Job Specification for an Artificially Intelligent Banker: The Artificially Intelligent Banker is responsible for the overall management of the AI2H (AI to Human) lending department. The following requirements (job specifications) were determined by extensive data mining analysis and derived from the job description as crucial for success in the Artificially Intelligent Banker role. The successful candidate for the Artificially Intelligent Banker position will possess the following qualifications: Experience Evidence of 8-12 months of continuous uptime without rebooting Progressively more responsible positions in human interface roles, preferably in a similar industry in two different decentralized autonomous firms Indicatively human sales interaction experience with least 10 mln Human subjects is required.
Eternal Risk Management One-Liners A single line is sometimes the only thing that separates you from disaster Do you know of any good one-liners that saved the day at one point? (Update May 2017) We moved the list to the Open Risk Manual for easier editing and contributions Send us your favorite one-liner via the Feedback Button. Please indicate what type of attribution you prefer (anonymous, nickname, full name etc.
Fintech, embrace your inner regulator! 2017 is shaping to be the year of #regtech, aka new technology startups setting up digital shop to help the financial services sector cope with its heavy regulatory burden. But what is regulation? Why is it a burden and how does it relate to real risks and risk management? The narratives around financial regulation have been, for some time, completely dominated by the so-called compliance perspective.
Top 10 Risk Manual Articles: The current list of Top 10 Risk Manual Articles, sorted by reader popularity covers a range of topics in risk management. External Fraud, (Operational Risk) Herfindahl-Hirschman Index, (Concentration Risk) Hannah-Kay Index, (Concentration Risk) Concentration Ratio, (Concentration Risk) Granularity Adjustment, (Concentration Risk) Business Execution, (Operational Risk) Internal Fraud, (Operational Risk) Employment Practices, (Operational Risk) Physical Damage, (Operational Risk) Basel II Advanced IRB Capital Model, (Basel II RWA) The Top 10 is dominated by the Concentration Risk category and the Operational Risk definitions, while the old staple, the Basel II formula for RWA calculations squeezes-in in the tenth place.
The Atlas of Bad Risk Management: The Atlas was discovered recently in archeological 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.
Visualizing the risk management of the future: How do we communicate risk insights? The information tools used by risk managers to communicate insights have been transformed multiple times over the ages. In each era we have adopted existing technologies, but we also created demand for new technologies. Our era is no exception. To understand where we are going, we need to understand where we are coming from. So lets briefly recap our industrious past before we peer briefly into the visually exciting crystal ball.
Reducing variation in credit risk-weighted assets - The benign and vicious cycles of internal risk models: March 2016 wasn’t a good month for so called internal risk models, the quantitative tools constructed by banks for determining such vital numbers as how much buffer capital is needed to protect the savings of their clients. First came the Basel Committee’s proposed revision to the operational risk capital framework applicable to banks, next came a similarly fundamental overhaul of what form of risk quantification will be acceptable for calculating credit risk capital requirements.
Save the AMA whale: ΝΒ: This is not a post about real whales and the ongoing struggle to keep these magnificent mammals alive for future generations to marvel at. Hopefully the individuals who have risked their lives to bring the near extinction of many whale species to worldwide attention will not take offense with us usurping imagery linked to this valiant campaign. We simply want to draw attention to another, rather more armchair type of campaign, namely: saving the AMA risk model.
Top 10 Reasons why Silicon Valley cannot disrupt Wall Street (yet): This is the 2016 update on our independent critical examination of the running meme of fintech disruption in the financial services space. The Top Ten list of why Silicon Valley cannot Disrupt Wall Street (yet) was published first here in October 2014 Motivation The possibility, heck inevitability, of Silicon Valley (Henceforth abbreviated SV, representing new technology entrants) aiming to disrupt Wall Street (Abbreviated WS, representing incumbents) is one of the fascinating memes of our times.
From OpenRisk, to all our friends, colleagues, collaborators, users, partners and the general public: May the network be with you in 2016!
