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Escp’s Msc in Big Data and Business Analytics Organised Its Annual Hackathon for the Third Year Running!

For the third edition of the MSc in Big Data and Business Analytics’ annual hackathon, students were challenged to find disruptive solutions based on machine learning and artificial intelligence, using novel marketing, operational and analytical approaches, as well as financial analytics.

They worked on three projects in the field of Marketing 4.0, Blockchain in Fintech, and Sustainable and renewable Energy for this year’s partner companies: Criteo, Equisafe and EuroWatt.

An Online Hackathon From 16 to 20 March 2020

Given the current global context with the Covid-19, this year’s hackathon took place online, highlighting the great agility and adaptability of students when faced with exceptionally challenging situations.

Over the course of 5 days, 20 teams worked tirelessly, leveraging their business and technical skills to real world issues to find solutions to create social and business value for the partner companies.

Their knowledge of analytics and cognitive computing, their commitment and passion to these issues enabled them to support organisations through major changes, proving that they are, undoubtedly, business leaders.

Equisafe Project

Fintech is disrupting the financial industry, giving a major advantage going forward to blockchain development companies in this sector.

The diffusion and scalability of the emerging Fintech will depend mostly on users’ adaptation and value propositions.

The economic models will soon become obsolete with the lengthy and costly money, asset and information transfers through multilayer schemes with several intermediaries. Fintech companies, such as Equisafe, are constantly growing and always looking for new challenges to implement the platform's potential.

Bilal El Alamy, CEO, founder, ESCP alumni and Hackathon winner; for this edition proposed three different challenges for ESCP students with the scope of possible development for new features of the product:

  • Quantitative Finance: Portfolio Optimization for tokenized private stocks.
  • Corporate Finance: Create a model for the Internal Rate or Return.
  • Graph Theory: Create a granular graph of corporate to track shareholder participation.

 

Criteo Project

Based on intricate observation and analysis of the paradoxes in view of the digital technology boom, Marketing 4.0 emerges in the recent past.

As Artificial Intelligence, Machine Learning, Big Data, IoT and mobile devices become more ingrained in consumers’ lifestyles – deeply influencing their attitudes and behaviors – consumers will increasingly look for the perfect mix of tech and traditional merchandise consumption that makes their lives easier.

Marketers need to brace up for this transition and adaptation period in the run up to a fast-developing digital economy.

Eurowatt Project

Energy worldwide needs to grow with the emerging technologies in Artificial Intelligence, IoT, Machine Learning, and Big Data Analytics.

Fast technology advancement has enabled many alternative and renewable sources of energy to emerge in the recent past.

All renewable energy sources like solar, wind, geothermal, hydropower, wave and tidal power are forms of sustainable energy. They have low environmental impact, widely available and are naturally replenished. Modern energy companies are keen to make renewable and sustainable energy more accessible to the world.

At the end of the week, each team presented its results in the form of prototypes, technical solutions or new uses to develop the practices of the various sectors represented, in front of a jury* made up of ESCP professors, technology partners and partner companies.

*Jury Members:

Special Thanks to All the Jury Members And:

  • Sabrina Azor
  • Huihui Chi
  • Sha Zhu

Winning Teams

1st Prize

  • Criteo: Maximilian Baum, Valentin Fischer, Salma Mezyaoui, Maxime Pracisnore
  • Eurowatt: Philipp Magnus Aring, Johan Larsson Garnich, Ziae Mustafa, Andrea Sabia
  • Equisafe: Yuxi Guan, Ding-Yao Jheng, Lorenzo Tozzi, Meng Zhang

2nd Prize

  • Criteo: Charles Biwer, Margot Crepsin, Gabriel Darmon, Mathilde Gomez, Luna Joseph
  • Eurowatt: Tanasit Mahakittikun, Nourhan Nassar, Jonathan Scheepers, Javiera Vines Alvarez

3rd Prize

  • Criteo: Antoine Guerrini, Yousseff Jactthar Noguera, Kim Vogel, Qinjiong Zeng
  • Eurowatt: Amaury Charbon, Inès Des Rieux de la Villoubert, Bastien Hellouin de Cenival, Olympia Hilverda, Alexandre Lachkar

Our analysis enables Criteo to focus on the right clients with the right measures as well as lower their overall risk exposure by reducing the likelihood of customer churn.

Valentin Fischer – 1st prize

After taking one day to explore all the dataset that we had been given by Criteo, we saw an opportunity in developing a client profile for specific products. We believed this would have a significant value proposition for Criteo as this is in their business model to expand the use of new products to more adequate customers

Luna Joseph – 2nd prize

Evolving in a growing but highly competitive market, where most of the companies are cannibalizing each other, we decided to propose a niche strategy for Criteo. In fact, in this ever-changing market, we truly believe that creating deep roots in certain unexploded segments is a promising investment for the future business of the company.

Antoine Guerrini  – 3rd prize

We leverage operations data to support and enhance maintenance activities. We generate insights regarding the nature and sequence of machine failures and couple these insights with a deep learning model.

Andrea Sabia – 1st prize

We investigate the social and political aspects of new wind farm development. By using natural language processing (NLP), we analyze the tweet content, and the outcome of the legislative election to evaluate the public opinion of renewable and sustainable energy.

Jonathan Scheepers – 2nd prize

We created a model for electricity producers, forecasting peak electricity days one month in advance by using electricity demand and nuclear production data. Thanks to this, Eurowatt will have more leverage to postpone maintenance and ensure production on those days, thus avoiding penalties and increase their revenue.

Olympia Hilverda – 3rd prize

Following Equisafe's business model, we created a tool for investors and companies using price and portfolio forecasting models. Our application helps customers track historical price, forecast future price and plot the most efficient portfolio. The tool and models used can create value for both the customer and, with more experimentation, development, for Equisafe.

Lorenzo Tozzi – 1st prize

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