Technical Note 5 An Analysis of Extreme El Niño Insurance in Protecting a Financial Institution s Portfolio

Transcription

1 5 Technical Note 5 An Analysis of Extreme El Niño Insurance in Protecting a Financial Institution s Portfolio Insurance for Climate Change Adaptation Project

2 Diario El tiempo, PIURA Technical Note 5 An Analysis of Extreme El Niño Insurance for Protecting a Financial Institution s Portfolio Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH Insurance for Climate Change Adaptation Project Main Advisor Alberto Aquino alberto.aquino@giz.de Jr. Los Manzanos 119, San Isidro Author GlobalAgRisk Translation Damian Hager Design and Layout Renzo Rabanal Photographs GIZ photo archives, Diario El Tiempo, Piura Printing Giacomotti Comunicación Gráfica S.A.C. Calle Huiracocha Of 302, Jesús María First edition, Lima (Peru), August 2012 Legal deposit in the Biblioteca Nacional del Perú (National Library of Peru) No Cooperación Alemana al Desarrollo Agencia de la GIZ en el Perú Av. Prolongación Arenales 801, Miraflores Total or partial reproduction of this work is allowed, provided the source is cited. 2

3 An Analysis of Extreme El Niño Insurance in Protecting a Financial Institution s Portfolio Executive summary The purpose of this paper is to present the portfolio benefits of Extreme El Niño Insurance for a financial institution and describe risk assessment results, a quantitative model of a financial institution s exposure to the El Niño Phenomenon, and the product s expected benefits. Specifically, insurance payments can contribute to maintaining a satisfactory capital ratio by compensating capital losses due to increased provisions and bad loans. The high cost of undercapitalization will, inevitably, translate into lost opportunities of cost effective loans (Van den Heuval, 2006); thus an insured financial institution should expect greater income than those that do not opt for this type of insurance coverage. The results of the model suggest it would be possible to obtain substantial portfolio protection by purchasing a relatively small amount of insurance, for example, a sum insured equivalent to 1% - 4% of the credit portfolio value. Since the insurance protects a financial institution s ability to extend loans after an extreme El Niño event the model also indicated that the product increases, on average, the final capital position at the end of a 15 year period. More importantly, the insurance greatly reduces the volatility of the bank s equity. In addition to the quantitative effects of the model, insurance coverage can produce other qualitative benefits, namely 1. Heightened reputation of the financial institution of the financial institution as an innovative, socially committed company and market leader. 2. Increased international visibility among socially conscious investors and donors. 3. Improved risk profile for credit rating agencies and debt and capital investors. 4. Reduced net regulatory burden since insurance is formally recognized as a risk management device. 5. Strategic market positioning after an extrem El Niño event which facilitates growth in market share. Based on the results of the model and these other potential benefits, let s assume that a financial institution chooses to insure partially its risk at an amount equivalent 3

4 to roughly 0.8% of its credit portfolio. The premium paid for this risk transfer is about 0.5 basis points of the credit portfolio, and thus it will reduce capital volatility related to an extreme El Niño by nearly 22%. Background The El Niño Phenomenon causes catastrophic flooding in northern Peru. This climatic event is associated with an increase in Pacific sea surface temperatures off the coast of Peru (Lagos et al., 2008). Warm air from the west collides with cold air cascading down from the Andes in the east, thereby setting off severe rainfall (McPhaden, 2003). During the and extreme events, January to May precipitation levels were nearly 40 times above. The volume of water in the Piura River was also 40 times the norm during those events(skees and Murphy, 2009). As a result of the extreme weather, bridges washed away, roads were destroyed, fields flooded, assets were lost, communities were isolated, and food prices, and diseases increased. An extreme El Niño creates problems for financial intermediaries and limits access to credit. For instance, the El Niño event caused credit payment problems that lasted for years (Trivelli, 2006). Afterwards, some financial intermediaries reacted by drastically reducing access to credit for sectors they considered highly vulnerable to the phenomenon, such as agriculture. Moreover, interest rates rose close to 3% in northern Peru on account of the hightened risk of nonpayment associated with the El Niño (Skees and Barnett, 2006). Extreme El Niño Insurance is a type of index insurance which provides pays out on the basis of objective measurements of the severity of a disaster and it is widely used in places where traditional insurance does not meet all the needs of the target market. Its payments are based upon the increase in Pacific sea surface temperatures (SST), which is the standard means climatologists gauge the severity of an El Niño event. The temperature readings accurately predict catastrophic flooding in northern Peru (Khalil et al., 2007), and because of that predictive ability, insurance can be paid even before disaster onset of the disaster. The contract the financial institution is evaluating employs November-December SST readings and pays out in January, the reason being that previous event reports indicate that catastrophic floods occur in February. Thus, the index insurance plan benefits are: 1) advanced payout for more robust disaster management, 2) coverage against business interruptions and higher costs that would not typically be included in traditional insurance plans, and 3) lower insurance costs since adverse selection and moral hazard related to traditional insurance are substantially reduced in index insurance. 4

