# OpenNPL

### Mathematical Representations of Credit Portfolio Data

What do we mean by credit data? This post is a discussion around mathematical terminology and concepts that are useful in the context of working with credit data, taking us from network graph representations of credit systems to commonly used reference data sets

Course Objective Digging into the meaning of credit data collections, the logic that binds them together towards understanding what they can be used for and what limitations and issues they may be affected by, this new course in the Credit Portfolio Management category explores a new angle to look at an old practice. The course is now live at the Academy. Pre-requisites Familiarity with credit provision in general (lending products, banking processes and credit risk) is required for getting the most out of the course.

### Marking Pi Day 2021 With a Raspberry Pi Docker Image for OpenNPL

We celebrate Pi Day 2021 releasing an ARM version of the openNPL platform that is suitable for the Raspberry Pi

Celebrating Pi Day 2021 Pi Day is celebrated every year on March 14th. The reason of course is that the day is denoted in some calendars as (3/14), which evokes of 3.14, the first three digits of “π”. A thin excuse maybe but sufficient for the true believers to join along! The occasion represents an annual opportunity for mathematics and science enthusiasts to recite the infinite charms of Pi, including its irrationality, to talk to friends and family about math and its uses, and, when everything else fails, simply eat pie.

### Non-Performing Loan Ontology

The NPL Ontology (NPLO) is a new ontology describing datasets of Non-Perfoming Loan Portfolios.

The Non-Perfoming Loan Ontology The Non-Performing Loan Ontology is a framework that aims to represent and categorize knowledge about non-performing loans using semantic web information technologies. Codenamed NPLO, it codifies the relationship between the various components of a Non-Performing Loan portfolio dataset.(NB: Non-performing loans are bank loans that are 90 days or more past their repayment date or that are unlikely to be repaid, for example if the borrower is facing financial difficulties).

### openNPL 0.2 REST API implementation

The 0.2 release of openNPL exposes a RESTful API that provides easy standardized online access to NPL credit portfolio data conforming to the EBA NPL templates

openNPL 0.2 release The open source openNPL platform supports the management of standardized credit portfolio data for non-performing loans. In this respect it implements the detailed European Banking Authority NPL loan templates. openNPL aims to be at the same time easy to integrate in human workflows (using a familiar web interface) and integrate into automated (computer driven) workflows. The latest (0.2) release exposes a REST API that offers machine oriented access using, what is by now, the most established mechanism for achieving flexible online data transfers.

### openNPL now Available in Dockerized Form

Open Source, cloud based management of Non-Performing Loan data following the European Banking Authority's templates with just a few keystrokes!

openNPL now Available in Dockerized Form Following up on the first release of openNPL the platform is now available to install using Docker. Running openNPL via docker is the installation option that simplifies the manual process (but a working docker installation is required!). Docker Hub You can pull the latest openNPL image from Docker Hub (This method is recommended if you do not want to mess with the source distribution).

### openNPL: Open Source NPL Platform - First Release

We introduce an open source platform that allows the easy management of non-performing loan data

Non-Performing Loans The covid-19 crisis will certainly impact the concentration of Non-Performing Loans but given the special nature of this economic crisis compared (in particular) with the 2008 financial crisis it is unclear how precisely things will evolve. In a previous post and white paper (OpenRiskWP07_022616) we discussed the importance of advancing open and transparent methodologies for managing the risks associated with such credit portfolios. Effective management of NPL is also a top regulatory priority.

### Comparing Google Community Mobility Reports Across Countries

The community mobility reports and OpenCPM In a previous post we introduced new OpenCPM functionality that integrates COVID-19 community mobility data (currently from Google). The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential. While these reports are unlikely to persist as open data sources in the long term, the current availability (as of May 2020) enables providing within OpenCPM a mobility data dashboard that can help draw insights through visualization and statistical analysis.

### Exploring Community Mobility Reports Using OpenCPM

The community mobility reports and OpenCPM As the COVID-19 pandemic unfolded technology providers (most notably Google and Apple) made available to the public aggregated and anonymized data about human mobility in the crisis period (on the basis of smartphone location data). These Community Mobility Reports provide insights into how mobility patterns changed in response both to pandemic news and policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of locations and activities, such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

### Visualization of large scale economic data sets

Visualization of large scale economic data sets Economic data are increasingly being aggregated and disseminated by Statistics Agencies and Central Banks using modern API’s (application programming interfaces) which enable unprecedented accessibility to wider audiences. In turn the availability of relevant information enables more informed decision-making by a variety of actors in both public and private sectors. An excellent example of such a modern facility is the European Central Bank’s Statistical Data Warehouse (SDW), an online economic data repository that provides features to access, find, compare, download and share the ECB’s published statistical information.

