Qualitative operational risk software -development of a software tool for determining the root of operational risk

This article shows software that allows determining the statistical behavior of qualitative data originating surveys previously transformed with a Likert’s scale to quantitative data. The main intention is offer to users a useful tool to know statistics' characteristics and forecasts of financial risks in a fast and simple way. Additionally,this paper presents the definition of operational risk. On the other hand, the article explains different techniques to do surveys with a Likert’s scale (Avila, 2008) to know expert’s opinion with the transformation of qualitative data to quantitative data. In addition, this paper will show how is very easy to distinguish an expert’s opinion related to risk, but when users have a lot of surveys and matrices is very difficult to obtain results because is necessary to compare common data. On the other hand, statistical value representative must be extracted from common data to get weight of each risk. In the end, this article exposes the development of “Qualitative Operational Risk Software” or QORS by its acronym, which has been designed to determine the root of risks in organizations and its value at operational risk OpVaR (Jorion, 2008; Chernobai et al, 2008) when input data comes from expert’s opinion and their associated matrices.

A methodology proposal to obtain operational parameter forecasts and operational risk assessment in container terminals

Las terminales de contenedores son sistemas complejos en los que un elevado número de actores económicos interactúan para ofrecer servicios de alta calidad bajo una estricta planificación y objetivos económicos. Las conocidas como "terminales de nueva generación" están diseñadas para prestar servicio a los mega-buques, que requieren tasas de productividad que alcanzan los 300 movimientos/ hora. Estas terminales han de satisfacer altos estándares dado que la competitividad entre terminales es elevada. Asegurar la fiabilidad de las planificaciones del atraque es clave para atraer clientes, así como reducir al mínimo el tiempo que el buque permanece en el puerto. La planificación de las operaciones es más compleja que antaño, y las tolerancias para posibles errores, menores. En este contexto, las interrupciones operativas deben reducirse al mínimo. Las principales causas de dichas perturbaciones operacionales, y por lo tanto de incertidumbre, se identifican y caracterizan en esta investigación. Existen una serie de factores que al interactuar con la infraestructura y/o las operaciones desencadenan modos de fallo o parada operativa. Los primeros pueden derivar no solo en retrasos en el servicio sino que además puede tener efectos colaterales sobre la reputación de la terminal, o incluso gasto de tiempo de gestión, todo lo cual supone un impacto para la terminal. En el futuro inmediato, la monitorización de las variables operativas presenta gran potencial de cara a mejorar cualitativamente la gestión de las operaciones y los modelos de planificación de las terminales, cuyo nivel de automatización va en aumento. La combinación del criterio experto con instrumentos que proporcionen datos a corto y largo plazo es fundamental para el desarrollo de herramientas que ayuden en la toma de decisiones, ya que de este modo estarán adaptadas a las auténticas condiciones climáticas y operativas que existen en cada emplazamiento. Para el corto plazo se propone una metodología con la que obtener predicciones de parámetros operativos en terminales de contenedores. Adicionalmente se ha desarrollado un caso de estudio en el que se aplica el modelo propuesto para obtener predicciones de la productividad del buque. Este trabajo se ha basado íntegramente en datos proporcionados por una terminal semi-automatizada española. Por otro lado, se analiza cómo gestionar, evaluar y mitigar el efecto de las interrupciones operativas a largo plazo a través de la evaluación del riesgo, una forma interesante de evaluar el effecto que eventos inciertos pero probables pueden generar sobre la productividad a largo plazo de la terminal. Además se propone una definición de riesgo operativo junto con una discusión de los términos que representan con mayor fidelidad la naturaleza de las actividades y finalmente, se proporcionan directrices para gestionar los resultados obtenidos. Container terminals are complex systems where a large number of factors and stakeholders interact to provide high-quality services under rigid planning schedules and economic objectives. The socalled next generation terminals are conceived to serve the new mega-vessels, which are demanding productivity rates up to 300 moves/hour. These terminals need to satisfy high standards because competition among terminals is fierce. Ensuring reliability in berth scheduling is key to attract clients, as well as to reduce at a minimum the time that vessels stay the port. Because of the aforementioned, operations planning is becoming more complex, and the tolerances for errors are smaller. In this context, operational disturbances must be reduced at a minimum. The main sources of operational disruptions and thus, of uncertainty, are identified and characterized in this study. External drivers interact with the infrastructure and/or the activities resulting in failure or stoppage modes. The later may derive not only in operational delays but in collateral and reputation damage or loss of time (especially management times), all what implies an impact for the terminal. In the near future, the monitoring of operational variables has great potential to make a qualitative improvement in the operations management and planning models of terminals that use increasing levels of automation. The combination of expert criteria with instruments that provide short- and long-run data is fundamental for the development of tools to guide decision-making, since they will be adapted to the real climatic and operational conditions that exist on site. For the short-term a method to obtain operational parameter forecasts in container terminals. To this end, a case study is presented, in which forecasts of vessel performance are obtained. This research has been entirely been based on data gathered from a semi-automated container terminal from Spain. In the other hand it is analyzed how to manage, evaluate and mitigate disruptions in the long-term by means of the risk assessment, an interesting approach to evaluate the effect of uncertain but likely events on the long-term throughput of the terminal. In addition, a definition for operational risk evaluation in port facilities is proposed along with a discussion of the terms that better represent the nature of the activities involved and finally, guidelines to manage the results obtained are provided.

