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31st October 2019 - Y-Parc, Yverdon-les-Bains

Leading Swiss conference on artificial
intelligence for fraud prevention

Fraud analytics

Conference

About

Please join us for a day where fraud specialists, data scientists, engineers and academics meet to share and exchange on fraud fighting and work on making this world a safer place.

If you are interested in fighting fraud, this is for you the place to be on Thursday, 31st Oct 2019.

Please save the date in your agenda. A detailed program will follow. Free entrance.

The event is hosted by:

HEIG-VD, the School of Engineering and Management Vaud, is the largest school of the University of Applied Sciences and Arts of Western Switzerland.

Award-winning Swiss FinTech, developing the smarter artificial-intelligence solution made for banks to proactively prevent fraud.

Who should attend

The conference attracts participants from the fields of fraud analytics and data science. The following graph should give you an idea about the technical complexity of the topics that will be covered.

Program

Discover the program and our outstanding speakers!

12h45

Opening & welcome

13h15
13h15

Welcoming words

Joël Winteregg, CEO at NetGuardians
Vincent Peiris, Head of TIC at HEIG-VD
13h30
13h30

Journey to fighting fraud: INTERPOL’s perspective

Fraud is always evolving. In the face of increasing challenges and dealing with smart criminals, we need to continuously grow our team and be innovative in fighting it. In this talk, we will bring you through INTERPOL’s journey to combat fraud, specifically, the roles played by the Financial Crime Unit in connecting not just the respective Police agencies of its Member Countries, but also all related stakeholders.

Keynote speaker: Jung Kee You, Executive staff – Criminal Intelligence Officer at the Financial Crime Unit of INTERPOL
14h10
14h10

Fraud, a case of digital transformation

The issue of fraud is a use case that is particularly interesting from a machine learning standpoint. Modelizing this problem is rather complex from a technical perspective, as it is considered a rare occurrence; therefore, creating a robust model is quite difficult. Furthermore, it would necessitate close cooperation with the business in order to build a thorough relationship with them and to understand their needs. Working on this subject with them enables us to undergo a true cycle of digital transformation. The following presentation will explore this perspective.

Assia Garbinato, Expert in data transformation, Consultant
Kim Leng Chhun, Business Intelligence Designer & Data Scientist at La Vaudoise
14h55
14h55

Break time

15h10
15h10

Machine learning against fraud: lessons learned from a real case

Billions of dollars of loss are caused every year due to fraudulent credit card transactions. The design of efficient fraud detection algorithms is key for reducing these losses, and more and more algorithms rely on advanced machine learning techniques to assist fraud investigators. The design of fraud detection algorithms is however particularly challenging due to non-stationary distribution of the data, highly imbalanced classes distributions and continuous streams of transactions.  At the same time public data are scarcely available for confidentiality issues, leaving unanswered many questions about which is the best strategy to deal with them.

In this talk we will discuss a number of lessons learned during our long-standing collaboration with the R&D team of Worldline. In particular we will focus on best practices for the assessment of credit card fraud detection models and we will discuss the impact of data unbalancedness and non-stationarity on the resulting accuracy. More recent directions of research, including big data infrastructure, active and transfer learning, will be sketched as well.

 Gianluca Bontempi, Prof. at ULB & co-Head at MLG
15h50
15h50

Unusual bank transactions detector

How to detect unusual bank transactions? Based on a case study, this talk presents the process of building an unusual bank transactions detector using AI that leverages data acquisition and cleansing, features & algorithm selection and industrialization.

 Stephan Singh, Head of data analytics for regulatory & strategic projects at Pictet
16h40
16h40

Break time

16h55
16h55

Interpretable machine learning for credit card fraud detection

Credit card issuers put great effort into preventing fraud in order to minimise their own losses as well as the inconvenience caused to the affected cardholders. At Viseca Card Services we have been exploring various approaches regarding the integration of machine learning into our fraud prevention processes with a high degree of success. In this presentation we describe the use of machine learning to score Card-Not-Present transactions and new approaches to interpret the individual scores.

