Risk, Randomness, Uncertainty and other Ambiguous Terms Uncertainty versus Risk is a popular discussion topic among risk managers, especially after major risk management disasters. The debate can get really hairy and drift into deep philosophical areas about the nature of knowledge etc. Yet the significance of having an as clear as possible language toolkit around these terms should not be underestimated. Practical risk management typically shuns too deep excursions into the meaning of things, yet that is not quite compatible with the use of sophisticated methods and tools (such as a Risk Model ) that assumes an understanding of the scope and limitations of “knowledge”.
Data Quality and Exploratory Data Analysis using Python In two new Open Risk Academy courses we figure step by step how to use python to work to review risk data from a data quality perspective and how to perform exploratory data analysis with pandas, seaborn and statsmodels:
Introduction to Risk Data Review Exploratory Data Analysis using Pandas, Seaborn and Statsmodels
The challenge with historical credit data Historical credit data are vital for a host of credit portfolio management activities: Starting with assessment of the performance of different types of credits and all the way to the construction of sophisticated credit risk models. Such is the importance of data inputs that for risk models impacting significant decision making / external reporting there are even prescribed minimum requirements for the type and quality of necessary historical credit data.
The Atlas of Bad Risk Management The Atlas was discovered recently in archaeological work studying pre-crisis civilizations. Despite the obvious wear and tear, all key risk failure areas have been preserved. We note the remarkable diversity of organizational forms and economic structures. Most interestingly, there is even an uncharted territory that was rumored to be inhabited by black swans.
We handed over this invaluable treasure to a risk management expert and asked her to identify any similarities with modern risk management challenges.
From Big Data, to Linked Data and Linked Models The big data problem:
As certainly as the sun will set today, the big data explosion will lead to a big clean-up mess How do we know? It is simply a case of history repeating. We only have to study the still smouldering last chapter of banking industry history. Currently banks are portrayed as something akin to the village idiot as far as technology adoption is concerned (and there is certainly a nugget of truth to this).