Strategic and operational risk in an international collaboration agency: a knowledge management solution

The International Cooperation Agency (identified in this article as IDEA) working in Colombia is one of the most important in Colombian society with programs that support gender rights, human rights, justice and peace, scholarships, aboriginal population, youth, afro descendants population, economic development in communities, and environmental development. The identified problem is based on the diversified offer of services, collaboration and social intervention which requires diverse groups of people with multiple agendas, ways to support their mandates, disciplines, and professional competences. Knowledge creation and the growth and sustainability of the organization can be in danger because of a silo culture and the resulting reduced leverage of the separate group capabilities. Organizational memory is generally formed by the tacit knowledge of the organization members, given the value of accumulated experience that this kind of social work implies. Its loss is therefore a strategic and operational risk when most problem interventions rely on direct work in the socio-economic field and living real experiences with communities. The knowledge management solution presented in this article starts first, with the identification of the people and groups concerned and the creation of a knowledge map as a means to strengthen the ties between organizational members; second, by introducing a content management system designed to support the documentation process and knowledge sharing process; and third, introducing a methodology for the adaptation of a Balanced Scorecard based on the knowledge management processes. These three main steps lead to a knowledge management “solution” that has been implemented in the organization, comprising three components: a knowledge management system, training support and promotion of cultural change.

Analysis of operational risk of banks – catastrophe modelling

Nowadays financial institutions due to regulation and internal motivations care more intensively on their risks. Besides previously dominating market and credit risk new trend is to handle operational risk systematically. Operational risk is the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. First we show the basic features of operational risk and its modelling and regulatory approaches, and after we will analyse operational risk in an own developed simulation model framework. Our approach is based on the analysis of latent risk process instead of manifest risk process, which widely popular in risk literature. In our model the latent risk process is a stochastic risk process, so called Ornstein- Uhlenbeck process, which is a mean reversion process. In the model framework we define catastrophe as breach of a critical barrier by the process. We analyse the distributions of catastrophe frequency, severity and first time to hit, not only for single process, but for dual process as well. Based on our first results we could not falsify the Poisson feature of frequency, and long tail feature of severity. Distribution of “first time to hit” requires more sophisticated analysis. At the end of paper we examine advantages of simulation based forecasting, and finally we concluding with the possible, further research directions to be done in the future.

