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Main Page
* [[Kraljic Model]] (New Entry) * [https://www.openriskacademy.com/course/view.php?id=73 Input-Output Model Interactivities]

19 KB (2,522 words) - 14:31, 9 May 2024
Model Risk
...can lead to a variety of financial and / or reputational [[Loss]] events. Model risk is generally considered to be a type of [[Operational Risk]]. ...ed to the assessment of risk, which is a common use in financial services, model risk can also be seen as a ''second-order'' risk (a contributing factor to

7 KB (1,077 words) - 19:50, 11 March 2024
Accuracy Ratio
...P)) of the model under consideration versus the "perfectly" discriminating model. (See also: [[Receiver Operating Characteristic]]) ...ex | Gini Coefficient]] yet it should not be confused with the more common use of that term to measure inequality.

3 KB (382 words) - 12:52, 16 September 2021
Algorithm
== Relevance for Model Performance == ...y constitute a significant component of the computational budget of a risk model in terms of computer memory requirements or computational power requiremen

2 KB (276 words) - 18:01, 5 December 2023
AMA Models
The AMA framework must include the use of four data elements: ...re is large discretion on how to combine the elements into a coherent risk model. Some common approaches:

2 KB (238 words) - 14:34, 19 November 2019
Backtesting
...ison of observed outcomes with expected outcomes derived from the use of a model. ...development or validation process. Backtesting compares the latest set of model predictions against actual realizations, with the validation sample being f

3 KB (371 words) - 23:40, 9 March 2021
Credit Bureau Scoring
...stem (i.e., the scoring system can use credit bureau scores as part of the model attribute set) ...riable(s) of the overall internal rating, there is a risk that an internal model may not consider all relevant information.<ref>ECB guide to internal models

4 KB (644 words) - 13:33, 19 November 2018
Data Cleansing
...ce a set that is suitable for use, e.g., in [[Model Development]] and/or [[Model Validation]]. ...a cleansing may hide issues with the dataset that would prevent building a model that is fit for purpose. For example engineering a less representative samp

2 KB (217 words) - 21:01, 11 September 2020
Default Definition
...mply with this requirement, institutions should ensure that when they make use of external data or pooled data they have a complete understanding of the d ...fault definition in [[External Risk Data]] used to support building a risk model may differ (see ECB TRIM section)

8 KB (1,109 words) - 16:07, 22 February 2021
Economic Capital Models
...odels''' are a class of [[Portfolio]] level or [[Enterprise]] level [[Risk Model | risk models]] which typically aggregate within and across the risk types The overall structure of an economic capital model mirrors the recognized and capitalized regulatory [[Risk Type | risk types]

1 KB (169 words) - 15:02, 23 June 2020
Model Validation
...practices and organizational arrangements supporting a rigorous (audited) model development and validation cycle. Model Validation ensures that developed models offer good presentation of the var

1 KB (145 words) - 11:03, 15 September 2021
Model Inventory
...mation that is in use by a firm or organization. Sometimes also called a ''Model Map''. ...rall [[Model Governance]], with a key objective identifying and managing [[Model Risk]].

939 bytes (133 words) - 14:35, 19 November 2019
Model Documentation
...ns, derivations, tests and other analyses that support the use of a [[Risk Model]] for a given purpose. ...g good [[Model Governance]] and is an indispensable tool for [[Independent Model Validation]].

2 KB (243 words) - 12:04, 31 March 2021
Model Parameters
...h reference to data or be subject to explicit policy decisions. Important model parameters may become integral to the risk management process as they have Examples of model parameters include

893 bytes (116 words) - 18:42, 28 January 2020
Model Usage
...ed into business actions. It is the context into a certian model is put to use. ...any other model adjustment mechanisms that may intermediate and modify the model output before final action.

1 KB (161 words) - 19:43, 11 March 2024
Out of Sample Testing
...esting''' is the label of one of the most powerful quantitative means of [[Model Validation]] in the pre-implementation phase. ...on separating the total data set and restricting model development to the use of a sub-sample only. The sub-sample can be restricted in the time-dimensio

526 bytes (69 words) - 19:42, 27 January 2020
Roll Rates
* Estimating a roll rate matrix constitutes a simple type of a credit [[Risk Model]] in that it allows projecting likely outcomes over the future periods. Com ...nal Transition Matrix]] are useful to mitigate this weakness (and hidden [[Model Assumptions]])