5 El Niño Risk Assessment To understand the effects the El Niño has on a credit portfolio and its performance, the financial institution surveyed and interviewed its field officers and managers working in northern Peru. There are two important estimates regarding the portfolio: 1) the percentage of the credit portfolio that is affected that requires an adjustment to credit terms through refinancing and restructuring and 2) the percentage of the credit portfolio that is lost. This analysis indicates that the departments of Tumbes, Piura, and Lambayeque are the most vulnerable to an extreme El Niño event. La Libertad is also vulnerable, but to a lesser degree, as only 60% of the department is exposed to an extreme event. The economic sectors of agriculture, fishery, and transportation in these regions are the most at risk, and loans for their investors will present the greatest problems. Management is anticipating some type of response from the federal government to the problems facing the agricultural sector, and prior interventions, such as RFA, motivated an estimated 50% recovery of agricultural credit since the government purchased them. Table 1 shows the effects of an extreme El Niño as described by this risk assessment. Percentages are related to the credit portfolio in the vulnerable regions. The bottom line, Total financial institution portfolio, sums up these effects as percentages of the total financial institution portfolio. In short, the analysis suggests that 11% of the portfolio will require refinancing or restructuring and that 4% of the portfolio value will be lost during an extreme El Niño event. Table 1: Expected results of an extreme El Niño event on loans in the vulnerable regions Sector Affected (%) Lost (%) Agriculture Fishery Transportation Commerce Other sectors 15 3 Total financial institution portfolio 11 4 It is very difficult to conduct these assessments because there are many sources of uncertainty. For example, the 1983 El Niño rainfall pattern and period differed from the 1998 event. The economy and the infrastructure have changed significantly since that last extreme event, and political reactions are difficult to predict. So, while the above figures represent a best estimate of the financial institution s risk exposure, from this point onward we will call it the moderate scenario. Yet, risk assessments also provide 5

6 optimistic and pessimistic scenarios. In terms of the former, an extreme El Niño affects La Libertad to a lesser extent and creates fewer portfolio losses in the transportation, commerce, and other sectors, thereby resulting in an affected portfolio of 9.5% and losses of 2.7%. Under a pessimistic scenario, an extreme El Niño has a greater affect in La Libertad and heightens the problems and/or losses in the agriculture, transportation, and commerce sectors, resulting in an affected portfolio of 14.5% and losses of 6%. If the government was not to intervene through the purchase of agricultural credits after an extreme event, then portfolio losses under the moderate scenario would also be as high as 6%. Table 2 summarizes the three scenarios in terms of the financial institution s total portfolio. Table 2: Summary of extreme El Niño effects on the portfolio in the three scenarios Sector Affected (%) Lost (%) Optimistic 9,5 2,7 Moderate 11,0 4,0 Pessimistic 14,5 6,0 Benefits of the insurance for an El Niño event The greatest risk the El Niño poses for a financial institution is asset loss through late loan payments, a situation that could destroy the bank s capital. Undercapitalization disrupts normal income generating opportunities since bank originates fewer new loans when it reduces leverage. Bad loans also reduce gross income from interest, thereby decelerating recovery due to a reduction in earnings flows. Graphic 1 was generated from a banking model using a moderate scenario. The solid line shows the effect of an extreme El Niño event has on the capital ratio during the second year of the model. El Niño Insurance protects the bank s capital, and it will be paid just before a strong event. The insurance money will be entered into the balance sheet as new capital since it increases the financial institution s assets without associated liabilities. Hence, it increases the capital ratio,by the dotted line in Graphic 1, where the insured amount is 4% of the portfolio value. Bear in mind that the financial institution s insured capital ratio will fall after the El Niño event for two reasons: 1) the portfolio insurance does not directly deal with problems related to borrowers failure to make loan payments, thus the portfolio value will continue to fall, and 2) we anticipate that the financial institution will want to offer loans aggressively after the catastrophic event in order to cover a growing demand from its good customers in the region who need to rebuild. While a financial institution is not very vulnerable to liquidity risks due to an extreme El Niño phenom- 6