Qualitative operational value at risk for an electric utility based on the guidelines of the basel committee

This paper presents a model for determining value at operational risk ?OpVaR? in electric utilities, with the aim to confirm the versatility of the Bank for International Settlements (BIS) proposals. The model intends to open a new methodological approach in risk management, paying special attention to underlying operational sources of risk.

Trust-Level Risk Evaluation and Risk Control Guidance in the NHS East of England

In recent years, the healthcare sector has adopted the use of operational risk assessment tools to help understand the systems issues that lead to patient safety incidents. But although these problem-focused tools have improved the ability of healthcare organizations to identify hazards, they have not translated into measurable improvements in patient safety. One possible reason for this is a lack of support for the solution-focused process of risk control. This article describes a content analysis of the risk management strategies, policies, and procedures at all acute (i.e., hospital), mental health, and ambulance trusts (health service organizations) in the East of England area of the British National Health Service. The primary goal was to determine what organizational-level guidance exists to support risk control practice. A secondary goal was to examine the risk evaluation guidance provided by these trusts. With regard to risk control, we found an almost complete lack of useful guidance to promote good practice. With regard to risk evaluation, the trusts relied exclusively on risk matrices. A number of weaknesses were found in the use of this tool, especially related to the guidance for scoring an event's likelihood. We make a number of recommendations to address these concerns. The guidance assessed provides insufficient support for risk control and risk evaluation. This may present a significant barrier to the success of risk management approaches in improving patient safety. © 2013 Society for Risk Analysis.

A physical approach on flood risk vulnerability of buildings

The design of efficient hydrological risk mitigation strategies and their subsequent implementation relies on a careful vulnerability analysis of the elements exposed. Recently, extensive research efforts were undertaken to develop and refine empirical relationships linking the structural vulnerability of buildings to the impact forces of the hazard processes. These empirical vulnerability functions allow estimating the expected direct losses as a result of the hazard scenario based on spatially explicit representation of the process patterns and the elements at risk classified into defined typological categories. However, due to the underlying empiricism of such vulnerability functions, the physics of the damage-generating mechanisms for a well-defined element at risk with its peculiar geometry and structural characteristics remain unveiled, and, as such, the applicability of the empirical approach for planning hazard-proof residential buildings is limited. Therefore, we propose a conceptual assessment scheme to close this gap. This assessment scheme encompasses distinct analytical steps: modelling (a) the process intensity, (b) the impact on the element at risk exposed and (c) the physical response of the building envelope. Furthermore, these results provide the input data for the subsequent damage evaluation and economic damage valuation. This dynamic assessment supports all relevant planning activities with respect to a minimisation of losses, and can be implemented in the operational risk assessment procedure.

Development of a 3-Dimensional Mathematical Collision Risk Model Based on Recorded Aircraft Trajectories to Estimate the Safety Level in High Density En-Route Airspaces