4 KB (658 words) - 12:17, 7 September 2020
Visualization
...ps between variables (e.g., scatter plots, Q-Q plots, histograms), overall model performance (power curves) etc. There is large variety of possible [[Visual ...information with the unintentional or intentional abuse of the technique (use of wrong scales, misleading areas or volumes

912 bytes (109 words) - 13:29, 6 July 2020
Basel II Advanced IRB Capital Model
...wn empirical model to quantify required capital for credit risk. Banks can use this approach only subject to approval from their local regulators. Under A-IRB banks are supposed to use their own quantitative models to estimate PD ([[probability of default]]),

7 KB (1,023 words) - 12:30, 26 March 2021
Risk Limit
...g to distinguish limit systems that utilize additional (potentially [[Risk Model]] dependent parameters) from those that are based more directly on observab There is a large collection of potential pitfalls associated with the use of risk limits. We can group them roughly in two categories: immediate issu

6 KB (943 words) - 14:11, 4 October 2021
Model Taxonomy
'''Model Taxonomy''' is a classification and documentation system for the (financial A model taxonomy might be the organizing principle behind a [[Model Inventory]] system. It is related to be is distinct from the [[Risk Taxonom

5 KB (679 words) - 19:39, 11 March 2024
Model Outputs
...rical Variable | categorical variables]] that encapsulate the outcome of a model calculation or "run". The significance of such outcomes lies in the manner There is a wide variety of possible model outputs:

1 KB (153 words) - 11:34, 20 November 2019
Risk Taxonomy
...hest level decomposition (and a distinctive future of the taxonomy) is the use of ''contracting'' as key differentiator of risk types ...l) perspective places less weight to day-to-day operational and [[Business Model Risk]]

8 KB (1,110 words) - 16:01, 16 January 2023
COPYING
Risk Manual Template (Version 1.0 - May 2014). Use this text when generating new articles In case of synonyms use a parenthesis to indicated alternatives: (Also: AlternateName1, AlternateNa

2 KB (288 words) - 20:52, 19 October 2014
Risk Data Standards
...expertise to develop specifications to support the collection, sharing and use of structured data for data reporting and analysis. ...w.eba.europa.eu/regulation-and-policy/supervisory-reporting EBA Data Point Model] (Based on XBRL)

10 KB (1,432 words) - 17:18, 5 December 2023
Risk Data
* Organizations typically use diverse sources of risk data, which formally can be organized using a [[Ris ...[[Abstract Risk Model]] into a concrete [[Model Implementation]] via the [[Model Specification]] process.

2 KB (221 words) - 00:50, 20 November 2019
IFRS 9 Modeling Resources
...lp us maintain this list up-to-date by submitting additions / corrections (Use info at openrisk eu). Submissions should have a publicly accessible URL (li |Use of changes in the risk of a default occurring over the next 12 months when

24 KB (3,113 words) - 16:52, 1 September 2020
Credit Scoring Models
'''The credit scoring model collection focuses on the classic one period credit assessment / classifica * credit migration models that besides default aim to model an entire [[:Category:Credit_Rating_System | credit rating system]] and ass

11 KB (1,491 words) - 15:41, 7 March 2023
Entry Types
...tions of links to external resources. Collection pages will typically make use of tables to create an easily readable list. As an example the list of [[Fi === Model Descriptions ===

3 KB (397 words) - 23:34, 8 March 2021
Representativeness
...n attribute of [[Risk Data]], relevant in the context of developing [[Risk Model | risk models]]. It denotes the degree to which the historical data set off The concept is linked to, but is more loosely use in practise, than the [[wikipedia:Representativeness Heuristic | representa

477 bytes (66 words) - 13:57, 4 August 2019
IFRS 9 Glossary
...ssions and (where applicable) mathematical definitions / formulae. You can use the [[:Category:IFRS 9 | category tree]] to browse these articles directly. ...e first day of the first reporting period following the change in business model that results in an entity reclassifying financial assets

10 KB (1,464 words) - 11:38, 25 September 2020
Restructuring
...ing in the [[Loan Tape]], which constitutes a direct input to the sampling model.

