Solvency Ii – Underwriting Credit Risk Models

This research project analyses the Solvency Capital Requirement (SCR) calculation models applicable to Trade Credit Insurance Underwriting Risk. The current regulation, the Solvency II Directive (25/11/2009), is not restrictive in this regard and allows each insurer to use the model of SCR calculation which best suits its purpose, with the condition that it obtains authorization from the local regulator. However, a Standard Formula is available, for those institutions that wish to use it, to evaluate SCR (with standard parameters or the company's own). This Standard Formula offers much greater simplicity in all aspects, and requires less documentation and evidence on the accuracy of the model. This simplicity and ease of calculation has its downside, as presumably insurers only use internal models if they are able to reduce the SCR versus the Standard Formula. This is precisely the downside, the excess capital implied by not applying an Internal Model adapted to the Insurance Company's Risks. In this paper we present a compendium of five different options or models of calculating SCR for Underwriting Risk in the Credit Insurance Business. The Standard Formula with standard parameters or with a company's own parameters. Internal Models derived from the Banking Model for Credit risk, Internal Models based on the generation of a large number of simulations of the Technical Income Statement and Internal Models based on the method of calculating the Claims Reserve. To clarify, the model based on Bank Credit Risk implies using the model accepted for Bank Credit Risk. This model is defined in the Basel II Directive, and is specifically applicable to the banking business as an Underwriting Risk Model for the Credit Insurance line of business. In the insurance business, the Solvency II Directive (25/11/2009) also defines a Credit Risk, which basically refers to third-party debtors of the insurance company, and is included in the counterpart sub-risk, specifically for Reinsurance balances. When we carry out the SCR calculation based on a company's data for Underwriting Risk with each of the five models mentioned, it should not come as a surprise to find that these fall in a narrow range. This is the logical conclusion of using different empirically contrasted techniques to evaluate the same thing. However, and despite the complexity of each model, this may not happen, which would give us a clue as to what other aspects of the models, such as their calibration, the coefficients used, the correlations or risk mitigators, among many other factors, may be the cause of the disparity in values. In this sense, this research project aims to evidence the differences between the models, questioning certain aspects and suggesting possible modifications in order to better reflect the reality of the risks they measure, and as a consequence, open future lines of investigation. On the other hand, and given the different ways the various models deal with Catastrophe Risk, (one of the sub-risks into which Underwriting Risk is divided), alternatives, and implicitly the obvious solutions, are posed for each specific model as a prerequisite to carrying out all the above. Lastly, Solvency II considers a 12 month timescale. This means that the calculated SCR must be sufficient to guarantee the solvency of the insurer over this period. However, this also dictates that the SCR calculation must be coherent with ERM (Enterprise Risk Management) and in this sense, if the business model and/or the behaviour of the assumed risks represent a longer term view, the capital calculation model should also contemplate this peculiarity. Addressing the above, it becomes very difficult to defend the one-year timescale. In insurance business practice, the implementation of all types of policies demands a much longer term vision than one year, given that risk and capital management, among many other aspects, should be on par with availability and capabilities, and especially, with the business model and the ease or difficulty of access to capital markets. This is never carried out with a short term outlook. Additionally, the increase in natural catastrophes, with the corresponding increase in claims and the cost of reinsurance, also impacts on the need to embrace much longer time periods, so that the cyclical nature of these phenomena can be contemplated. Together, the models analyzed are based on the hypothesis that, should an LGD (Loss Given Default) event occur, the business would fail and cease trading, unless its shareholders or external investors provide sufficient capital. It is highly questionable that this would occur, given that the shareholders may not be disposed to continue investing when they doubt if they will recover their capital or not, and when access to capital markets is going to be difficult, basically due to the excess they must pay or simply because of the lack of any offer or interest in entering the company. Obviously a multi-annual view would help to circumvent these issues. All the topics dealt with are extremely complex, and this work aims to show the significant differences between the various methods, their pros and cons and especially their limitations, all of which may produce very different capital requirements. This implies, depending on the directionality of the local regulator, that if left uncorrected, insurers will be more or less solvent and in the reverse sense more or less competitive in terms of capital cost, depending on the method they use. This is not only undesirable, but steps should be taken to prevent it. As a conclusion to the research project, the author is of the opinion that sufficient elements have been introduced for all these aspects to deserve a deep and exhaustive analysis, leading to the generation of a current of opinion that allows a wide consensus in terms of the method/s that best serve the reality of Trade Credit Insurance Underwriting Risk and if relevant, the modifications that should be proposed to overcome the limitations detected.