The Book presents a survey on the principal quantitative models on Asset Liability Management in Insurance Companies and Banks. It goes through the duration and the market value approach till the stochastic optimization. The model, by using a contingent claim approach, determines the fair value of the insurance life policies. Furthermore, it shows that the value of equity can be immunized with respect to the movevement of interest rate. Moreover, the model determines the fair value of the banks liabilities accounting for the protection and the surrender possibility.
Asset Liability Management in Insurance Companies and Banks: Quantitative Models. Team, where his team contributes to the ALM models and indicators. Association of Asset and Liability Managers asset liability management in insurance companies and banks quantitative models. Since 2005, Alexandre.
A version of this paper appears as a chapter in CCAR and Beyond: Capital Assessment, Stress Testing and Applications , Jing Zhang, ed., London, UK: Risk Books, 2013. Authors Booksellers Customers Journalists Lecturers Librarians asset liability management in insurance companies and banks quantitative models pdf. A major source of firm funding and liquidity, credit lines can pose significant credit risk to the underwriting banks.
Since 2005, Alexandre. SME Financing: Measuring Private Firm Credit Quality - Disintermediation and the Rise of SME Loan Funds . Required economic capital (EC) and regulatory capital (RegC) are two measures frequently used in loan origination and other decisions related to portfolio construction. EC accounts for economic risks such as diversification and concentration effects. When used in measures such as return on risk-adjusted capital (RORAC) or Economic Value Added (EVA™), EC can provide useful insights that allow institutions to optimize risk-return profiles, facilitate strategic planning and limit setting, as well as define risk appetite. Meanwhile, when RegC is binding, an institution faces a tangible cost, in that additional capital is needed for new investments that face a positive risk weight. Given these observations, both EC and RegC should influence decision making.
As most life insurance contract liabilities are long-duration contracts, it is not always easy to achieve a perfect match of long-duration assets. In a low interest rate environment, it is challenging to find relatively low-risk, high-yield, long-duration assets to match annuities that guarantee a minimum annual return (e.g., 4%).
For example, older fixed income insurance products that guarantee rates of around 6%—closely matching or conceivably even surpassing current investment portfolio yields—are likely to put a strain on life insurers as a result of spread compression or interest rate risk for insurers, relative exposure to interest rate risk could be gauged by considering the type and the proportion of interest rate risk-sensitive products of each insurer. Figure 2 below presents the degree of interest rate sensitivity of each life product type, from high to low. interest rate risk because they are guaranteed to earn a fixed rate of return throughout the life of the product. Products that combine protection with asset accumulation guaranteeing minimum returns (e.
, by lowering guaranteed rates), thereby challenge for insurers’ ALM is that current lower-yielding investments cannot meet past return assumptions (reinvestment rate risk). As higher-yielding investments mature and roll over into lower-yielding assets, the degree of risk faced by an insurer depends on the extent of the duration mismatch between assets and liabilities. The duration of some life insurers’ liabilities exceed the longest duration assets that may be available for purchase and, as a result, companies could be exposed to reinvestment rate risk. of duration match seems straightforward enough in theory, in practice it is much harder to achieve a perfect hedge against interest rate risk.
The NAIC Capital Markets Bureau has begun analyzing changes in asset mix from year-end 2010 to year-end 2011 and found significant dollar increases in two areas; structured securities and investments in commercial real estate, either through mortgage loans or equity. In the case of structured securities, the increase is largely attributable to additional investments in agency-backed Residential Mortgage-Backed Securities (RMBS), which are effectively supported by the Federal government. In the case of commercial real estate investments, growth was higher than overall growth in invested assets. However, the increase as a percent of invested assets was modest and the current percentage remains below strategies based on derivatives that allow them to manage and mitigate risk by “locking in” higher interest rates. On the other hand, hedging with derivatives could also pose certain risks, such as counterparty risk, which increases substantially with the length of time required for the hedging strategy.
