![Probability & Partners](https://i0.wp.com/probability.nl/wp-content/uploads/2014/11/pp-logo3.png?fit=340%2C156&ssl=1 "Probability & Partners\"){kind=logo}
This white paper addresses whether and how it is possible to measure a company’s or a portfolio’s contribution to specific goals (SDGs).
Tag Archive for: Svetlana Borovkova
Svetlana Borovkova’s column in the Financial Investigator about factor investing and sentiment. The role of news and social media as a factor and a risk indicator is discussed.
In this paper we describe AI fairness from a quantitative perspective, on the example of credit decision making – which candidates should receive a loan and which not – but the principles we will describe hold more generally in financial services. We explore the roots of bias in AI systems and present popular definitions of fairness adopted by the industry.
Svetlana Borovkova’s column in the Financial Investigator about Fairness in Artificial Intelligence (AI) and Machine Learning (ML) by financial institutions.
Svetlana Borovkova’s column in the Financial Investigator about Fairness in Artificial Intelligence (AI) and Machine Learning (ML) by financial institutions.
Svetlana Borovkova, our head of Quantitative Modelling, will be one of the speakers at the TopQuants event on the impact of COVID-19 on modelling.
With this paper, Probability and Partners would like to assist financial institutions in understanding the implications the ECB guide has for them, as well as help them prepare for the future where climate-related
and environmental risks are a part of everyday reporting.
In this paper, we discuss the three main emerging societal trends that we have identified: social transformation, digitalization and socially responsible innovation – and the effect of these trends on companies and sectors. In our high-level qualitative analysis we take into accountissues such as consumer behavior, business opportunities and government support.
In this paper we highlight the principle of Fairness – being crucial for financial institutes given the potential financial and regulatory risks, but even more concerning tremendous reputational risks – and
why it should be on top of mind for senior executives. We give guidance on how organizations can address AI ethics more proactively from a business perspective as well as in the model validation and
model risk management.
In this online interactive course, we will address issues that a quant will encounter when applying machine learning models to typical problems in the finance sector.