Compete with leading data scientists and machine learning experts in NLB Group Hackathon 2021 - Data Science and receive the chance to join one of the best financial data science companies in the region or even win 10.000 €.
This is your chance to work on a real life data science problem, improve your skill set, learn from expert data science professionals, participate in round-table discussions with renowned experts and hack your way to the top of the hackathon leader board!
So, get your thinking hat on and join us. Start your data science hackathon journey today!
This is your chance to:
Topic discussed: The ethical issues of AI go beyond the mere accumulation of data and direction of attention – legal aspects.
Find out more on round tables here.
Registration for Hackhaton is closed. Thank you to everyone who submitted an application. You will be notified of the next steps.
The competition part of Hackhaton is going to take place from June 8th, 2021 at 12.00, until June 24th, 2021 at 23.59 inclusive.
You may find a more detailed timeline of events here.
We welcome game changers, entrepreneurs, developers, basement hackers, university students, enthusiasts, creative people and “geeks” in FinTech, InsureTech, RegTech, AI, UX designers, coders, idea generators, marketeers, data scientists, mad scientists ... You get the idea. So, YOU are kindly welcome as well.
Hackathon is open to individuals who meet the following conditions:
It is open only for individuals, participation in teams is not possible.
How can we speed-up lending decisions for new bank`s customers with Artificial Intelligence?
The financial industry is highly regulated and loan issuers are required by law to make fair decisions and explain their credit models to provide reasons whenever they decide to decline loan application. At NLB Group, we are issuing thousands of loans every month and our underwriting model has to provide declination reasons when the model rejects one’s loan application. The NLB Group wants to improve its loan origination process for new clients by automating eligibility validation based on customer detail provided while filling online application form.
Complementary solutions and technologies that could shape new types of services based on the interpretation and processing of large amounts of collected data, machine learning, and artificial intelligence and to be integrated in the complex solution of automating eligibility validation based on customer detail provided.
Source code in Phyton or R programming language and presentation of the solution with additional improvement of your predictive model.