Risk-mitigation techniques: from (re-)insurance to alternative risk transfer

Insurance risks knowledge is becoming essential for both financial stability and social security purposes, moreover in a country with a very low insurance education like Italy. In insurance industry, Solvency II requirements introduced new issues for actuarial risk management in non-life insurance, challenging the market to have a consciousness of its own risk profile, and also investigating the sensitivity of the solvency ratio depending on the insurance risks and technical results on either a short-term and medium-term perspective. For this aim, in the present thesis, firstly a partial internal model for underwriting risk is developed for multi-line non-life insurers. Specifically, the risk-mitigation and profitability impacts of traditional reinsurance in the underwriting risk model are introduced, and a global framework for a feasible application of this model consistent with a medium-term analysis is provided. Reinsurance have to be considered in the assessment of Non-Life insurers risk profile, with particular regard to the Solvency II Underwriting Risk because of its impact on business and risk strategy. Risk mitigation techniques appear as a key driver of Non-Life insurance business as they can change risk profile over either the short-term or medium-term perspective. They impact the technical result of the year in such a way that it is important to assess how reinsurance strategies decrease the volatility, reducing the capital requirements, but, on the other hand, they also change the mean of distributions in different ways according to the price for risk requested by reinsurers. At the same time, risk mitigation also influences Non-Life insurance management actions as it can improve business strategy and capital allocation (also in potential capital recovery plans). Furthermore, the analysis a medium-term capital requirement would ask insurers to have more capital than in a one-year time horizon, and in this framework risk mitigation effects linked to reinsurance strategies must be assessed on either risk/return perspective trade-off. On the other hand, (re)insurance can play an active role in mitigating physical risks, and in particular natural catastrophe risks. In this context, as well as in natural disasters, Alternative Risk Transfer (ART) is becoming a new significant actuarial and capital management tool for insurers and, potentially, for government measures in recovery actions of economic and social losses in case of natural disasters. Catastrophe Bonds are insurance-linked securities that have been increasingly used as an alternative to traditional reinsurance for two decades. In exchange for a Spread over to the risk-free rate, protection is provided against stated perils that could impact the insured portfolio. A broad literature has flourished to investigate what are the features that significantly influence the Spread, in addition to the portfolio’s expected loss. Almost all proposed models are based on multivariate linear regression, that has provided satisfactory predictive performance as well as easily interpretability. This thesis also explores the use of Machine Learning models in modeling the determinant at issuances, contrasting both their predictive performance and their interpretability with respect to traditional models. An overview of the economics of CAT bonds, on current literature and on the statistical methodologies will be provided also. Aim of this Thesis is to provide a solid framework of insurance risk transfer for both pure underwriting and catastrophe risks, investigating risk transfer practices from traditional to alternative and most innovative technique. In these fields, firstly a suitable risk model is used in order to describe main impacts on insurance business model. Then, the main innovative alternative risk transfer for catastrophe risks are illustrated and CAT Bond will be adequately described, investigating main pricing models using a machine learning approach. Finally, a possible Italian CAT Bond issuance is provided in order to investigate an integrated solution with a traditional reinsurance underlying an alternative risk transfer in order to achieve a public-private partnership to natural catastrophe

AUTOMATED ANALYSIS OF NATURAL-LANGUAGE REQUIREMENTS USING NATURAL LANGUAGE PROCESSING

Natural Language (NL) is arguably the most common vehicle for specifying requirements. This dissertation devises automated assistance for some important tasks that requirements engineers need to perform in order to structure, manage, and elaborate NL requirements in a sound and effective manner. The key enabling technology underlying the work in this dissertation is Natural Language Processing (NLP). All the solutions presented herein have been developed and empirically evaluated in close collaboration with industrial partners. The dissertation addresses four different facets of requirements analysis: • Checking conformance to templates. Requirements templates are an effective tool for improving the structure and quality of NL requirements statements. When templates are used for specifying the requirements, an important quality assurance task is to ensure that the requirements conform to the intended templates. We develop an automated solution for checking the conformance of requirements to templates. • Extraction of glossary terms. Requirements glossaries (dictionaries) improve the understandability of requirements, and mitigate vagueness and ambiguity. We develop an auto- mated solution for supporting requirements analysts in the selection of glossary terms and their related terms. • Extraction of domain models. By providing a precise representation of the main concepts in a software project and the relationships between these concepts, a domain model serves as an important artifact for systematic requirements elaboration. We propose an automated approach for domain model extraction from requirements. The extraction rules in our approach encompass both the rules already described in the literature as well as a number of important extensions developed in this dissertation. • Identifying the impact of requirements changes. Uncontrolled change in requirements presents a major risk to the success of software projects. We address two different dimen- sions of requirements change analysis in this dissertation: First, we develop an automated approach for predicting how a change to one requirement impacts other requirements. Next, we consider the propagation of change from requirements to design. To this end, we develop an automated approach for predicting how the design of a system is impacted by changes made to the requirements