4 KB (520 words) - 11:13, 31 March 2021
IFRS 9
...ring]] systems. While banks currently using the [[Advanced IRB Credit Risk Model | advanced internal ratings-based approach]] (IRB) to establish their capit If the asset passes the contractual cash flows test, the business model assessment determines how the instrument is classified. If the instrument

8 KB (1,123 words) - 13:25, 25 October 2019
Financial Guarantee
* It should include provisions on the use of ratings of third parties that provide contractual support to more than o ...uaranteed by a third party that is not in the range of application of a PD model and the guarantee fulfils all requirements for credit risk mitigation (CRM)

6 KB (895 words) - 14:41, 6 September 2020
Lifetime PD
* Whether the model estimation based on market data or historical default data ...th respect to SICR, when making the assessment, the reporting entity shall use the change in the risk of a default occurring over the expected life of the

2 KB (319 words) - 19:10, 21 December 2020
Risk Model
'''Risk Model''' denotes any quantitative (mathematical), qualitative or hybrid approach ...s still essential in quantitative risk models, at all stages of the [[Risk Model Lifecycle]]

2 KB (334 words) - 14:34, 20 November 2019
Open Source Risk Management Software
...list of projects (both big and small) that adopt the open source licensing model in the development of software relevant for risk management. The scope of t ...lp us maintain this list up-to-date by submitting additions / corrections (Use info at openrisk eu). Submissions should have a publicly accessible URL (li

4 KB (551 words) - 13:27, 28 June 2020
Garbage In Garbage Out
...l data ("Garbage In") and as a consequence produce nonsensical, unusable [[Model Outputs]] outcomes ("Garbage Out"). * Extensive use of [[Data Proxies]] due to lack of more relevant / representative data

2 KB (351 words) - 11:30, 27 June 2020
Five Cs Of Credit Analysis
* the intended purpose of the loan ([[Use of Funds]]) (consumption, investment etc.) ...jectively (in [[Expert Based Models]]) or quantitatively in [[Quantitative Model | quantitative / statistical models]].

9 KB (1,373 words) - 14:11, 29 March 2021
Economic Scenario Generator
An '''Economic Scenario Generator''' (ESG) refers to a mathematical model (and its computer implementation) that simulates possible future paths of e .... Such auxiliary specific models are typically implemented via [[Satellite Model | satellite models]].

5 KB (698 words) - 17:17, 30 October 2019
Collateral Valuation
* Automated Valuation Model * Use of consensual vs. non-consensual foreclosure (historic and forward looking)

2 KB (323 words) - 18:40, 24 January 2021
IT Data Integrity Risk
...T data life cycle (i.e. designing the data architecture, building the data model and/or data dictionaries, verifying data inputs, controlling data extractio * Use of faulty external data.

5 KB (777 words) - 19:01, 4 March 2020
Expected Life
...bly estimate the expected life of a financial instrument, the entity shall use the remaining contractual term (Maturity) of the financial instrument. * Use of the expected life of an instrument for ECL purposes differentiates the I

3 KB (392 words) - 13:13, 1 December 2022
Var-Covar Model
'''Var-Covar''' (Variance-Coveriance) model denotes a simple methodology that allows the [[Risk Aggregation]] of distin ...gation, e.g, to aggregate [[Market Risk]] in the [[Trading Book]]. Another use is to apply Var-Covar at the top level of risk aggregation, for example com

2 KB (274 words) - 13:00, 16 April 2021
SREP
...all the risks in their business but also to encourage banks to develop and use better risk management techniques in monitoring and managing their risks. F * Analysis of the viability of the [[Business Model]] of the bank or banking group and analysis of the sustainability of its [[

8 KB (1,117 words) - 15:00, 5 February 2020
Concentration Risk
* [[Revenue Risk]], e.g. from excess reliance on a particular [[Business Model]] ...bination of off-site monitoring and on-site examination. Some supervisors use off-site monitoring only, and some supervisors consider input from suppleme

4 KB (601 words) - 11:01, 24 September 2020
How to Build a Credit Scorecard
...n a business context. The approach follows the general lifecycle of [[Risk Model]] development adapted to the specific requirements of [[Credit Risk]]. ...specific to credit scorecards but are common across wider ranges of [[Risk Model Lifecycle | risk models]]

5 KB (622 words) - 18:41, 18 November 2020
Credit Scorecard Business Requirements
* The business use of the scorecard, e.g. [[Risk Acceptance]] of new clients on the basis of a ...rformance characteristics]] for accepting the deployment and/or continuing use of the scorecard

2 KB (310 words) - 21:01, 11 September 2020
Privacy Policy
Cookies : We use cookies to help identify and track visitors in their usage of the website, Log files :We use IP addresses to analyse trends, administer the site, track usage, and gathe

3 KB (521 words) - 16:00, 16 May 2022
Credit Portfolio Model
'''Credit Portfolio Model''' denotes any mathematical framework that aims to emulate the evolution of == Model Types ==

3 KB (429 words) - 14:55, 23 June 2020
The Zen of Modeling
* An undocumented risk model is only a computer program * A risk model that cannot be programmed is only a concept

1 KB (214 words) - 12:53, 30 May 2017
EXIOBASE
...cribed as “a global (multi-regional) Environmentally Extended Supply-and-Use / Input-Output database”. ...ion related to agricultural and settlement activities for 15 types of land use.