Como en todos los medios de transporte, la seguridad en los viajes en avión es de primordial importancia. Con los aumentos de tráfico aéreo previstos en Europa para la próxima década, es evidente que el riesgo de accidentes necesita ser evaluado y monitorizado cuidadosamente de forma continúa. La Tesis presente tiene como objetivo el desarrollo de un modelo de riesgo de colisión exhaustivo como método para evaluar el nivel de seguridad en ruta del espacio aéreo europeo, considerando todos los factores de influencia. La mayor limitación en el desarrollo de metodologías y herramientas de monitorización adecuadas para evaluar el nivel de seguridad en espacios de ruta europeos, donde los controladores aéreos monitorizan el tráfico aéreo mediante la vigilancia radar y proporcionan instrucciones tácticas a las aeronaves, reside en la estimación del riesgo operacional. Hoy en día, la estimación del riesgo operacional está basada normalmente en reportes de incidentes proporcionados por el proveedor de servicios de navegación aérea (ANSP). Esta Tesis propone un nuevo e innovador enfoque para evaluar el nivel de seguridad basado exclusivamente en el procesamiento y análisis trazas radar. La metodología propuesta ha sido diseñada para complementar la información recogida en las bases de datos de accidentes e incidentes, mediante la provisión de información robusta de los factores de tráfico aéreo y métricas de seguridad inferidas del análisis automático en profundidad de todos los eventos de proximidad. La metodología 3-D CRM se ha implementado en un prototipo desarrollado en MATLAB © para analizar automáticamente las trazas radar y planes de vuelo registrados por los Sistemas de Procesamiento de Datos Radar (RDP) e identificar y analizar todos los eventos de proximidad (conflictos, conflictos potenciales y colisiones potenciales) en un periodo de tiempo y volumen del espacio aéreo. Actualmente, el prototipo 3-D CRM está siendo adaptado e integrado en la herramienta de monitorización de prestaciones de Aena (PERSEO) para complementar las bases de accidentes e incidentes ATM y mejorar la monitorización y proporcionar evidencias de los niveles de seguridad. ABSTRACT As with all forms of transport, the safety of air travel is of paramount importance. With the projected increases in European air traffic in the next decade and beyond, it is clear that the risk of accidents needs to be assessed and carefully monitored on a continuing basis. The present thesis is aimed at the development of a comprehensive collision risk model as a method of assessing the European en-route risk, due to all causes and across all dimensions within the airspace. The major constraint in developing appropriate monitoring methodologies and tools to assess the level of safety in en-route airspaces where controllers monitor air traffic by means of radar surveillance and provide aircraft with tactical instructions lies in the estimation of the operational risk. The operational risk estimate normally relies on incident reports provided by the air navigation service providers (ANSPs). This thesis proposes a new and innovative approach to assessing aircraft safety level based exclusively upon the process and analysis of radar tracks. The proposed methodology has been designed to complement the information collected in the accident and incident databases, thereby providing robust information on air traffic factors and safety metrics inferred from the in depth assessment of proximate events. The 3-D CRM methodology is implemented in a prototype tool in MATLAB © in order to automatically analyze recorded aircraft tracks and flight plan data from the Radar Data Processing systems (RDP) and identify and analyze all proximate events (conflicts, potential conflicts and potential collisions) within a time span and a given volume of airspace. Currently, the 3D-CRM prototype is been adapted and integrated in AENA’S Performance Monitoring Tool (PERSEO) to complement the information provided by the ATM accident and incident databases and to enhance monitoring and providing evidence of levels of safety.

Managing project risk using combined analytic hierarchy process and risk map

The main purpose of the study is to develop an integrated framework for managing project risks by analyzing risk across project, work package and activity levels, and developing responses. Design/methodology/approach: The study first reviews the literature of various contemporary risk management frameworks in order to identify gaps in project risk management knowledge. Then it develops a conceptual risk management framework using combined analytic hierarchy process (AHP) and risk map for managing project risks. The proposed framework has then been applied to a 1500 km oil pipeline construction project in India in order to demonstrate its effectiveness. The concerned project stakeholders were involved through focus group discussions for applying the proposed risk management framework in the project under study. Findings: The combined AHP and risk map approach is very effective to manage project risks across project, work package and activity levels. The risk factors in project level are caused because of external forces such as business environment (e.g. customers, competitors, technological development, politics, socioeconomic environment). The risk factors in work package and activity levels are operational in nature and created due to internal causes such as lack of material and labor productivity, implementation issues, team ineffectiveness, etc. Practical implications: The suggested model can be applied to any complex project and helps manage risk throughout the project life cycle. Originality/value: Both business and operational risks constitute project risks. In one hand, the conventional project risk management frameworks emphasize on managing business risks and often ignore operational risks. On the other hand, the studies that deal with operational risk often do not link them with business risks. However, they need to be addressed in an integrated way as there are a few risks that affect only the specific level. Hence, this study bridges the gaps. © 2010 Elsevier B.V. All rights reserved.

Early Warning System Potential for Single Sourcing Risk Mitigation

Part 17: Risk Analysis

Inferential, non-parametric statistics to assess quality of probabilistic forecast systems

Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.