Operational risk management, modelling and capital requirements determination

OpCapital Analytics is a set of best of breed tools for operational risk management through quantification and modelling. It also permits the determination of operational risk capital requirements (Basel`s Pillar 2 and ICAAP and Internal Models and ORSA under Solvency II). Operational Risk Capital Analytics have received 10 awards by Risk.Net and InsuranceERM including Best operational risk solution, Op risk scenario product of the year, Best stress testing product and Best risk analytics tool (contact The Analytics Boutique for a demo and commercial details).

In addition, Chartis Research’s Enterprise GRC Solutions, 2019 classified The Analytics Boutique as:

  • Best of Enterprise Solutions in GRC Analytics Quadrant
  • Best of Breed on the Quadrant of OpRisk & Conduct Risk
  • Best of Enterprise Solutions in Model Risk Governance Quadrant

In addition, OpCapital Analytics methods (including operational risk capital modelling) are widely published and our publications recognised by top practitioners (see Actuary Magazine and RiskBook).

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The Analytics Boutique differential value proposition using OpCapital Analytics in GRC is breaking the “bubble chart” paradigm by strong quantification and analytics. By the “bubble chart” paradigm we mean that GRC output should no longer be limited to nice dashboards of GRC basic metrics (i.e., loss collection, indicators, risk evaluations…). These GRC basic metrics are hard to understand by senior and upper management and too frequently end up ignored and not effectively integrated into daily management due to their unclear monetary value. Using quantification techniques (distribution models, forecasting models, correlations, Monte Carlo…), our solution transforms GRC basic metrics into GRC monetary value metrics (i.e., how much does risk cost, how much can be saved, NPV of risk mitigation investments, capital requirements…). Monetary metrics are the language senior and upper management understand and use daily. GRC metrics translated into monetary value can easily be integrated with the standard risk management processes: planning, budgeting, resource allocation, and so on.

Hence, the influence of the operational risk management function into the organization is maximised.

OpCapital Analytics can be used for the following purposes:

