Data Scientists Have No Future The working definition of a Data Scientist seems to be in the current overheated environment:
doing whatever it takes to get the job done in a digital #tech domain that we have long neglected but which is now coming back to haunt us!
That is nice urgency while it lasts, but it is not a serious job description for the future.
You will always find entrepreneurial institutions to offer degrees and certifications on the latest trending hashtag.
Four individuals that can look straight into your eyes Here are four individuals that can look straight into your eyes
Torvalds developed the #linux operating system, the software engine now powering anything from the tiniest #raspberrypi to the scariest supercomputer. Humanity’s best guarantee that the digital era remains an equal playing field Mullenweg developed the #wordpress blogging platform. Gave voice and content ownership to millions of digital authors making him the closest to the Gutenberg of our era Dougiamas developed #moodle, the world’s digital Academy.
Machine Learning Ballyhoo Are you getting a bit tired with all the machine learning ballyhoo?
You can blame it all on a German mathematician(*), Carl Friedrich Gauss, who started the futuristic mega-trend back in 1809: He showed us how to train a straight line to pass nicely through a cloud of unruly, scattered data points. To find, in effect, a path of least embarrassment.
Two+ centuries later it is still a profitable enterprise to invent elaborate variations of that theme, now going under the more exalted name of supervised learning, which may or may not include deep learning.
If programming languages were human languages which one would be which? Most developers know (or get to know quickly once they join a team) that programming languages are as much about communicating with other developers as they are about instructing the computer. Which raises the interesting question: If programming languages were human languages which one would be which? Here is a (tonque-in-cheek mind you!) compilation of a mapping between programming languages and human languages.
The Zen of IFRS 9 Modeling At Open Risk we are firm believers in balancing art and science when developing quantitative risk tools. The introduction of the IFRS 9 and CECL accounting frameworks for reporting credit sensitive financial instruments is a massive new worldwide initiative that relies in no small part on quantitative models. The scope and depth of the program in comparison with previous similar efforts (e.g. Basel II) suggests that much can go wrong and it will take considerable time, iterations, communication and training to develop a mature toolkit that is fit-for-purpose.
Guiding principles for a viable open source operational risk model (OSORM) Such a framework:
Must avoid formulaic inclusion of meaningless risk event types (e.g., legal risk created by the firm’s own management decisions) or any risks where the nature and state of current knowledge does not support any meaningful quantification. Such potential risks would be managed outside the framework Must employ a bottom-up design that addresses the risk characteristics of simpler business units first and (if needed) creates a combined profile for a more complex business in a building block fashion.
The data privacy genie is out of the bottle From Yahoo’s massive email data leaks, to Equifax’s exposing of sensitive data for a large segment of the US population, to Apple’s resisting the bypassing the security features of the iPhone, not a week goes by without some alarming piece of news around data privacy.
The ramifications for the legal use of private digital data by companies and government and the consequences of illegal or unintended use are huge.
How to Stress Test Financial Weapons of Mass Destruction In recent decades we have been collectively spared the haunting images and existential anxiety provoked by the sight of detonating nuclear weapons for testing purposes - not to mention the increased levels of radiation in the atmosphere and other side-effects. This achievement is largely thanks to a series of treaties to control nuclear bomb testing that have been signed and enforced by most (unhappily not all) countries worldwide.
The Promise of Open Risk Data There is a legend that every time a data set is released into the open, somewhere dies a black swan Well, it is not a true legend. Legends take centuries of oral storytelling to form. In our frantic age, dominated by the daily news cycle and viral twitter storms, legends have been replaced by the rather more short-lived memes and #hashtags.
Black Swans need no introductions The whole informal theory of black swans concerns improbable events (low likelihood events) that come as a nasty surprise and have large impact.
Seeking clues for financial stability from quantum physics How physicists discovered why the world is stable Physics is one of those remarkably successful branches of science that have helped shape the modern era. Let your gaze drop on any man made gadget in your surroundings and its likely that its working principles go back to a fundamental discovery in physical science that dates back no more than two hundred years or so.
If banks were airlines Ever since the scary turbulence of the Great Financial Crisis it has been instructive and illuminating to compare the travails of the financial industry with the state of other industries, especially those more down to earth, also known as real world industries.
The automotive industry was particularly handy for good analogies: Almost all of us have first-hand experience with the successes and failures of risk management when it concerns cars and driving.
Lehman, Brexit, De-Regulation and the future of EU fintech The decision by the citizens of the United Kingdom to vote against continuing membership of the European Union (#brexit) will have wide ranging repercussions on many facets of the European (and even global) economic system. As of early 2017, we see this trend further reinforced by a new US administration that aims to revisit a wide range of policy choices, including aspects of financial services regulation.
Transparency, collaboration key to regaining trust in financial services In banking, confidence is the first order of business Maintaining the confidence of market participants, clients, shareholders, regulators and governments is uniquely important for the financial sector. Trust is, quite literally, the real currency. Yet it is a truism that confidence is hard to build up and rather easy to destroy. Why is this so?
The short answer: The difficulty in rebuilding trust is linked to the lack of transparency.
We are hiring artificially intelligent bankers 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:
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 to include in the list. Please indicate what type of attribution you prefer (anonymous, nickname, full name etc.
Accounting probably would not count among the more glamorous of professions. The reasons for that status and whether it is justified are beyond the scope of this brief commentary.
What is interesting to note, though, is that the relative attractiveness of accounting is arguably improving, driven by a number of systemic societal developments:
the need for more proactive assessment of the state of the world, eliminating the infamous “rear-view mirror” pathology.
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 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.
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.
