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Quantitative Risk Management

There is an old management adage that states “you can’t manage what you don’t measure.” An organization’s ability to quantify risk is becoming increasingly important. Stakeholders are demanding it. Regulators are seeking clarity for how much capital is being held, executives are searching for optimal allocation of it, business’ are inquiring for justification about control expenditures, and project managers want assurance about meeting budgets and timelines, and so on.

The ability to analyze risk data and extrapolate potential future effects (both positive and negative) can have tremendous benefits. The more detailed and reliable the analysis, the better and more informed management decisions can be made. As risk data becomes more readily available and of higher quality, organizations can use quantitative techniques to reduce guesswork. They can gain insight into potential risks, estimate exposures, determine control weaknesses, assist with the viability of new products/services, evaluate cross-selling and up-selling opportunities, evaluate cash flow variances, and improve or streamline operations. Each of these activities have a risk component to them. Enumerating these and evaluating them (e.g., through stress tests, modeling, trending, metric evaluation, etc.) enables a quicker response to take advantage of opportunities and address potentially adverse impacts before they occur.

QUANTITATIVE RISK MANAGEMENT (QRM) WITH THE BWISE® RISK MANAGEMENT SOFTWARE SOLUTION

BWise offers modeling capabilities as part of its Risk Management software solution. Users can seamlessly incorporate data from purchased BWise software solutions or other data sources. The solution offers an extensive range of probability distributions, correlation structures, and time series capabilities. Built in visual interfaces help to interpret and explain the model. Additionally, the software solution offers specialized tools to address and simplify unique modeling needs such as extreme events, fat tails, and aggregate distributions.

BWise QRM provides a comprehensive, configurable risk analysis reporting tool. Some of these reporting features include:

  • Histograms
  • Ascending and descending cumulative plots
  • Box and Pareto plots
  • Tornado, scatter, and spider plots 
  • Trend plots 
  • Results filtering and statistical summaries including the ability to review data from each simulation

KEEPING TRACK OF THE ENTIRE RISK MODEL

Keeping track of how a model changes, the different scenarios that have been used, and simulation results is challenging. Managers can run and store analyses of different scenarios directly in BWise without accessing the model. This enables the organization to keep a full and reliable audit trail including all relevant model variables.

EXAMPLE USES OF QUANTITATIVE RISK MANAGEMENT

Cash Flow at Risk (CFaR)

Cash flow is one of the most, if not the most, important business driver. Management needs strong cash flows prognoses to substantiate business decisions like making or delaying investments, reinvesting in the business, cutting costs, or reengineering operations. Variability in factors such as sales, currency fluctuations, operational costs, vendor viability, and product and service pricing play a significant role in being able to effectively extrapolate cash flows. BWise QRM makes it possible to create sophisticated cash flow risk models, which can provide invaluable management information and affirm business decisions.

Value at Risk (VaR) and Other Modeling Techniques

Mature and forward thinking risk management organizations continue to use quantitative techniques to run their businesses well. For example, large, complex financial institutions must evaluate their risk exposures to determine the amount of capital needed to absorb unanticipated losses. BWise QRM has the tools needed to perform these sophisticated analyses; including a wide range of correlation tools (copulas), univariate and multivariate time series like ARCH and GARCH, calculations of VaR and CVaR at any confidence level, aggregate modeling tools like fast Fourier transform, de Pril, Panjer, and many others.

Project Risk Management

Many projects fail to meet their budget, milestones, and deadline because of an insufficient evaluation of the project’ variables (e.g., risks, and uncertainties) during planning. BWise QRM can bring clarity to the mercurial nature of the project. For example, QRM has built in templates that can help to codify project cost and schedule variances by identifying the correlation between task durations and risk events. 

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