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Data-Driven Financial Risk and Regulatory Reporting (DaDFiR3)

Description

DaDFiR3 pursues the vision of a system for automated regulatory financial reporting that uses financial contract-level data combined with market data to produce the required analyses as required for internal and external oversight.

Content and objective

We will deploy an ICT infrastructure that provides a suitable ecosystem for forward-looking financial simulation and analysis. We will also further develop the financial mathematical toolset for risk analysis. Key elements of our technology are:

  • the ACTUS standard for the digital representation of financial contracts;
  • blockchain technology and smart contracts for decentralized finance;
  • Big Data technology;
  • state-of-the-art financial analytics.

This infrastructure enables largely automated, situational risk assessment of individual financial institutions (microprudential supervision) and, in the final development, of the entire financial system (macroprudential supervision).

Scientific and societal context

Effective and efficient financial regulation serves is essential for a stable financial system and thus for the whole economy and society. The financial crisis of 2007-2009 demonstrated this impressively. Regulatory financial reporting is a key element.

With the new infrastructure, regulatory financial reports can be flexibly adapted to the respective needs and quickly produced. The currently considerable costs for banks will be greatly reduced through automation. At the same time, the new DeFi area will also be included. The ultimate goal is to create an automated system similar to the worldwide daily weather forecast.

Key data

Projectlead

Prof. Dr. Henriette Elise Breymann, Dr. Gisela Reichmuth

Project team

Christoph Auth, Dr. Patrick Hauf, Prof. Dr. Walter Farkas (Universität Zürich UZH), Prof. Dr. Tim Weingärtner (Hochschule Luzern)

Project partners

Universität Zürich UZH; Hochschule Luzern

Project status

ongoing, started 04/2022

Institute/Centre

Institute for Data Science (IDS); Institute of Wealth and Asset Management (IWA)

Funding partner

BRIDGE Discovery

Project budget

1'500'000 CHF