineering

SALES

Sara BorroniPh.D Physics

PROJECT DEV.

Giorgio SalernoPh.D. Physics

Maria Luisa GrecoMs Economics

ADMINISTRATION

Giacomo ScettriMs. Physics

Tiziano AbdelsahlinPh.D Physics

Daria MorozovaMs. Math

Giovanni BallarinMs. Math

• Combined ~100 years in Data Analysis

• Work together from a long time• Low turnover

Stefano Di VitaPh.D Physics

Francesco MicheliPh.D Physics

Our Team

CLIENTS & credentials

14

CORPORATE

PA & Consulting

SME

University and Research Center

15

Credentials

Main Objectives Activities ResultsCompany

FRA

UD

MA

NA

GEM

ENT

§ Fraudster advanced profiling§ Alarm calibration

§ Investigation speed-up§ Back-office workload

lightening

§ Fraudster profiling§ Sensitivity analysis § Fraud frequency decreaseFraud Prevention

Support for Anti-Fraud Investigations

FAIL

UR

E PR

EDIC

TIO

N

§ Monthly failure rate estimation § Decrease maintenance cost§ Optimal budget planningPredictive Maintenance

§ Failure probability updates§ Operation scenario analysis

§ Sufficiency probability computation

§ Stock size optimizationInventory Management

CA

PAC

ITY

PLA

NN

ING

§ Number of request estimation§ Seasonal trend and year on

year analysis

§ Stock size optimization§ Asset efficiency increase

Planning Optimization of Cloud Computing

Resources

MARINA MILITARE

§ Development of an analytical model for the estimation of energy price

§ Buy-sell strategy optimization§ Sensitive gain in the daily

operationsEnergy market price

prediction

§ Risks and controls quantification

§ Links identification and weigh§ Risk impact estimation§ Control system optimization

Quantitative Enterprise Risk Management

16

AU

DIT

§ KPI definition and maximization

§ Development of an algorithm for optimal asset allocation

§ Quality improvement and cost saving

§ Reduction of #FTEQuality Optimization for Internal Audit Activities

RIS

K

MA

NA

G’N

TTR

AD

ING

§ Development of a bayesianalgorithm for cellphone traffic estimation

§ Selling risk reduction§ Margin increase

Wholesale negotiation support for roaming

services

CU

STM

’R

CA

RE § High risk failure identification

§ New failure probability estimation

§ Large decrease of frequency of new failures

§ Operational cost savingTechnical assistance

operations optimization

Credentials

Main Objectives Activities ResultsCompany

17

MA

RK

ET

ING

§ DB enrichment with open data

§ Development of a predictive model for the Next Best Product

§ Advanced Dashboard§ Strategic marketing tailored

on company targets.

New marketing approach through

quantitative modelling

INN

OV

AT

ION

&B

US

INE

SS

DE

V.M

EN

T § Touristic interest estimation (via Google Trends)

§ Gap Analysis interest/presences

§ Touristic potential estimation in Italy

§ Trends and Seasonality§ Dashboard

Tourism flows analysis and local potential

estimation

§ Key factors evaluation§ Bayesian Network

construction and feeding

§ RoamingZero impact estimation

§ Fair use analysisRoaming Evolution

Analysis

§ Development of an AI algorithm for the profiling of visiting SIMs

§ Enabling effective marketing with specific programs of customer experience

Profiling Visitors

§ Scraping and selection of online news

§ Anomaly detection using Twitter

§ Reduced human workload § Trending topics identification

with a 10 min maximum delayBreaking news identificationD

AT

A

MIN

ING

Credentials

Main Objectives Activities ResultsCompany