7 Capital ratio (%) Graphic 1: El Niño effects on insured and uninsured capital ratio 21 El Niño With insurance 7 Without insurance Time (years) enon, early payouts also improve its cash position, and thus facilitate handling of unforseen liquidity needs. A financial institution with a low capital ratio will need to be more cautious than those with a sufficient capital ratio. Management, debt holders, and capital holders are not the only ones with an interest in protecting the financial institution s solvency, but also its supervisors, who can intervene when the capital ratio is low. Specifically, the model encompasses an objective capital ratio so the bank can adjust credit generation if the capital ratio deviates from this objective. For example, if the financial institution undercapitalizes, it would issue fewer loans in the current period. As illustrated in Graphic 1, the insured financial institution is in a strong position when an extreme El Niño event occurs because it receives the insurance money. Therefore, it can decide of how aggressively to invest this new capital in loans, balancing losses related to delinquent borrowers that reduce the bank s capital, with new opportunities for issuing loans to households and businesses that want to rebuild. We expect the financial institution will rely on some combination in order to maintain additional capital reserves as it verifies the payment capacity of current borrowers, thus taking advantage of the strong market opportunities. The model demonstrates that the insured financial institution is in a strong position as the extreme El Niño takes effect since it has received the insurance payment. Graphic 2 compares the loan generated model for insured and uninsured financial institutions. In the aftermath of the El Niño, the insured financial institution generates much higher levels of loans. In reality, the insured institutions will have the option of how aggressively it would like to apply this new capital to loans. It must balance imminent losses from delinquent borrowers, which will reduce its capital, with the opportunity of new loans for households and businesses that need to rebuild. We expect the financial institution will rely on some sort of combination in order to maintain additional capital 7

8 reserves as it determines the repayment capacity of its current borrowers, whereby it takes advantage of the strong market opportunities. One financial benefit of the insurance not shown in this model is that after an extreme event, the stronger financial intermediaries have the potential to gain more of the market share from the weaker. Graphic 2: Portfolio growth 1,20 1,00 0,80 CPortfolio growth (%) 0,60 0,40 0,20 0,00-0,20-0,40 With insurance Without insurance -0, Time (years) Results comparison over a 15 year time period The above example describes how an extreme El Niño event can affect a financial institution. The following analysis compares a range of possible results in order to determine whether the bank will be in a better or worse position due to the purchase of the insurance. We use a 15 year time period because it offers a clearer image of how the insurance helps protect the bank s long term stability We use the Monte Carlo simulation for this analysis, in which the same test is repeated when a result is uncertain (for example, if and when the El Niño event will occur) and the possible results are summarized. Thus, a Monte Carlo simulation is like throwing dice over and over again, while documenting the results. The result of interest in this method is the financial institution s capital at the end of a 15 year period. Graphic 3 features the results for a moderate scenario. The insured amount is equal to 4% of the credit portfolio value, the price of the insurance in this model is 7% of the insured amount each year, and the number of simulations is 10,000. The graph is laid out so that the simulations with lower final capital are on the left and those with higher are on the right. Approximately 35% of the time during the 15 year period, an El 8