 Viton Vitanis, Head of Risk Analytics at Viseca Card Services
17h35
17h35

Data analytics on cyber crimes complaints registered at C3N, of Gendarmerie Nationale in France

Cyber risk cannot be avoided, whatever the implemented IT security measures. For improving society resilience to cyber-attacks, there is a strong need for understanding theses risks. A way towards this goal is the search for reliable data and their statistical analysis. It is what is proposed here, thanks to the partnership between the Center of Research in Econo-finance and Actuaria science on Risk (CREAR-ESSEC Business School) and the SCRC (service Central du Renseignement Criminel) of PJGN (Pôle Judiciaire de la Gendarmerie Nationale). We proceed to the statistical data exploration and analysis of the cyber crimes complaints by victims (individuals and companies) registered at the Gendarmerie National’s Cyber Crime Unit (C3N). Using an algorithmic method developed by Debbabi et al. (2017)2 for extremes modeling, we show the existence of heavy-tailed distributions, one of the main characteristics of cyber risk.

 Michel Dacorogna, Partner at Prime Re Solutions, and lecturer at ETHZ

18h15
18h15

Round table discussion

Fraudsters versus Data scientists, who is winning?

All speakers & Yves Genier, Business Journalist at La Liberté
19h00
19h00

Aperitif

20h30
20h30

Closure of the conference

Speakers

Keynote speaker
Jung Kee You

Jung Kee You

Executive staff - Criminal Intelligence Officer at the Financial Crime Unit of INTERPOL

Jung Kee You is currently seconded to the Organised and Emerging Crime Directorate, Financial Crime Unit of INTERPOL. He joined the Korean National Police in 2003 and graduated with a Master’s degree in Law from the Kyung Hee University Law School in 2013.

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Assia Garbinato

Assia Garbinato

Expert in Data Transformation, Consultant

After graduating as an engineer in Algeria, Assia Garbinato joined the EPFL’s School of Life Sciences in 1995 to do her doctorate in Computer Science. After her thesis, she began her professional career in a startup and later joined the Kudelski Group as a Software Engineer.

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Kim Leng Chhun

Kim Leng Chhun

Business Intelligence Designer & Data Scientist at La Vaudoise

Kim Leng Chhun is a Business Intelligence Designer & Data Scientist. She received a Bachelor’s degree in Software Engineer from School of Management and Engineering Vaud (HEIG-VD) in 2014.

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Gianluca Bontempi

Gianluca Bontempi

Professor at the ULB Department of Computer Science and co-Head of Machine Learning Group of ULB

Gianluca Bontempi is Full Professor in the Computer Science Department at the Université Libre de Bruxelles (ULB), Brussels, Belgium, founder and co-head of the ULB Machine Learning Group (mlg.ulb.ac.be).

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Stephan Singh

Stephan Singh

Head of data analytics for regulatory & strategic projects at Pictet

Stephan Singh is the head of a unit working across the entire data value chain, providing business intelligence and data science as well as data quality improvement for the Private Client Data field in one of the largest Swiss private bank.

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Viton Vitanis

Viton Vitanis

Head of Risk Analytics at Viseca Card Services

Viton Vitanis is the Head of Risk Analytics at Viseca Card Services. Focus of his team is the development of methods and tools that enable Risk Operations better assess credit risk, prevent fraud and reduce chargebacks.

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Michel Dacorogna

Michel Dacorogna

Partner at Prime Re Solutions, and lecturer at ETHZ

Michel Dacorogna is partner at Prime Re Solutions, a company advising financial institutions on actuarial and economic matters. He is also Director of Risk Management at the Geneva Association and head of DEAR-Consulting.

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Moderator

Yves Genier

Yves Genier

Business journalist at La Liberté

Yves is a seasoned business reporter in Western Switzerland, notably in the Geneva area. Head of the business section of the daily "La Liberté", he was previously business writer at "L‘Hebdo" newsmagazine, "Le Temps" newspapaper and "L’Agefi" business daily.

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Registration

Please fill out the form to register. RSVP early as places are limited and will be available on a first-come, first-served basis.

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