### Machine learning approaches to synthetic credit data

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.

### Stressing Transition Matrices

Release of version 0.4.1 of the transitionMatrix package focuses on stressing transition matrices Further building the open source OpenCPM toolkit this realease of transitionMatrix features: Feature: Added functionality for conditioning multi-period transition matrices Training: Example calculation and visualization of conditional matrices Datasets: State space description and CGS mappings for top-6 credit rating agencies Conditional Transition Probabilities The calculation of conditional transition probabilities given an empirical transition matrix is a highly non-trivial task involving many modelling assumptions.

### Release 0.4 of transitionMatrix adds Aalen-Johansen estimators

Release of version 0.4 of the transitionMatrix package Further building the open source OpenCPM toolkit this realease of transitionMatrix features: Feature: Added Aalen-Johansen Duration Estimator Documentation: Major overhaul of documentation, now targeting ReadTheDocs distribution Training: Streamlining of all examples Installation: Pypi and wheel installation options Datasets: Synthetic Datasets in long format Enjoy!

### Comparing IFRS 9 and CECL provision volatility

Is the IFRS 9 or CECL standard more volatile? Its all relative Objective In this study we compare the volatility of reported profit-and-loss (PnL) for credit portfolios when those are measured (accounted for) following respectively the IFRS 9 and CECL accounting standards. The objective is to assess the impact of a key methodological difference between the two standards, the so-called Staging approach of IFRS 9. There are further explicit differences in the two standards.

### Version 0.4 of the Concentration Library adds geographic / industrial concentration functionality

Release of version 0.4 of the Concentration Library adds Geographic / Industrial concentration indexes Further building out the OpenCPM set of tools, we release version 0.4 of the Concentration Library, a 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 classic indexes (the Hoover index is a new addition in this release) Atkinson Index Hoover Index Concentration Ratio Berger-Parker Index Herfindahl-Hirschman Index Hannah-Kay Index Gini Index Theil Index Shannon Index Generalized Entropy Index Kolm Index An important new direction that appears first in this release is the introduction of indexes that measure geographical and industrial concentration.

### Credit Portfolio PnL volatility under IFRS 9 and CECL

Credit Portfolio PnL volatility under IFRS 9 and CECL Objective We explore conceptually a selection of key structural drivers of profit-and-loss (PnL) volatility for credit portfolios when profitability is measured following the principles underpinning the new IFRS 9 / CECL standards Methodology We setup stylized calculations for a credit portfolio with the following main parameters and assumptions: A portfolio of 200 commercial loans of uniform size and credit quality Maturities extending from one to five annual periods A stylized transition matrix producing typical multiyear credit curves Correlation between assets typical for a single business sector and geography portfolio Focusing on PnL estimates one year forward, with PnL being impacted both by Realized Losses (defaults) and Provision variability (both positive and negative).

### Version 0.2 of the Open Risk API incorporates the standardized EBA portfolio data templates

Extending the Open Risk API to include the EBA Portfolio Data Templates The Open Risk API provides a mechanism to integrate arbitrary collections of risk data and risk modelling resources in the context of assessing and managing financial risk. It is based on two key technologies of the modern Web, RESTful architectures and Semantic Data. OpenNPL, the credit portfolio management platfrom we launched recently fully integrates the latest versions of the Open Risk API.

### Credit Portfolio Management in the IFRS 9 / CECL and Stress Testing Era

Credit Portfolio Management in the IFRS 9 / CECL and Stress Testing Era The post-crisis world presents portfolio managers with the significant challenge to asimilate in day-to-day management the variety of conceptual frameworks now simultaneously applicable in the assessment of portfolio credit risk: The first major strand is the widespread application of regulatory stress testing methodologies in the estimation of regulatory risk capital requirements The second major strand is the introduction of new accounting standards (IFRS 9 / CECL) for the measurement and disclosure of expected credit losses While both Regulatory Stress Testing and IFRS 9 / CECL accounting require investment in analytic capabilities and provide unique new insights, both are aimed at satisfying evolving prudential or investor disclosure requirements.