9 Niño event does not occur. In those instances, the uninsured financial institution has a higher final capital position than the insured financial institution. However, an El Niño event does occur at least 65% of the time, and the insured financial institution is in a better position than the uninsured one. This is because the insurance protects the financial institution s capital, as described above, and enables it to continue aggressively leveraging its profits. In a comparison of 10,000 simulations, the average capital position at the end of the 15 year period for the insured financial institution is higher than that of the uninsured one. While the effect on average capital is minimal, its effect on risk is not. The final capital variance i.e. the volatility of the bank s capital reserves is reduced by approximately 80%. In conclusion, the benefits of the insurance clearly outweigh its cost. Graphic 3: Monte Carlo Simulation: Final capital after 15 years 100 Average Variance With insurance Without insurance 34,84 226,65 37,34 45,93 No El Niño 70 Simulations (%) El Niño With insurance Without insurance Final Capital Afterwards, we compared results for different levels of insured amounts. We ran the Monte Carlo simulation, plugging in several insured amounts and comparing the results vis-à-vis 1) average final capital after 15 years and 2) final capital volatility. Graphics 4, 5, and 6 show the results for moderate, optimistic, and pessimistic scenarios. The y-axis represents average final capital and the x-axis the volatility. Each point on the graph represents one application of the Monte Carlo simulation, similar to the lines in Graphic 3. For each one of these simulations, both expected value and final capital volatility improve for relatively small insured amounts compared to those that are uninsured, or as call self-insured here. This finding is reliable for all the risk assessment scenarios. Additionally, though the insurance betters the financial institution s expected final 9

10 capital position, the sound risk reduction benefits of acquiring even a small amount of insurance are extremely evident. Graphic 4: Comparison of the final capital position of insured amounts in the moderate scenario after 15 years % 39 6% Average % 36 2% 35 Self-insured Variance Graphic 5: Comparison of the capital position of insured amounts in the optimistic scenario after 15 years 43,0 42,5 6% 42,0 Average 41,5 41,0 40,5 40,0 4% 2% 39,5 39,0 38,5 Self-insured 38, Variance 10

11 Graphic 6: Comparison of the capital position of insured amounts in the pessimistic scenario after 15 years % % Average % 6% 31 4% % 28 Self-insured Variance Benefits for financial sustainability After studying this analysis, the financial institution s managers should look into the possibility of purchasing insurance for an amount equal to approximately 0.8% of the credit portfolio value. As indicated in Graphics 4, 5, and 6, this level of insurance can greatly reduce risk, as measured by the volatility of the capital base. Table 3 demonstrates these differences for the specific position of the financial institution in the three scenarios. Under all scenarios, the insured financial institution is in a better position. On average, these studies indicate that the financial institution reduces its risk by 22%, for an amount of 0.5 basis points. Table 3: Modeled effect on expected value and capital volatility of the Financial institution s purchase of insurance, according to the scenarios Scenario Measure Uninsured Insured % Change Optimistic Average 38,54 39,21 +1,7% Variance 143,37 102,92 28,2% Moderate Average 34,83 34,93 0,3% Variance 226,65 174,49 23,0% Pessimistic Average 27,90 28,33 +1,2% Variance 384,23 325,36 15,3% 11

12 Social and qualitative benefits Insurance has several benefits additional to those presented in the previous model. 1 Heightened reputation as an innovative, socially committed company and market leader The financial institution is already known as a rapidly growing, effective, and socially committed financial intermediary. This reputation should improve when it becomes the first to insure itself against a major banking risk in Peru. The financial institution s marketing strategies will highlight this innovation and the increased resiliency. 2 Increased international visibility among socially conscious investors and donors The financial institution plans to use the protection offered by the insurance to increase its outreach to underserved households and businesses. Furthermore, if there were an extreme El Niño event, it would expect to allocate its payments to the most affected regions where it operates where the demand for credit for recovery and reconstruction will be greatest. The opportunities for extending the benefits of the insurance to borrowers in a more formal manner through the financial services it offered may also be a significant step for the financial institution. 3 Improved risk profile of credit rating agencies and debt and capital investors Although it is not clear if the insurance will improve the financial institution s explicit rating, it certainly will improve its risk profile, a factor which can also be important to current and potential investors. 4 Potential for reduced regulator burden of the financial institution because insurance is a formally recognized as a risk management tool The banking sector provides important services to the economy that can facilitate growth. Bank failure can generate shocks in credit generation 12