Crop Insurance and Climate Change: Balancing structure and flexibility to improve on-farm management of climate risk

EXECUTIVE SUMMARY: INTRODUCTION Crop insurance has become an important tool for managing economic and environmental risk in the agricultural sector, and one of the largest sources of Federal subsidies to agricultural producers. This research examines the near- and long-term risks to agricultural producers, and seeks to identify and evaluate potential policy opportunities within the federal crop insurance program to improve the climate adaptation capacity of insured farms. The crop insurance program contains several structural barriers to sustainable, adaptive management practices, including a lack of soil and water conservation requirements common to other farm support programs (remedied in the Agricultural Act of 2014), and stringent planting date requirements which discourage farmers from using cover crops to protect their soil from erosion and enhance fertility, as well as diversify their farms (both economically and biologically) and increase climate resiliency. POLICY RECOMMENDATIONS 1. Reinstate conservation compliance requirements for eligibility to receive federal subsidies towards crop insurance coverage (successfully passed in the Agricultural Act of 2014). 2. Provide farmers who plant cover crops with an additional “buffer” period after their policy’s final planting date to allow appropriate termination of the cover crop without jeopardizing the insurance coverage on their primary crop. ANALYSIS & METHODS To evaluate the economic impacts of requiring conservation compliance for eligibility to receive crop insurance subsidies, I constructed a cost benefit analysis at the national scale, including cash flows for the economy as a whole, the government, and affected farmers. My analysis focuses on the marginal impact of the program, quantifying only the marginal costs and benefits of implementing the program on farms which are not currently participating in any other Farm Bill programs requiring conservation compliance, and which will be coming under the compliance requirement for the first time due to their use of subsidized crop insurance. This eliminates all farms which would be subject to the requirement whether or not it was added to the crop insurance program, and thus more accurately quantifies the impact of the policy change within the context of other interrelated farm support programs. Due to the lack of data from the field regarding the dynamics of planting date restrictions and cover cropping decisions, I could not construct a national-scale cost benefit analysis to evaluate my second policy recommendation. I instead created a farm-scale cost benefit model to compare the performance of a commodity mono-crop with a dual, cover crop and commodity crop system. The model takes into account the unique economic, social, and biological attributes of the farm using yield, acreage, crop selection, planting dates, management practices, and insurance parameters to produce estimates of the costs and benefits at the farm level. RESULTS The results of my analysis show that conservation compliance, even under the most conservative scenario, provides a net benefit to farmers and to the economy as a whole for a comparatively modest initial investment on the part of farmers and the government. In my moderately conservative cost benefit analysis scenario, reinstating the conservation compliance requirements in association with crop insurance provides an incremental net benefit of at least $4,411 per acre in present value terms, with over$780 per acre of those benefits accruing to the farmer. The cover crop analysis did not provide any generalizable results, however it does suggest that a buffer period within the planting date restrictions for farmers growing cover crops may help mitigate the risk of cover crops interfering with the profitability of farmers’ primary commodity crop, and thus remove one of the barriers to adoption. I recommend a pilot test of this policy change, with rigorous measurement and evaluation of the impacts on farm revenue, insurance and subsidy payments, and environmental outcomes. CONCLUSIONS With impending near- and long-term threats of climate change, the crop insurance program should balance the need for rigid management requirements to ensure an appropriate baseline level of risk mitigation and management with the flexibility to allow farmers to experiment with new management practices to find what works best in their new climate context. The benefits of the conservation compliance requirement vastly outweigh the costs, and provide a cost-effective mechanism for improving adaptive capacity on already vulnerable agricultural lands. While the planting date buffer period is a promising mechanism for increasing the use of cover crops and improving farmers’ capacity to develop new adaptive risk management strategies at the local level, additional research and field testing is needed to determine the impact of relaxing the constraint on actual adoption rates in the field