7 KB (1,018 words) - 19:04, 30 April 2024
Risk Event
.... The required detail of that description is open-ended and depends on the use case and context. ...may require specialized additional attibutes and an underlying conceptual model for a meaningful description of the event. As an example the description of

3 KB (517 words) - 15:08, 10 August 2021
EBA 2018 EU-Wide Stress Test
...Stress Test | "bottom-up"]] in the sense that banks are requested to make use of their models but are subject to a number of [[Conservative Constraints i ...ation of impairments and the translation to available capital requires the use of statistical methods and includes the following main steps:

4 KB (678 words) - 14:10, 17 February 2021
IFRS 9 Model Validation
'''IFRS 9 Model Validation''' refers to the policies and procedures that must be in place t Guidance on IFRS 9 Model Validation is provided in EBA's Guidance Paper<ref>EBA/GL/2017/06</ref> and

6 KB (893 words) - 12:53, 16 September 2021
NPL Risk Factors
...fast high NPL portfolios should be reduced. These stakeholders will often use national or international benchmarks and peer analysis. * NPL risk is not normal part of the business model of banks and there is significantly less developed framework for understand

4 KB (608 words) - 16:57, 1 September 2020
Targeted Review of Internal Models
...and appropriateness of approved [[Pillar I]] internal models permitted for use by significant institutions when calculating own funds requirements Reduction of unwarranted variability in RWA as it relates to internal model outcomes, taking into account

1 KB (168 words) - 11:42, 16 April 2020
Default Rate
...pool and additionally for the type of exposures covered by the relevant PD model as well as for any relevant calibration segment. ...observation period, but which were within the range of application of the model under consideration (‘missing

11 KB (1,612 words) - 14:40, 6 September 2020
Credit Rating System
* A set of [[Credit Rating Model | credit rating models]] * Credit markets make extensive use of various forms of explicit [[Financial Guarantee]] contracts or implicit

3 KB (358 words) - 16:06, 22 February 2021
Expected Loss Best Estimate
...imating LGD on non-defaulted exposures as they are in fact part of the LGD model * When estimating ELBE institutions should use the same RDS and the same methods for computing the long-run average LGD in

4 KB (570 words) - 09:59, 14 May 2021
Margin of Conservatism
...ed with the selection of methods and quantitative methods underpinning the model. For the purposes of applying the MoC during the phases of model development, estimation and calibration institutions should consider:

9 KB (1,337 words) - 00:44, 14 November 2019
EBA 2018 Stress Test Definitions
...rtant component of the LGD estimations. In doing so, banks are required to model cure rates when estimating PDs and LGDs, and report them in the template CS ...aired Financial Asset]] in appendix A of the IFRS 9 regulation. Banks will use their own interpretation of definition of S3 for the starting point of the

17 KB (2,890 words) - 23:45, 4 May 2018
IFRS 9 versus IRB Models
...and Regulatory [[Pillar I | Internal Rating Based]] frameworks require the use of quantitative [[Credit Risk]] estimates. This entry summarizes their rel ! Aspect !! Internal Ratings-Based Model !! IFRS 9 Model

2 KB (250 words) - 14:14, 29 March 2021
Risk Metric
...management disciplines such as [[Market Risk]] or [[Credit Risk]] tend to use wider and mathematically more complicated risk metrics. ...hybrid. Quantitative metrics may involve a more or less complicated [[Risk Model]].

1 KB (193 words) - 13:55, 16 April 2021
Forward-Looking Scenario
...he context of [[IFRS 9]] and [[Regulatory Stress Testing]]. It denotes the use of defined narratives ([[Scenario | scenarios]]) about the temporal develop ...actors]] underpinning the scenario are used in conjuction with [[Satellite Model | satellite models]] to assess the impact on the organization, portfolio et

655 bytes (85 words) - 12:30, 9 October 2019
LGD In-Default
...imating LGD on non-defaulted exposures as they are in fact part of the LGD model. ...t does not allow an accurate assessment of risk. Where an institution does use a constant charge, it should justify this. It should demonstrate that the c

3 KB (422 words) - 10:16, 14 May 2021
Best Practices in Credit Portfolio Management
** Management of Inherent Model Risk * Embedding and use in Business Operations