According to 2010 year-end NAIC data, about 64% of insurers’ total notional value of outstanding over-the-counter (OTC) derivatives and futures contracts is used in mitigating risks resulting from were the most common swaps derivative instrument utilized by insurers in their hedging strategies, representing approximately 75% of the swaps exposure. Furthermore, interest rate swaps comprised about 73% of the hedges with maturity dates of 2021 and beyond, and 45% of the hedges with maturity dates mitigate interest rate risk, are fixed-income futures (which obligate the insurer to sell a specified bond at a specified price to a counterparty at a future date), floors (which entitle the insurer to receive payments from a counterparty if interest rates drop under a specified level) and “swaptions” (which give the insurer an option to enter into a fixed swap with an interest rate environment on the life insurance industry in the United States. The data used in the study was gathered from the financial annual statements filed by life insurance companies for the years 2006 through 2010. The objective of the study was to determine the effect the low interest rate insurance company legal entities that had submitted data for all five years of the study (2006—2010).
It is also interesting to note that the smaller-size companies (i.e., those with reserves of less than $5 million) had a larger decline in gross portfolio yield. Smaller-size companies are less able to leverage their investment activities and must purchase smaller-sized assets than larger competitors.
Again, the data show a decline in the life insurance industry’s yield between 2006 and 2010. The industry lost 49 basis points of net yield between 2006 and 2010 (71 basis points of net yield between the high in 2007 and the low in 2009). The drop in net portfolio yield is less than the drop in gross yield which could be due, in part, to cost-cutting measures companies have taken as spreads have declined and a shift to less asset-intensive securities. The difference between the gross and net portfolio yields reflects investment expenses, as well as investment taxes, licenses and fees.
2 billion of lost spread revenue over the five-year still in a position of positive net investment income spread of around 136 basis points. So, to date, the low interest rate environment has created spread compression on earnings, but has not yet impacted insurance company solvency, which would begin to occur when the spread compression drops below zero. It is important to note that the pricing of life insurance products in the United States not only contains an investment spread margin, but also a spread margin built into the mortality rates and the expense component (e.g., contract fees and policy expense charges).
The American Academy of Actuaries (AAA) has developed an economic scenario generator that randomly generates interest rate scenarios as well as market rate scenarios. Companies typically use the AAA’s economic scenario generator to develop the stochastic interest rate increasing over five years at 1.0% per year and then uniformly decreasing over decreasing over five years at 1.0% per year and then uniformly increasing over tests to help ensure that life insurance companies have either well matched asset and liability cash flows or have established additional reserves that are available to cover any interest rate or reinvestment rate risk that is embedded insurance companies to post an additional reserve if the appointed actuary determines that a significant amount of mismatch exists between the company’s asset and liability cash flows. As part of this study, the NAIC pulled the additional reserves liabilities that were established by companies at year-end 2010. The life insurance industry posted an additional asset/liability cash on the life insurance industry is something that bears watching.
Clipping is a handy way to collect and organize the most important slides from a presentation. You can keep your great finds in clipboards organized around topics. Some practitioners prefer the phrase "surplus optimization" as better to explain the need to maximize assets available to meet increasingly complex liabilities. Alternatively, surplus is known as net worth, or the difference between the market value of assets and the present value of the liabilities and their relationship. The discipline is conducted from a long-term perspective that manages risks arising from the interaction of assets and liabilities; as such, it is more strategic than tactical.
Estimation of the severity levels, occurrence and duration of those stress events on the bank funding structure. The rate at which money is exchanged from one transaction to another, and how much a unit of currency is used in a given ... You might like: What is an Actuary? Research at SOA. The Task Force encourages readers of the new guide to share their comments and suggestions about the guide so that future editions can incorporate appropriate changes. Readers may send feedback on the guide to:. insurance company and how cash flow testing is done in Prophet, an actuarial software used in.