Collaboration in Risk Markets

Collaboration in Risk Markets

Scott Rummler (laserthread.com, USA)
DOI: 10.4018/978-1-60566-727-0.ch014

Abstract

Collaboration can be an effective tool for managing risk. A structured environment for sharing critical risk information can improve decision-making. The business environment currently in place makes it difficult to collaborate, due to complex and overlapping regulatory schemes. In addition, the computing framework used in risk-based sectors is not integrated, resulting in a patchwork of ad-hoc systems that make it difficult to collaborate in an efficient or transparent way. This chapter will present an example of a business framework in which organizations collaborate by trading risk-based products. This arrangement mitigates risk by allocating it to those organizations that can best handle it. A computing framework utilizing Web Services is presented that can help facilitate these types of transactions. Several challenges recur in knowledge management of risk, including trust, information filtering, connecting information (‘connecting the dots’), and fluid information exchange. Examples from the insurance and financial industries are presented. Knowledge management of risk information can be facilitated by the development of an Ontology used to describe Web Semantics. A user interface for knowledge management that incorporates collaborative mapping, filtering, and community discussion is presented. Collaboration is being used more frequently to handle core business processes (deep collaboration) as opposed to generic communications such as Wikis (shallow collaboration). A structured environment for collaboration is risk environments can improve security, transparency, and effectiveness. This type of environment might have been used to mitigate the impact risk-based problems such as the current financial emergency. In conclusion, it is posited that a new type of product can emerge which incorporates the social-computing value of risk.
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Collaborative Systems For Risk Environments

Organizational Framework

In order for collaboration to be practical in this context, various ways of looking at risk market organization should be considered. There are precedents for collaboration in risk management.

In the area of emission trading, the government assigns emission allowances for atmospheric pollutants produced in the U.S. on a yearly basis. Polluters that reduce their emissions can sell their pollution credits. Companies collaborate toward the most effective solution by buying and selling pollution credits. This is intended to encourage companies to make money by adopting new non-polluting processes. Those that do not will contribute to the cost of finding better alternatives.

In energy trading, power generators and users are never sure exactly how much power they will need in a given time frame, so they arrange for production based on estimates. They may buy or sell power to which they have already committed. This scheme will allow all parties to achieve the lowest marginal cost for power. The implementation of such a scheme is a large potential target of opportunity for the U.S. economy.

A related use is in the area of alternative fuels. If controls are used to create longer-term risk products, which can be fluidly traded, there is the potential for attracting a new large capital hedge market for investing in alternative energy, which is currently a major impediment to its development (Davis, 2008).

These approaches may be characterized by three layers of organization, which would form the basis for the core data model (Figure 1):

  • A control layer, in which products are given time or quantity limits. An example is an insurance policy, which is purchased for one year, and is then placed into the risk market.

  • A risk market (‘broker mediated layer’), in which prices, purchases, and sales of risk products are maintained, and matches between buyers and sellers are found;

  • A collaborative layer, in which groups are free to form and to buy and sell risk products amongst themselves.

    Figure 1.

    Core Layers of Collaboration

This scheme has the benefit of clarifying the underlying data model for the risk control environment. Each layer has clear entities in the form of organizations, roles, objects, and transactions (see Figure 2).

Figure 2.

High Level Data Model for Risk Collaboration

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