  • Collect scenario analysis
  • Determine the money value of Risk and the NPV of mitigation actions
  • Collect loss events and KRIs
  • Manage mitigation plans and build their business case to justify required investments and insurance premiums
  • ICAAP and ORSA Operational Risk stable and robust capital estimates
  • Comply with ISO31000
  • Risk and control mapping
Scenario Analysis
Scenario analysis is a fundamental tool for modelling. OpCapital provides the following benefits:
  • Great efficiency and strong model governance: workflow, approvals, complete audit trail, workshop invites, automatic reminders, answer aggregation, report generation and more
  • Cognitive bias mitigation permitting a high-quality operational risk capital modelling: Group thinking, herding, authority bias, confirmation bias and others
  • Scenario planning and identification of most relevant scenarios for operational risk capital
  • Priority scenario detailed development
  • Scenario support data in questionnaire including case studies, to support experts when answering
  • Possibility to answer form in workshop or, alternatively, answering each expert individually and aggregating individual answers into a single answer per scenario
  • Evaluation of risk scenarios under any number of dimensions: ie, financial, reputational and operative
  • Scenario scientific validation of qualitative estimates of risk using Structured Expert Judgment
  • On-the-fly Monte Carlo simulation for estimating loss profile by the first line of defence
  • Audit trail of origin and all transformations in the scenario down to the simulation report
  • Extensive model regulatory approval reporting
Operational Risk Capital Models Scenario Analysis
Action plans and mitigation analysis
Action plans are critical for the management of operational risk and for obtaining a forward-looking estimate of operational risk capital. OpCapital Analytics provides the following benefits:
  • Action plan management determining responsibles, reminders and alerts
  • Simulation of action plan NPV for building business case for required investments
  • Simulation of the impact of insurance policies permitting the detailed modelling of insurance features and calculating the NPV of insurance policies and their impact in operational risk capital
  • Combination of insurance with action plans to determine the total mitigation in the risk profile and resulting NPV and corresponding impact in operational risk capital
Pre and post mitigation action loss distributions and operational risk capital
Operational Risk Capital Models Action plans and mitigation analysis
Sensitivity analysis on scenario loss estimates
A robust operational risk capital calculation requires a solid validation of assumptions which can be done by sensitivity analysis. Sensitivity analysis provides the impact on operational risk capital of changes in the underlying modelling assumptions. OpCapital Analytics permits the following:
  • Automatically generates pre-defined sensitivity shocks for the scenario loss estimates
  • Permits scenario ad-hoc sensitivity shocks
  • Allows sensitivity analysis on distribution law assumptions
  • Automatically calculates sensitivity analysis operational risk capital results
  • Sensitivity analysis operational risk capital report
Operational Risk Capital Models Sensitivity analysis on scenario loss estimates
Global capital aggregation
The calculation of operational risk capital requires the consideration of many ORCs (operational risk categories) which requires multiple phases for their aggregation into a single figure of operational risk capital. OpCapital Analytics helps in the following way:
  • In case of very large number of scenarios simulation, it is possible to aggregate scenarios using flexible aggregation paths in multiple steps
  • Each aggregation node permits the definition of a specific correlation matrix
  • Total capital is allocated down to all steps providing allocated capital to scenarios
Operational Risk Capital Models Global capital aggregation
Bayesian network modelling of scenario analysis
Operational risk capital is largely determined by the impact of a reduced number of highly damaging scenarios which deserve a more detailed attention and modelling. OpCapital provides the means to model scenarios using Bayesian Networks:
  • Most damaging scenarios or those in need of expensive mitigation plans can be modelled using our Bayesian networks user friendly and highly flexible capabilities
  • Results are integrated into the hybrid model together with the rest of scenarios or even LDA models
  • Bayesian network provides the pre-and post-mitigation analysis and the mitigation plan NPV, including insurance impact, in consistency with the rest of modelled scenarios
  • Bayesian networks approach is integrated with the rest of the workflow and governance framework: audit trail, permissions, aggregation and overwrite phases, reporting, etc.
Operational Risk Capital Models Bayesian network modelling of scenario analysis
Loss and Indicators Collection
Loss data and indicators are a valuable input into operational risk capital determination. OpCapital provides the following features:
  • Customizable loss and indicators collection forms
  • Unlimited number of collection processes for losses and any other indicators
  • Customised indicator (KRI, KPI, KCI...) collection workflows with reminders and alerts for faulty collection
  • Customization of indicator collection frequency and responsibles
Loss data analysis
Analysis of operational risk data is a fundamental step in the modelling of operational risk capital permitting the definition of the correct modelling sample. OpCapital provides the following features among many others:
  • Multiple incident management modules activated simultaneously
  • Multiple visual representation and analysis
