DATATHON Spring 2025
Key Facts of past Datathons
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100 + Participants |
7 Challenges |
1000 € Prize money |
What happened at the STADS Datathon?
Participants anticipated two days of intense teamwork focused on data science, data visualization, or programming challenges, along with plenty of fun.
The benefits included:
🚀 €1,000 for the winning team
🚀 Exciting prizes
🚀 Food + drinks included
🚀 Get-together with many companies
An insight into past challenges
Ernst & Young
In this challenge, the goal is to identify duplicate payments for the same invoice within a large dataset. You can choose from various approaches to solve this problem. We are excited to see what ideas you come up with.
PHOENIX group
msg systems
A price shock is a sudden surge in material prices, which can lead to rising production costs and even to an uneconomical production. In order to be able to predict these shocks, a model was trained using key factors that have caused sudden increases in prices in the past. The model can predict future prices and identify possible shocks based on currently occurring key factors. To provide these current factors to the model as features, they must be extracted from current news articles.
RSM Ebner Stolz
One of the main tasks of auditors, for example, is to assess the valuation of a balance sheet item at the end of the fiscal year. The amount of the balance sheet items to be valued depends on the business transactions on the underlying accounts of the company. They are recorded in the form of entries. Over the course of the fiscal year, for example, assets such as receivables are recorded in an account and derecognized when they are settled. In many cases, there is a so-called sub-ledger that can provide information about the composition of an account, but this does not apply to all accounts. In the midst of the greatest stress, the audit manager needs this information for an account, but the accounting department is already completely overwhelmed with other issues. Can you use your analytical skills and algorithmic thinking to crack this numerical puzzle?
Ebner Stolz
BearingPoint
The assessment, processing, and settlement of claims are core business activities and cost drivers for insurance companies. Today, assessments are primarily conducted based on image data and on-site by experts. This process is error-prone, time-consuming, and highly manual. A faster, automated, and more accurate assessment of damage amounts represents a significant improvement for companies and employees. You are to support the AI-based estimation of damage amounts with the additional use of computer vision methods! You are free to choose the methods, approaches, and models you apply. A dataset containing image material, label information, and other features related to water damage will be provided to you.
STADS
Due to constant growth in recent years, McCar unfortunately no longer keeps up with the pricing. Everyday, the optimal sales prices has to be found for dozens of vehicles.
McCar has a data set with the characteristics and sales prices of the last year at its disposal – can you support them and develop a model that predicts the optimal sales price for every vehicle in the future?
Ernst & Young
Ebner Stolz
PHOENIX group
BearingPoint
Die Bewertung, Prozessierung und Abwicklung von Schadensfällen ist für Versicherungen Kerngeschäft und Aufwandstreiber. Die Bewertungen werden heute vor allem anhand von Bilddaten und vor Ort durch Sachverständige vorgenommen. Diese sind dadurch fehleranfällig, langwierig und hochgradig manuell. Eine schnellere, automatisierte und präzisere Einschätzung der Schadenshöhe stellt eine wesentliche Verbesserung für Unternehmen und Mitarbeiter dar. Dafür sollt ihr die KI-gestützte Einschätzung der Schadenshöhe unter zusätzlicher Zuhilfenahme von Computer Vision-Methoden unterstützen! Welche Methoden, Ansätze und Modelle ihr anwendet steht euch frei. Euch wird hierzu ein Datensatz mit Bildmaterial, Label-Informationen und weiteren Features von Wasserschäden bereitgestellt
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