This document summarizes the impact of key European regulations on data science in finance, including opportunities and challenges. It discusses regulations around privacy (GDPR), financial stability (MIFID II), climate change (BOE SS3/19), and artificial intelligence (EC White Paper). These regulations influence the development of explainable, unbiased, and causally accurate AI models. They also create commercial opportunities to leverage regulations through technology. Examples are provided around applying explainable AI to credit risk and reducing regulatory burden through AI.

1. Data Science vs
European Regs
(in Finance)
Stop complaining and start mining

2. European Regulations
Privacy Protection GDPR
Financial Stability MIFID-II
Climate Change BOE SS3/19
Impact of AI EC White
paper

3. Impact of regulations
● Explainable AI (GDPR Right to explain, EC White paper)
● Causal inference (BOE SS3/19 ‘what if’ scenario)
● Unbiased AI (EC White paper)
● Commercial opportunities (MIFID II)
Examples (Right to explain)
● Explainable AI in Credit Risk: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3506274
● FICO: https://community.fico.com/s/explainable-machine-learning-challenge
● Bias: https://www.oreilly.com/radar/how-data-privacy-leader-apple-found-itself-in-a-data-ethics-catastrophe/

4. GDPR
● Right to be forgotten: https://gdpr-info.eu/art-17-gdpr/
“This Regulation lays down rules relating to the protection of natural persons with regard to the processing
of personal data and rules relating to the free movement of personal data.”
● Right to explanation: https://www.privacy-regulation.eu/en/r71.htm
such processing should be subject to suitable safeguards, which should include specific information to the
data subject and the right to obtain human intervention, to express his or her point of view, to obtain an
explanation of the decision reached after such assessment and to challenge the decision.
Impact:
● Explainable models
● Non discriminatory models

5. EC AI White Paper
The Commission published a Communication31 welcoming the seven key requirements identified in
● the Guidelines of the High-Level Expert Group:
● Human agency and oversight,
● Technical robustness and safety,
● Privacy and data governance,
● Transparency,
● Diversity, non-discrimination and fairness,
● Societal and environmental wellbeing, and
● Accountability.
Source: https://ec.europa.eu/info/sites/info/files/commission-white-paper-artificial-intelligence-feb2020_en.pdf

6. Unbiased AI
https://www.europarl.europa.eu/news/en/agenda/briefing/2020-02-10/3/artificial-intelligence-how-to-ensure-its-safe-and-unbiased-use
“When interacting with automated decision-making systems, one should be “properly informed about how
it functions, how to reach a human with decision-making powers, and how the system’s decisions can be
checked and corrected”, says the draft resolution by the Internal Market and Consumer Protection
Committee.”
Research:
https://www.frontiersin.org/articles/10.3389/frai.2020.00034/abstract
https://www.csail.mit.edu/news/ai-de-biases-algorithms

7. MIFID II
“Our rules to implement the Markets in Financial Instruments Directive (MiFID) II
require asset managers to explicitly pay for third-party research, and brokers to
price and provide research separately. These are the findings of our review on
how firms have implemented these rules since their introduction in January 2018.”
● Increased regulatory burden
● Use of AI to minimize it: https://feedstock.com
○ Leverage regulation: extract information from research ...
○ … while implementing compliance

9. Bank of England SS3/19
“Climate change, and society’s response to it, present financial risks which are
relevant to the [Prudential Regulation Authority]’s objectives.”
“scenarios based around average global temperature increases consistent with, or
in excess of 2˚C; and scenarios where the transition to a low-carbon economy
occurs in an orderly manner, or not.”
Source: https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/supervisory-statement/2019/ss319