Economic Networks

The role of simulation in risk management and decision support

A Simulation is a simplified imitation of a process or system that represents with some fidelity its operation over time. In the context of risk management and decision support simulation can be a very powerful tool as it allows us to assess potential outcomes in a systematic way and explore what-if questions in ways that might otherwise be not feasible. Simulation is used when the underlying model is too complex to yield explicit analytic models (An analytic model is one can be “solved” exactly or with standard numerical methods, for example resulting in a formula).

Federated Credit Systems, Part I: Unbundling the Credit Provision Business Model

As an architectural design and information technology approach, federation has received increased attention in domains such as the medical sector (under the name federated analysis), in official statistics (under the name trusted data) and in mass computing devices (smartphones), under the name federated learning.

Open Risk White Paper 9: Federated Credit Systems, Part I: Unbundling The Credit Provision Business Model

In this (the first of series of three) white paper, we introduce and explore the concept of federated credit systems. We review the rapidly developing fields of Federated Analysis and Federated Learning as already actively studied in the domains of medicine and consumer computing devices. This forms the backdrop for understanding the potential and challenges of applying similar concepts in finance and more particular credit provision. The context of modern banking is substantially different from the above-mentioned use cases. Understanding and shaping federated information systems to cater to its unique features and constraints (key added value, competitive landscape, regulatory frameworks) will help accelerate the adoption of new designs. Towards that purpose we construct a framework that conceptually unbundles the complex operation that is modern credit provision. We introduce a number of fundamental business entities (subunits) and their associated functions and discuss the underlying business models. We discuss, in particular, how and why they exchange data and metrics and the key risk management challenges of each. Finally, we sketch current architectures for credit information sharing with an overture to the new possibilities opening up with federation architectures.

Course Content

This course is a CrashProgram (short course) introducing the GeoJSON specification for the encoding of geospatial features. The course is at an introductory technical level. It requires some familiarity with data specifications such as JSON and a very basic knowledge of Python

Course Content

This course is an introduction to the concept of credit contagion. It covers the following topics:

• Contagion Risk Overview and Definition
• Various Contagion Types and Modelling Challenges
• The Simple Contagion Model by Davis and Lo
• Supply Chains Contagion
• Sovereign Contagion

Connecting the Dots: Economic Networks as Property Graphs

We develop a quantitative framework that approaches economic networks from the point of view of contractual relationships between agents (and the interdependencies those generate). The representation of agent properties, transactions and contracts is done in the context of a property graph.

A typical use case for the proposed framework is the study of credit networks.

Open Risk White Paper 8: Connecting the Dots, Economic Networks as Property Graphs

We develop a quantitative framework that approaches economic networks from the point of view of contractual relationships between agents (and the interdependencies those generate). The representation of agent properties, transactions and contracts is done in the context of a property graph. A typical use case for the proposed framework is the study of credit networks.

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.

Release of version 0.3 of the ConcentrationMetrics Library

Further building out the OpenCPM set of tools, we release version 0.3 of the ConcentrationMetrics Library. This python library for the computation of various concentration, diversification and inequality indices.

The below list provides documentation URL’s for each one of the implemented indexes