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H2020Doctoral network2015–2019

BigDataFinance · Training for Big Data in Financial Research and Risk Management

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2015-10-01 → 2019-09-30
EU contribution
€3,463,286
Participants
13
Scheme
MSCA-ITN-ETN

Lines connect the coordinator with its partners.

Results in brief

Training for Big Data in Financial Research and Risk Management

We are witnessing a new industrial revolution driven by digital data, computation, and automation. The resulting datasets are so large and complex that such “Big Data” is becoming difficult to process with the current data management tools and methods. If successfully processed and managed, Big Data has the potential to spur new products, services, and practices as well as new scientific methodologies. One European sector that could greatly benefit from the use of Big Data is Finance. To exploit this potential, banks and other financial institutions must be able to handle and process massive heterogeneous data sets in a fast and robust manner. BigDataFinance ITN, “Training for Big Data in Financial Research and Risk Management”, has provided doctoral training in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 Early State Researchers (ESR). The main training objective of BigDataFinance were to meet the increasing commercial demand for well-trained researchers with experience in both Big Data techniques and Finance. The main research object was to develop and implement new quantitative models and econometric methods for empirical financial research and risk management by bridging the gap between research methodologies in Finance and Data Science. To achieve the objectives, the emphasis was put on exploiting big data techniques to manage and use datasets that are too large and complex to process with conventional methods. This program provided new realistic data-driven scientific approaches that will be requisite in finance.

Data: CORDIS, © European Union

Project objective

BigDataFinance, a Marie Skłodowska-Curie Innovative Training Network “Training for Big Data in Financial Research and Risk Management”, provides doctoral training in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 researchers. The main objectives are i) to meet an increasing commercial demand for well-trained researchers experienced in both Big Data techniques and Finance and ii) to develop and implement new quantitative and econometric methods for empirical finance and risk management with large and complex datasets. To achieve the objectives, the emphasis is put on exploiting big data techniques to manage and use datasets that are too large and complex to process with conventional methods.Banks and other financial institutions must be able to manage, process, and use massive heterogeneous data sets in a fast and robust manner for successful risk management; nonetheless, financial research and training has been slow to address the data revolution. Compared to the USA, Europe is still at an early stage of adopting Big Data technologies and services. Immediate action is required to seize opportunities to exploit the huge potential of Big Data within the European financial world.This world-class network consists of eight academic participants and six companies, representing banks, asset management companies, and data and solution providers. The proposed research is relevant both academically and practically, because the program is built around real challenges faced both by the academic and private sector partners. To bridge research and practice, all researchers contribute to the private sector via secondments. BigDataFinance provides the European financial community with specialists with state-of-the-art skills in finance and data-analysis to facilitate the adoption of reliable and realistic methods in the industry. This increases the financial strength of banks and other financial institutions in Europe.

Original text from CORDIS.

Participants

Links

Data: CORDIS, © European Union