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KPMG enables companies to make better business decisions with the help of modern analysis methods and predictive models.We optimize planning models by using AI and machine learning.Marcin Jakubowski - Consulting Learn moreLearn more
Forward-looking companies use AI and consider internal and external data to make the best possible business decisions. Predictive models and modern analytics improve forecast accuracy and enable companies to make better decisions. AI and machine learning form the basis for intelligent forecasts that are faster and more accurate than conventional calculations. Our predictive forecasting technologies, which have already proven themselves in the market, are based on data sources from KPMG, which achieve significantly higher forecast accuracy with less effort and offer companies significant advantages.
Mathematical optimization in sports
Fairer game schedules, shorter travel times and lower CO2 emissions: KPMG uses prescriptive analytics to optimize tournament schedules and achieve better results.Prescriptive analytics make better planning possible.Pierre-Henri Pingeon - Audit Learn moreLearn more
KPMG has developed an algorithm to optimize the tournament planning of a renowned international sports association and to coordinate 32 teams, more than 65,000 variables, 270,000 restrictions and 1,050 possible solutions. Using a sophisticated approach and complex mathematical methods, KPMG was able to narrow the spectrum of potential options and help the client make an informed decision. The result: a fairer game plan, shorter travel times and fewer CO2 emissions.
Automated data collection for transfer pricing
The annual compilation of all mandatory data for transfer pricing can be very time-consuming. By automating the process, the effort can be reduced and the data quality improved.The automatic fulfillment of all transfer pricing requirements gives companies more time for strategic initiatives.Andreas Wiesner - Tax & Legal Learn moreLearn more
The annual reporting on transfer pricing requires a large amount of raw data that has to be processed for segment reporting and other requirements. The relevant data must be queried by various teams and ERP systems. To automate this process, we have analyzed the data sources and developed extraction mechanisms that automatically retrieve the data. The results are now presented in a standardized way on a dashboard; they can be used for reporting purposes in local transfer pricing files.
A start-up wanted to have its business environment assessed. Our fast and effective ecosystem radar provided the company with all the necessary data.Powerful data collections and stakeholder-specific analyzes enable intelligent business decisions.Jeanette Hasenberger - Deal Advisory Learn moreLearn more
KPMG helped create a business plan for a groundbreaking technology start-up in the field of random number generation. Little data on investors and competitors is available in this new, rapidly growing market. With the help of DealTech and PitchBook, we have created an overview of all competitors, investment phases and investors using a tableau model, which dynamically displays all data to the customer. With the methods used to consolidate, validate and analyze large volumes of data, the customer saved a lot of time and money thanks to the analytics solution developed by KPMG.
We are convinced that our digital future is shaped by our commitment to innovation in technology and the entrepreneurial spirit of our employees.Beat Seger, Partner, Real Estate Advisory, Chief Digital Officer
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MSc Physics, MSc Science, Technology and Policy
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Lead Data Scientist Financial Services Transformation
MSc Information Systems and Management, MSc International Business and Enterprises
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MSc Information Systems
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