Risk is something that we all love to shun. Businesses are no exception to this
phenomenon—indeed they are more agitated by it, for their profit generation ability will be adversely impacted by it. To be successful, the output of a business must always be more than the input since it is this positive difference between the output and the input that creates ‘value’. Indeed, value creation is the primary objective of any enterprise. Enterprises create value by interacting with external environment—their customers, suppliers, technology, competition, markets, government, etc.—via the internal environment employees, process, innovation, etc. Any unanticipated change in these two environments generates risk. This risk, if left unmanaged, is potential-enough to impact the ‘value’ creation for owners. Therefore, businesses always keep their eyes and ears open for identifying the risks that they are exposed to—deviations from the expected business happenings—and manage them with least delay so that the anticipated cash flows are realized.

Risk is after all an enterprise-wide issue: it has strategic, operational, financial and technological implications. Intriguingly, insurance companies trade on risk for generating their profits. Insurance companies are thus more concerned about risk management. Driven by increased concern for the return on the capital, stability and growth of future earnings, and shareholder’s value, insurance firms have of late been attempting to include the diverse perceptions of all stakeholders on what constitutes a risk to a company’s business in their risk management practices. Thus emerged enterprise-wide risk management, which can provide comprehensive identification of organization-wide risk; develop a systematic analysis of the organization’s risks; identify the risk-retention capacity of the organization; enable an organization to combine like-risks for evaluation; and ultimately promote better strategic decision making leading to optimization of overall risk profile of the firm.

It involves bringing together of all data at one location whereby one can apply a full range of risk management techniques and create measures that represent the cumulative knowledge of the market held by the organization. Such centralized data makes identification of both global and organizational risks in terms of frequency, severity and public perception possible. It assists in statistical modeling and time series analysis to estimate the financial risks faced by an organization more accurately. It also facilitates evaluation of assets of the firm in terms of their contribution to enterprise-wide risk. Finally, it enables risk managers and senior management to communicate risk measures across the enterprise and ensure that everyone stay focused on risk management vision without of course losing sight of the granular details.

Against this backdrop, the authors, Heng Yik Seik, Jifeng Yu and Jared Li, of the first paper, “Enterprise Risk Management in Financial Crisis”, have assessed the efficacy of ERM in enabling property and causality insurers to withstand the recent financial crisis by analyzing a sample of publicly traded US insurance companies. They found that all ERM programs are not that beneficial: well-designed ERM programs outperformed the market with lower stock volatility and higher profit margins, while companies with poor ERM programs ended up with worst operation ratio.

Moving away from enterprise-wide risk, we have Jim Gustafsson talking about risk in terms of known-knowns; known-unknowns and unknown-unknowns in his paper, “Rule of Thumb for Optimal Number of Runs in Monte Carlo Simulations”. The author argues that the known-unknowns in the overall risk perception of an organization can, to a great extent, be accounted for and managed strategically by diversification, etc. The whole problem emanates, the author argues, from unknown-unknown risk, for we are not aware of it, and worse still, ‘we do not know that we are not aware of it’. Thus, it is almost impossible to mitigate such risks, but the author argues that by understanding the known-unknown risks better one can reduce the uncertainty associated with the unknown-unknowns. With this argument, the author has worked on identifying the optimal number of Monte Carlo simulations required to develop a formula that converts the known-unknown risk into a known-known fact and also presented the formula.

Moving on to non-life insurance, we have the authors, Amir T Payandeh Najafabadi and Atefeh Kanani Dizaji, of the next paper, “A Dynamic Bonus-Malus System for the Automobile Insurance: A Case Study in Iranian Third Party Liability”, who, by employing the hidden Markov models along with the ordinal logistic regression, introduced a dynamic Bonus-Malus System (BMS) so as to take the policyholders’ personal information into consideration to predict the exact level of each policyholder and the same has been used in an Iranian automobile insurance company and found that the dynamic BMS does not retain the transition rule.

In the next paper, “A Study About Policy Holders of GIC, Sivakasi”, its authors, J Vimal Priyan and V Karthihaiselvi, have made an attempt to assess the relationship between annual income of the policyholders and the duration of the policies taken by the insured by collecting data from policyholders through a structured interview. The authors opine that it is the quality of service rendered by the insurance companies which alone can attract consumers towards a insurance company.

In the last paper, “AIG Crisis: Impact on Insurance Business with Special Reference to China, Japan and India”, its author, A V Narsimha Rao, has made an attempt to map the risks that the AIG entertained to make profits and in the process suffering massive losses—all out of its ignorance about the embedded risks in credit default swaps.

-- GRK Murty
Consulting Editor