  • Audit trail of all transformations, filters, etc., introduced in data
  • Audit trail of the data origin, filters and transformations which goes down to simulation report Frequency projections
Operational Risk Capital Models Loss data analysis
Distribution fitting
The modelling of probability distributions is needed to interpolate and extrapolate out of the observed losses and to calculate the loss percentiles that determine operational risk capital. OpCapital provides the following features among many others:
  • Operational Risk Capital Models Distribution fitting24 basic severity and frequency distributions
  • Mixtures of any combination of basic distributions
  • Simulations, fitting and comparison of all fitted distributions
  • User defined distributions via XML
  • Fitting via MLE, Robust Least Squares, Probability Weighted Least Squares, Probability Weighted and Moments approach
  • Distribution split in 3 segments (low losses, medium losses and tail losses)
  • GoF: AD, KS, Kramer von Mises, etc.
  • GoF visual: PP and QQ plots, histogram and CDF
  • Non parametric distributions
Extreme Value Theory
Operational risk capital is mostly influenced by loss distribution tails which are better modelled using Extreme Value Theory (EVT). OpCapital provides the following EVT analysis:
  • DEdH analysis
  • Tail parameter stability analysis by threshold
  • Tail plot
  • Mean Excess Plot
  • Hill estimator
  • HKKP-Hill
  • GoF analysis by threshold
Operational Risk Capital Models Extreme Value Theory
Comprehensive hybrid model
A complete modelling of operational risk capital capital requires the accommodation of multiple loss types characterised by their loss frequency and criticality of the loss: high frequency and low frequency ORCs are worth modelling in detail using Bayesian networks; other ORCs are not worth the detailed operational risk capital modelling effort. OpCapital Analytics hybrid model accepts all cases for a comprehensive and adapted to the ORC characteristics and complete OpRisk modelling:
  • Internal Loss Data for high frequency risk categories
  • External Loss Data complementing tails
  • Scenario analysis based on direct loss estimates
  • Scenario analysis modelled in detailed using Bayesian networks, for those most critical scenarios
Monte Carlo simulation
Finally, the operational risk capital figures are generated using Monte Carlo simulation. OpCapital provides multiple features including the followings: Operational Risk Capital Models Monte Carlo simulation
  • Copula parameters fitting: Gaussian and t-student
  • OpRisk correlations calculation and stress testing
  • Nested copulas for the aggregation of multiple scenarios, data cells, etc.
  • Automatic stop when stability of results is reached
  • Audit trail report
  • Batch process for multiples consecutive runs with different parameterizations
  • Simulation in multiple currencies for multinational institutions
  • Allocation of operational risk capital to its drivers
Insurance modelling
Insurance policies may or may not have a significant impact into the operational risk capital figures. OpCapital provides the means to model in detail the clauses of the insurance policy and test their real impact into the operational risk capital and expected loss, including:
  • Modeling deductibles
  • Modeling maximum coverage
  • Applying deductibles and coverage for total losses or/and individual incidents
  • Calculation of pre and after insurance operational risk capital figures
  • Number of incidents covered by the insurance policy
  • Other
Operational Risk Capital Models Insurance modelling
Operational loss forecasting, budgeting and stress testing
ICAAP and ORSA operational risk capital final figures take stress testing analysis as an input. OpCapital provides the means for creating operational risk stress testing models including the following;
  • Time series loss forecasting models (ARIMA, ARIMAX and others)
  • Possibility to build operational loss forecasting models based on macroeconomic data or any other indicator (KRI, KPI, KCI...)
  • Projectionof operational losses under macroeconomic scenarios or under indicators scenarios, i.e., loss budgeting in case of attrition growing 20%
  • Strong times series model out of sample validation features
  • Modelling archive
  • Extensiveregulatory validation reporting
Backtesting of operational risk
Operational risk capital needs to be backtested for validation purposes. OpCapital provides the means for backtesting:
  • QQ and PP plotscomparingnew losseswithdistributionsusedin capital estimates
  • GoF statisticscomparingnew losseswithdistributionsusedin capital estimates
Operational Risk Capital Models Backtesting of operational risk
Reporting in MS Office, PDF and RT
Most time-consuming tasks in operational risk capital modelling is the reporting to internal validation and regulators. OpCapital permits the generation all these reports effortlessly:
  • All graphics, tables and analytics have the corresponding report: Incident data analysis, Distribution fitting, EVT, etc. that were used into the operational risk capital model construction
  • Operational risk capital model regulatory approval report
Formal functionalities
The maintenance, validation and documentation of the operational risk capital model is greatly enhanced when supported by formal functionalities such as the following: Operational Risk Capital Models Formal functionalities
  • Audit trail
  • User control
  • Interface with GRC software to import events, scenarios, user rights, etc.
  • Interface via ODBC drive
  • Handling of multiple currencies
  • Parallel computing for simulation
  • One click model replication
  • Modelling journal
  • Modelling archive
  • Operational risk capital results archive

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