Risk Management Skills for the Fintech Era Risk Management Skills for the Fintech Era: Financial services jobs continue being decimated. A recent (as of the initial post date) FT article was a sobering summary of the continuing transformation of the financial sector: 2015 alone has seen more than 10% reduction of the total workforce across large EU/US banks: As main drivers for this true jobs hecatomb are cited higher minimum capital requirements (that depress Return on Equity and hence require lower costs to restore it to investor acceptable levels), low interest rates that erode Profitability Margins, and a generally subdued economic landscape which reduces Volumes.
Seven Heavens of Finance and the Open Risk API: Back-to-basics is not salvation It has become trendy since the financial crisis to be wearing an anti-complexity hat in matters concerning the shape of the financial system. This is an understandable reaction to the entangled constructions that had sprung to existence in the hyper-leveraged markets of the naughty noughties. Yet shifting through the ruminations and proclamations one cannot help but get the impression that there is a sort of denial of the complexity that underlies the real economy.
What Inka quipus teach us about data management: Chances are that your knowledge of ancient Peruvian culture is a bit rusty. Maybe you have some vague high-school memories of an extensive but backward empire that was conquered and then asset-stripped by a handful of Spanish conquistadores. Or maybe your best preserved memory is the excitement of reading von Daniken’s speculations that the Nazca lines are extraterrestrial spaceports. But unless you happened at some point later in life to hear about the work of Prof.
Risk modeling is as much art as it is science: The Zen of Modeling aims to capture the struggle for risk modeling beauty An undocumented risk model is only a computer program A risk model that cannot be programmed is only a concept A risk model only comes to life with empirical validation Correct implementation of an imperfect model is better than wrong implementation of a perfect model In complex systems there is always more than one path to a risk model There are no persistently true models but there are many persistently wrong models Correlation is imperfectly correlated with causation Nirvana is the simplest model that is fit for purpose Hierarchical systems lead to hierarchical models.
The four stages of social: Homo Staticus The web as we now know it burst first into the open in the early nineties. It certainly did not start among the socially active classes. It was an invention by and for nerdy CERN physicists, to exchange data about elementary particle experiments. The academics did finally figure out the true value of this technology: You could put your face online, along with a CV.
The mystery of the collapsed cathedral: You walk to the center of an old city and you see its glorious cathedral lying in ruins. What in the world has happened here? Your investigative instinct goes into overdrive. This is not supposed to happen. Not in peacetime anyway. How can it be that this magnificent edifice, after gracing the town’s central square for who knows how many centuries, is now little more than a rubble pile in the center of town?
Securitisation versus Banking: The ever elusive CMU dream There is(/was) renewed interest in EU-land over deepening a capital markets union, aka CMU. It is among the initiatives being pursued by the Commission in order to help accelerate growth in the European Union. The initiative encompasses many elements, both around equity (shares) and debt markets. One important pillar of the CMU aims to re-launch some version of an EU securitisation market. This segment was never really defined in a EU-wide basis.
Criteria for identifying simple, transparent and comparable securitisations: (See BIS D304) Our view is that securitisation is fundamental financial technology and there is no intrinsic technical reason why it could not be harnessed to best serve the functioning of modern economies. We believe, though, that a comprehensive overhaul of historical securitisation practices is the best means of addressing the stigma that has been attached to it in the follow up to the recent financial crisis.
Open Source Risk Modeling Manifesto: This post is a summary of a presentation given at the 2014 Autumn TopQuants Meeting, aka, the Open Source Risk Modeling Manifesto. The dismal state of quantitative risk modeling The current framework of internal risk modeling at financial institutions has had a fatal triple stroke. We saw in quick sequence: market risk, operational risk, and credit risk measurement failures, covering practically all business models.
In our personal lives, it is the balance between work and life, or the dreadful weight balance. In the professional sphere it might be the balance between debt and equity in the financial industry, or the balance between convenience and citizen privacy in the new tech industry, or the welfare of the many balanced against the property of the few, or finally the geopolitical balance of power of different peoples… Balance ensures sustainability as it helps steer away from the risks that lurk at the extremes.