An improved requirement change management model for agile software development

Business requirements for software development projects are volatile and continuously need improvement. Hence, popularity of Agile methodology increases as it welcomes requirement changes during the Agile Software Development (ASD). However, existing models merely focus on change of functional requirements that are not adequate to achieve software sustainability and support change requirement processes. Therefore, this study proposes an improved Agile Requirement Change Management (ARCM) Model which provides a better support of non-functional requirement changes in ASD for achieving software sustainability. This study was carried out in four phases. Phase one is a theoretical study that examined the important issues and practices of requirement change in ASD. Then, in phase two, an exploratory study was conducted to investigate current practices of requirement changes in ASD. The study involved 137 software practitioners from Pakistan. While in phase three, the findings from the previous phases were used to construct the ARCM model. The model was constructed by adapting Plan-Do-Check-Act (PDCA) method which consists of four 4 stages. Every stage provides well-defined aims, processes, activities, and practices. Finally, the model was evaluated by using expert review and case study approaches. There were six experts involved to verify the model and two case studies which involved two software companies from Pakistan were carried out to validate the applicability of the proposed model. The study proposes the ARCM model that consists of three main components: sustainability characteristics for handling non-functional requirements, sustainability analysis method for performing impact and risk analysis and assessment mechanism of ARCM using Goal Question Metrics (GQM) method. The evaluation result shown that the ARCM Model gained software practitioners’ satisfaction and able to be executed in a real environment. From the theoretical perspective, this study introduces the ARCM Model that contributed to the field of Agile Requirement Management, as well as the empirical findings that focused on the current issues, challenges and practices of RCM. Moreover, the ARCM model provides a solution for handling the nonfunctional requirements changes in ASD. Consequently, these findings are beneficial to Agile software practitioners and researchers to ensure the software sustainability are fulfilled hence empowers the companies to improve their value delivery

Operational risk model for MSES :impact on organisational information communication technology

The aim of the study was to investigate the impact of Information Communication Technology Operational Risk Management (ICT ORM) on the performance of a Medium Small Enterprise (MSE). The study was based upon a survey design to collect the primary data from 107 respondents using simple random sampling. The research instrument was administered online. A one stage normative model, associative in nature, was developed based upon reviewing previous research and in line with the research findings. The model elicited five factors based upon the multiple regression analysis of the data: principal causes of ORM failure related to ICT; change management requirements and ICT risk; characteristic(s) of information; challenges posed by ORM solutions and evaluation models affecting ICT adoption within MSEs. Based on the methodologies used in this study including factor analysis and multivariate regression analysis, it is recommended that this model be applied to monitor these changes more closely and to measure the changing strategies and the associated factors such as insufficient or improper user participation in systems development process, identified as potential barriers to the effective adoption and implementation of ICT within an MSE

Credit derivatives, the liquidity of bank assets and banking stability

The emerging markets for credit derivatives have improved the liquidity of bank assets by providing banks with various new possibilities for selling and hedging their risks. This paper examines the consequences for banking stability. In a simple model where liquidation of bank assets is costly, we show that increased asset liquidity benefits stability by encouraging a representative bank to reduce the risks on its balance sheet. Stability is further enhanced because the bank can now liquidate assets in a crisis more easily. However, we find that these stability effects are counteracted by increased risk-taking by the bank. Overall, stability actually falls because the improved possibilities for liquidating assets in a crisis make a crisis less costly for the bank. The bank therefore takes on an amount of risk that more than offsets the initial positive impact on stability

Towards a change process planning tool

The relationship between a product and its design process is generally complex and not fully understood. When modifying a product, industry still rarely considers the implementation process and its consequences for other design activities in the company, which is hard to assess with conventional planning methods. Although change processes are highly constrained, product and process constraints are not usually considered together or traded off against each other when planning the change. Inadequate assessment and planning of the change implementation process can lead to costly knock-on effects across the product and the design process. This paper argues for a combination of change and process research and discusses requirements for a change process planning tool. It proposes a system for the analysis of the impact of change on the product as well as other company activities. Then, a more informed selection between change alternatives is possible

Impact analysis of enterprise resource planning post-implementation modifications

Enterprise Resource Planning (ERP) as business system integration evolves in the post-implementation phase due to the change in business requirements caused by competitive environments. Uncontrolled or poorly managed changes may lead to low quality, chaotic systems and data that are difficult to use and maintain. Constructivist approaches to effectively manage post-implementation change in ERP systems from the design-related standpoint are currently lacking. Research in this field mostly focuses on CSF (Critical Success Factors) of the post-implementation phase rather than providing a well-structured approach for managing the changes. Thus, this thesis is designed to close this gap by devising methods and tools for controlled ERP post-implementation change management to support stakeholders, such as business analysts and developers, in assessing the impact of the modification. Our methodology draws a parallel approach between ERP post-implementation change management and traditional engineering change management in product design and proposes a framework for impact analysis of ERP post-implementation modifications. The framework defines a meta-model of the dependencies among ERP entities such as business processes, functions, and data. Based on the identified dependencies, the framework allows to automatically analyse the impact of a proposed change through a set of impact analysis mechanisms. Then, evaluate the scope and depth of a proposed change through a set of impact assessment metrics. As part of the evaluation process, our framework has been embedded in a software tool i.e. decision support system to demonstrate the feasibility of our approach. Then, provides an empirical study to validate the research method and the tool through a panel of ERP experts and end users. The result confirms that our framework provides scientifically grounded method to manage ERP post-implementation modification in a controlled manner. The application of our approach improved change impact analysis and reduced the risk associated with post-implementation change management in future