12 KB (1,494 words) - 20:11, 11 March 2024
Downturn LGD
...ars (see paragraph 123(a) above) for each facility grade or pool that they use. When the LGD estimates result from combining different components (for exa ...LGD estimates (by facility grade or pool) or, if applicable, estimates of model components (including MoC) obtained by the institution are lower than those

6 KB (861 words) - 18:45, 7 November 2019
Loss Given Default Models
== Model Usage == ...anges are identified by splitting the full range of application of the LGD model into different parts on the basis of potential drivers for risk differentia

7 KB (1,048 words) - 12:27, 16 September 2021
FX Lending Risk
...ture the full impact of FX risk in credit performance, it is unlikely that use of such FX sensitive credit parameters with one of the capitalization optio ...oss rates. For transition rates, the impact should be based on [[Satellite Model | satellite models]] that link the macroeconomic scenario to the transition

3 KB (512 words) - 13:04, 16 April 2021
Threshold Models
== Model Variations == * '''The Role of thresholds in model construction'''. For a large class of models, thresholds are ''inputs'' an

6 KB (1,061 words) - 19:01, 4 September 2020
External Credit Assessment Institution
...ratings to financial and non-financial companies under the subscriber-pays model. ...Rating Platform. Consult www.Moodys.com for current information & terms of use.

14 KB (2,064 words) - 22:31, 27 September 2021
External Risk Data
...ures to obligors or facilities grades or pools, the data used to build the model must be representative of the population of the institution’s actual obli ...sis and/or qualitative argumentation) that the information gained from the use of the external data outweighs any drawbacks stemming from the deficiencies

4 KB (542 words) - 21:01, 11 September 2020
Vendor Risk Model
...ny risk quantification systems (including data and algorithms) that are in use by a firm / organization without having been developed in-house ...ons should ensure in such cases that all relevant internal information for model development and parameter calibration is taken into account.

1 KB (165 words) - 14:31, 19 November 2019
Probability of Default Model
A '''Probability of Default Model''' (PD Model) is any formal quantification framework that enables the calculation of a [ * at a PD model level when assigning exposures to different ranking/scoring methods;

6 KB (863 words) - 17:49, 11 October 2019
Credit Rating Philosophy
* the model should perform under different economic conditions. ...ignments or risk parameters estimates with caution, especially when making use of rating information or default experience obtained

5 KB (700 words) - 10:27, 22 February 2021
Shadow Rating
* when an internal model of a bank or other credit risk bearing firm targets external ratings provid A shadow rating model<ref>ECB guide to internal models - Credit Risk, Sep 2018</ref> (SRM) is an

4 KB (539 words) - 19:21, 8 February 2021
Catalog of Loss Given Default Models
...academic priority but to provide sufficient documentation for each listed model == LGD Model Classification ==

6 KB (778 words) - 12:39, 16 September 2021
Long-run Loss Given Default
...thin the LGD grade. Institutions should demonstrate that the approach they use does not distort the actual observed loss. ...n the realised LGDs before the application of this floor in the process of model development for the purpose of risk differentiation<ref>Paragraph 6.3.2.4 o

9 KB (1,396 words) - 18:07, 7 November 2019
Risk Distribution
...racteristics and these tend to be very important in determining fitness of use for particular risk applications ...e nature of the realized risk usually dictates which type is meaningful to use

10 KB (1,033 words) - 13:56, 18 October 2021
Credit Scoring with Python
...e functionality of various existing packages with the various steps of the model development / validation process. * models that use [[Financial Market Information]] such as observed [[Credit Spread | credit

8 KB (1,121 words) - 13:48, 21 September 2020
ESMA Leasing Exposures Table
...Region fields, e.g. 2013 for NUTS3 2013. All geographic region fields must use the same classification consistently for each underlying exposure and acros Use the same currency denomination as that used for this underlying exposure.

26 KB (3,745 words) - 20:58, 12 February 2019
ESMA Automobile Exposures Table
...Region fields, e.g. 2013 for NUTS3 2013. All geographic region fields must use the same classification consistently for each underlying exposure and acros ...odel|ESMA Automobile.Exposures.Model]] || ALPHANUM-100 || Name of the car model.