13 that lead to economic losses. Therefore, one policy objective is to avoid shocks in the credit market, thereby reducing bank failure. Policymakers expect to satisfy this objective with minimal social cost related to a reduction in credit access. Capital requirements are an important risk management mechanism that can act as a buffer against losses from a variety of risks. Banking law dealing with portfolio risk management that solely uses capital reserves is limited in the following ways: 1) Basel requirements are not sensitive to the systemic risks that Peruvian banks face, 2) they implicitly limit access to credit and raise interest rates, 3) they fail to promote portfolio risk reduction, through diversification, 4) they fail to encourage loans in regions where systemic risks can be transferred, and 5) they perpetuate credit shocks since banks have to reduce investment after losing capital. Insuring against significant systemic risks can be a viable complement to capital reserves that improve prudent regulatory efficiency and effectiveness by addressing these limitations of capital requirements. The best use of insurance will probably be for unsettling systemic risks that can generate substantial portfolio losses, such as disasters. Insuring against natural disasters is usually more important for development banks in the country since their portfolios tend to be more concentrated in geographic area and economic sectors. El Niño Insurance is an excellent example and creates an opportunity for the Peruvian banking regulatory agency to set a precedent that will reward strategies which tend to reduce risks among banks in developing countries and that tackle limitations in the current international banking standards. 5 Strategically market positioning after an extreme El Niño event can open doors to the financial institution for an increased market share After a severe El Niño event, borrowers will have a growing need for credit to recover and to rebuild, but many banks will not be in a good position to extend them loans because they will have experienced huge losses. Bankers that were in business during the 1998 El Niño reported that strong banks were able to take over entire groups of weakened banks in the aftermath. Since the insurance will improve the financial institution s position after a severe El Niño event vis-à-vis uninsured banks, it will be able to capture a greater market share in that period. 13

14 References Boucher, S; Carter, M, and C. Guirkinger. Risk Rationing and Wealth Effects in Credit Markets: Theory and Implications for Agricultural Development in American Journal of Agricultural Economics 90 (2008): Khalil, A.F., H.H. Kwon, U. Lall, M.J. Miranda, J.R. Skees. El Niño-Southern Oscillation-based Index Insurance for Floods: Statistical Risk Analyses and Application to Peru. Water Resources Research 43 (2007): W McPhaden, M. J. El Niño and La Niña: Causes and Global Consequences. Encyclopedia of Global Environmental Change, Volume 1: The Earth System: Physical and Chemical Dimensions of Global Environmental Change. MacCracken, M. M., Perry, J. S. (Eds.) & Munn, T. (Editor-in-Chief), Wily: Hoboken, NJ, Skees, J.R. and B. J. Barnett. Enhancing Microfinance Using Index-Based Risk-Transfer Products. Agricultural Finance Review 66 (2006): Skees, J.R. and A. G. Murhpy. ENSO Business Interruption Index Insurance for Catastrophic Flooding in Piura, Peru. GlobalAgRisk, Inc. Trivelli, C. Rural Finance and Insurance on the North Coast of Peru. Summary Report 2005/06. Instituto de Estudios Peruanos, Lima, September Van den Heuvel, S. The Bank Capital Channel of Monetary Policy Meeting Papers 512, Society for Economic Dynamics (2006). 14

15 15 Diario El tiempo, PIURA

16 Risk is out there, get insured. The Insurance for Climate Change Adaptation Project is part of the International Climate Initiative (ICI) of the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU).