Risk Model

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). Yet it is also true that banks, in many jurisdictions and across trading styles and business lines, have adopted data driven models already a long time ago. In fact, long enough ago that we have already observed how it call all ended pear shaped, Great Financial Crisis and all.

Open Risk White Paper 6: Stress Testing Methodology for FX Lending

We develop a simple methodology for stress testing portfolios of credit instruments classified as foreign exchange lending. Loans whose repayment schedule is denominated in a currency other than that of the borrower’s domestic currency are commonly seen in many jurisdictions and have a risk profile that is considerably more complicated than domestic currency loans. Yet the literature for credit risk assessment and stress testing of portfolios of such loans is very limited, which means that Stress Testing and Internal Capital Adequacy Assessment (ICAAP) requirements are harder to meet. Our methodology builds on existing standard tools used in portfolio credit risk modeling and enables obtaining insights into the additional risk factors embedded in foreign currency lending.

Presentation at TopQuants 2015: Open Risk API

Improved financial risk management through open data, open source and web technologies.

This is a Presentation given at the TopQuants/DNB Autumn Meeting, Amsterdam, Nov 18, 2015

Download

Download OpenRiskPR00

Source Code

• Open Risk API

Citation

@ARTICLE{OpenRiskPresentation00,
 author = {P. Papadopoulos},
 year = {2015},
 note = {\href{https://www.openriskmanagement.com/wp-content/uploads/2015/11/TopQuants2015.pdf}{Download URL}},
 title = {{Presentation at TopQuants 2015: Open Risk API}},
 journal = {Open Risk Presentations}
}

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 noughts.

Open Risk White Paper 4: Open Risk Model Taxonomy

We develop a taxonomy for risk models that aims to support an open source risk models framework. The proposal builds on and extends some commonly used risk taxonomies within financial services firms but introduces some significant new elements. We first review the motivation for risk taxonomies, the concepts and tools that are involved and some weaknesses of current schemes. We try also to clarify the link between risk models and risk taxonomies.

Open Source Risk Data with MongoDB and Python

Open source software is all the rage those days in IT and the concept is making rapid inroads in all parts of the enterprise. An earlier comprehensive survey by Gartner, Inc. found that by 2011 more than half of organizations surveyed had adopted open-source software (OSS) solutions as part of their IT strategy. This percentage may have currently exceeded the 75% mark according to open source advisory firms.

Open Risk API

If you work in financial risk management you will most likely recognize where the following sentence is coming from:

One of the most significant lessons learned from the global financial crisis that began in 2007 was that banks information technology (IT) and data architectures were inadequate to support the broad management of financial risks. This had severe consequences to the banks themselves and to the stability of the financial system as a whole

Open Risk White Paper 3: Introducing the Open Risk API

We develop a proposal for an open source application programming interface (API) that allows for the distributed development, deployment and use of financial risk models. The proposal aims to explore the following key question: how to integrate in a robust and trustworthy manner diverse risk modeling and risk data resources, contributed by multiple authors, using different technologies, and which very likely will evolve over time.

Risk modeling is as much art as it is science

The Zen of Modeling aims to capture the struggle for risk modeling beauty

1. An undocumented risk model is only a computer program
2. A risk model that cannot be programmed is only a concept
3. A risk model only comes to life with empirical validation
4. Correct implementation of an imperfect model is better than wrong implementation of a perfect model
5. In complex systems there is always more than one path to a risk model
6. There are no persistently true models but there are many persistently wrong models
7. Correlation is imperfectly correlated with causation
8. Nirvana is the simplest model that is fit for purpose
9. Hierarchical systems lead to hierarchical models. Uncertainty is highest at the top
10. Model assumptions are more vulnerable than model structure
11. Building risk models is easy, managing model risk is not
12. Models inherit their nature from their creators, but nurture from their use environment
13. Models don’t speak people’s languages. It is the responsibility of the modeler to translate to an understandable idiom
14. People don’t care about models, only about model outcomes. It is the responsibility of the modeler to be responsible.
15. Models closed in black boxes perish. Models live a healthy life when open and free.

Update May 2017: The Zen of Modeling has also been integrated into the Open Risk Manual to enable easier linking to the knowledge based developed there.

A mini course on risk management, its perils and the silver lining

When talking about risk management, it is not very clear what we are talking about in broad terms, definitely not getting clearer when we start getting into the details and it is even not clear how to best use the (possibly flawed) insights we produce.

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. The laudable objective of introducing criteria for simple, transparent and comparable securitisations, (STCS Criteria for short) should aim to achieve a quantum leap in transparency and avoid the risk of perceived ineffectual measures. Technically this would require a visible reduction of model risk for prospective investors, expressed for example in tangible new ability to perform relevant risk analyses.

This page 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.

Financial Risk Modelling has suffered enormous setbacks in recent years, with all major strands of modelling (market, credit, operational risk) proven to have debilitating limitations. It is impossible to imagine a modern financial system that does not make extensive use of risk quantification tools, yet rebuilding confidence that these tools are fit-for-purpose will require significant changes. These need to improve governance, transparency, quality standards and in some areas even the development of completely new strands of modelling.

We are happy to publish the first installment of a trilogy that focuses on the risk factors that can turn any credit portfolio toxic.

The first topic is default correlation, a topic that is both core to understanding credit risk and much misunderstood.

Enjoy!

The rationale for continuing with internal capital models in the Basel 3 world

Overview of the challenges and opportunities offered by internal capital models (economic capital models) in the post-crisis era. Conference Presentation given at:

• Venue: 2nd Annual Capital Modelling under Basel III (Marcus Evans Conference)
• Location: London
• Time: January 28th 2014
• Link to presentation: Local file

A Python module of analytic solutions suitable for testing credit portfolio models has been uploaded in the Open Risk github repository