Latest Insights

Traveling with bitcoins

In the past 20 years, all industries have felt the impact of technological innovation. In some cases, this impact has been so great that disruption has occurred. A clear and often used example is the travel industry, where companies that did not exist 20 years ago, like AirBnB and Booking.com, are now major players.

News Sentiment Analysis and Credit Risk

Do we still need humans to monitor and interpret qualitative data for our risk models?

Recent technological advances increase the possibility of using qualitative data in risk models to ensure a timelier recognition of threats. News articles, which can be seen as a type of unstructured data, are flooding the world every day. However, one can imagine the time it would take to manually process all this information. Recent developments in natural language processing (NLP) show some very promising results in automating that task by a computer. We assess the possibilities of these recent advances within credit risk management.

How can banks manage climate-related and environmental financial risks

Zanders developed a Scan & Plan Solution

Climate and environmental changes are viewed among the most important risks in society at present. As the financial sector is key for the transition towards a low-carbon and more circular economy, financial institutions have to deal with climate-related and environmental financial risks (C&E risks). At the same time, the increased importance of these C&E risks also presents new business opportunities for the financial sector. Therefore, to support banks in their self-assessment and action plans, Zanders developed a Scan & Plan Solution on C&E risks.

SARON hedging strategies

Hedging of SARON exposure, Part II

On 5 March 2021, the Financial Conduct Authority (FCA) announced the official dates of the cessation and loss of representativeness of the LIBOR rates. As a result, 31 December 2021 will be the last day on which the CHF LIBOR will be published. During the last months, a multitude of informative documents were provided by the Alternative Reference Rates Committee (ARRC) and the International Swaps and Derivatives Association (ISDA). As a follow-up from the previous article Hedging of SARON exposure, Part I: Explanatory power of SARON term and actual rates, this article assesses the different compounding methodologies with respect to hedging strategy.

Can machine learning predict the probabilities of default?

According to Moore’s law, computing power doubles up each two years. This performance increase in computing power makes machine learning increasingly efficient each year, and widely applicable. But does this also apply to credit risk issues?