27 KB (3,842 words) - 21:04, 12 February 2019
Equity Correlation Matrix
A '''Equity Correlation Matrix''' denotes a ''measure'' (or a ''model'') of ''dependency'' between different corporate entities that is inferred ...of investment portfolios (usually as component of a larger set of data and model assumptions)

11 KB (1,744 words) - 12:13, 10 June 2021
Mean-Variance Model
...odels that underpin [[wikipedia:Modern portfolio theory]]. A mean-variance model is built on a limited set of parameters namely, mean, standard deviation an ...able return projections, have nice mathematical properties and are easy to use, interpret and understand.

1 KB (134 words) - 22:31, 25 March 2019
Asset Correlation Matrix
...ation Matrix]] used in the context of a certain type of [[Credit Portfolio Model | credit portfolio models]] ...the liability structure of the firm. The underlying theory supporting the use of an asset matrix as input to estimating [[Default Correlation]] is that o

1 KB (195 words) - 15:19, 3 April 2019
Business Model
A '''Business Model''' is the blueprint of how the resources, providers, clients, partners etc ...tionships and processes between external and internal actors. The business model describes the rationale of how an organization creates, delivers, and captu

4 KB (538 words) - 15:41, 11 May 2023
Calibration Segment
...y identified ''subset'' of exposures under the scope of application of the model which is jointly calibrated. <ref>EBA Guidelines on PD estimation, LGD est ...or LGD model are jointly calibrated, the whole scope of application of the model is considered one calibration segment

1 KB (195 words) - 00:11, 24 May 2019
Human Judgement
...'' is used in the assignment of exposures to the grades or pools of a risk model Institutions may use human judgement in the application of risk model in the following cases:

5 KB (744 words) - 14:41, 6 September 2020
Roll Rate versus Rating Migration Matrices
...data and interpretations that may introduce significant subjectivity and [[Model Risk]] (but also - in principle - allow more forward looking risk assessmen

1 KB (150 words) - 16:09, 15 June 2019
SME Credit Scorecard
* Quantitative Scorecards ([[Credit Scoring Models]]) that use exclusively or primarily quantitative inputs and algorithmic processing ([[ #the linear probability model

3 KB (412 words) - 12:59, 7 September 2020
How to Build an SME Credit Scorecard
...| performance characteristics]] for accepting the deployment or continuing use of the scorecard ...gulatory bodies involved. This may place constraints on data requirements, model explainability etc.

9 KB (1,305 words) - 17:41, 8 September 2020
SME Credit Risk Literature
...cular purpose. All quantitative methodologies are subject to substantial [[Model Risk]] * Use the feedback functionality to request adding or removing a reference

8 KB (1,007 words) - 13:00, 7 September 2020
Expert Scorecards
While any linear quantitative model shares some commonalities with a scorecard it is best to keep separate term The main reason scorecards see widespread use is because the technique allows non-quantitative staff to develop a risk an

2 KB (241 words) - 19:55, 11 March 2024
Logistic Regression Credit Scorecard
...e a type of [[Credit Scoring Models | credit scoring model]] in widespread use to support [[Credit Decisioning]] in various [[Consumer Finance]] and [[SME This entry serves as the [[Abstract Risk Model]] specification of a Logistic Regression Scorecard

3 KB (417 words) - 21:01, 11 September 2020
Integrated Assessment Model
An '''Integrated Assessment Model''' (IAM) is any model that attempts to integrate knowledge from two or more domains of expertise ...ions along a number of dimensions.<ref>TCDF 2018, Technical Supplement The Use of Scenario Analysis in Disclosure of Climate-Related Risks and Opportuniti

837 bytes (116 words) - 12:07, 22 July 2019
Risk Model Ontology
...any framework that aims to represent and categorize knowledge about [[Risk Model | risk models]] using semantic information technologies. This article documents a Risk Model Ontology (Description of a Model, DOAM)

4 KB (617 words) - 15:52, 20 November 2019
Open Source Financial Software
...projects that adopt the [https://spdx.org/licenses/ open source licensing model] in the development of financial / insurance software. ...is achieved with the predominant use of open source software the business model is termed [[Open Source Finance]]

4 KB (544 words) - 13:11, 12 October 2021
Exploratory Data Analysis
...t of [[Quantitative Risk Management]] as one of the first steps towards [[Model Development]] . Due to the reliance on data and sensitivity to [[Data Quali * Support the selection of appropriate [[Risk Model | models]]

4 KB (561 words) - 17:34, 5 December 2023
Credit Risk Modelling with Python
...rganized along two dimensions: risk model use (which typically implies the model type) and borrower/product type. ! Use Case !! Retail Unsecured !! Retail Secured !!

2 KB (95 words) - 12:39, 2 August 2019