Description: Adaptive Risk Management harnesses social intelligence to identify emerging risks. We have entered an age of disruption where exponential technologies are transforming every industry. The ability to pivot in a rapidly evolving ecosystem is essential. Centralized “predict and control” paradigms will increasingly fail as complex interactions drive phase transitions. Successful organizations will harness social intelligence to “sense and respond” to giant waves of change. Maps amplify intelligence to help us navigate challenging terrain. Maps play a central role in all command centres, enabling rapid risk identification with a shared visual language. Interactive financial network maps allow analysts to explore and diagnose systemic fragilities, and mitigate critical vulnerabilities. Dynamic financial maps can also build visual intuition to detect escalating risk patterns. After observing early warning signals, analysts can apply network analytics to estimate likely second order effects. This allows organizations to proactively manage emerging risk before tipping points are crossed.

Description: When companies engage in risk management activities, they can be seen as modifying their distributions of future outcomes. Often, this takes the form of trading off a sure cost for a decrease in some potential risk of loss. Companies may carry out these activities with several goals in mind, such as reduction in earnings volatility or preservation of capital. This paper will demonstrate a method for evaluating possible strategies by dividing the effects on costs and risks into three tranches: earnings, impact and estate. The tranches can be associated with different interests of the various stakeholders. This trifurcation analysis can help to explain the risk-reward trade-offs of different risk treatment alternatives and can aid in risk-related decisionmaking.

Description: Increasing uncertainties and volatility in financial as well as real goods markets increasingly reveal that controlling systems based on deterministic and pseudo-exact values are insufficiently eligible to manage the business activities. This raises the question how management systems can be modified to generate the adequate management impulses in volatile periods. Risk management deals from identifying, evaluating and aggregating chances and risks, which again determine the potential fluctuation range of relevant performance indicators. Everyday corporate life shows that risk management is considered important; but the corresponding processes to identify, evaluate and report chances and risks are seldom part of established decision criteria. This “paradox” lets assume that risks are managed in various differing and unsystematic ways. The combination of traditional controlling methods and risk management is not primarily a methodological challenge. The behavior of the whole organization, practiced over a long-year period, has to be transferred into a new corporate culture of transparent dealing with chances and risks. This paper describes the necessary change management process, which has to come along with necessary methodological modifications.

Description: We develop a model based on causal mortality in order to better understand inequalities in life expectancy across socioeconomic circumstances.

Description: The costly, time-consuming and complicated process of enterprise risk management (ERM) can be improved in many companies and made less tedious for managers by using reasonable data and templates obtained from peer group entities. The models used to calculate economic capital (EC) often underestimate its value because they do not consider decision-maker perception about risk. We assume here that managers, as the decision-makers, have appropriate business understanding and they can provide substantial information about risk characteristics regarding all business processes. Therefore we are focused, in this paper, on collecting data from managers across the different businesses to derive the appropriate knowledge about risky events, the importance of particular types of risk, the relationship between the risk outcomes and the level of risk control in a particular industry. We conclude that the collected data has a high potential for use as a benc hmarking reference and analysis for improving ERM models for individual businesses.

Description: Increased attention was paid to regulatory capital with the global financial crisis in 2008. Whilst companies may not have the incentives to retain a large amount of capital in the absence of regulatory capital requirements, overcapitalized entities can have drawback such as its impact on competitiveness. There are other weaknesses in the regulatory capital model such as its limitation in facilitating risk-based decisions as regulatory capital does not necessarily reflect the economic reality and risks an entity faces. Nonetheless, there are ways for regulators and/or companies to handle the weaknesses in the regulatory capital model. For instance, granularity can be introduced in determining regulatory capital. Economic capital can be used to encourage entities to implement risk management controls and facilitate risk-based business decisions (e.g., risk-adjusted performance assessment and risk-based capital allocation). Ultimately, hav ing effective risk management and risk-based capital determination are ways to prevent company failures and bankruptcies.

Description: Risk management and capital budgeting are two critical components of the corporate decision process. They often need to be considered jointly at the corporate level because of their natural interaction through the dependent risk exposures and other synergetic relationships within an intricate corporate structure in a dynamic business environment. . This paper develops an integrated framework that aligns these two important corporate strategies across business divisions to optimize the streamlined enterprise strategic goal in a multi-period setting. The proposed integrated framework can serve as a practical guideline for corporate executives to optimally coordinate capital budgeting and risk management at the enterprise level.

Description: This paper provides a description of a system using statistical spatial methods for measuring, analysis, and managing ERM losses. An example of its application to a delinquency rate in a residential mortgage portfolio analysis demonstrates how this methodology can help decrease a company’s exposure in high-risk areas and increase exposure in low-risk areas.

Description: We describe our process of hand-curation of centenarian pedigrees and software that we developed for the automated construction of pedigrees.

Description: Adaptive Risk Management harnesses social intelligence to identify emerging risks. We have entered an age of disruption where exponential technologies are transforming every industry. The ability to pivot in a rapidly evolving ecosystem is essential. Centralized “predict and control” paradigms will increasingly fail as complex interactions drive phase transitions. Successful organizations will harness social intelligence to “sense and respond” to giant waves of change. Maps amplify intelligence to help us navigate challenging terrain. Maps play a central role in all command centres, enabling rapid risk identification with a shared visual language. Interactive financial network maps allow analysts to explore and diagnose systemic fragilities, and mitigate critical vulnerabilities. Dynamic financial maps can also build visual intuition to detect escalating risk patterns. After observing early warning signals, analysts can apply network analytics to estimate likely second order effects. This allows organizations to proactively manage emerging risk before tipping points are crossed.