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Eurozone's economic growth potential permanently hampered, report says

2018 US Property Casualty Insurance Market Report

Four Early Warning Signs Of Public Company Credit Risk Deterioration

Credit Analytics Case Study Poundworld Retail Ltd

Opinion: Look Outside the US for Insurance Blockchain Projects

Eurozone's economic growth potential permanently hampered, report says

The slowdown of economic growth in the eurozone has been sharp as a number of one-off factors drag on activity, but the ability to rebound will be limited, according to Oxford Economics, which argues the group of 19 countries has been operating at close to its economic potential.

Growth of just 0.2% in the fourth quarter of 2018 was the latest in a series of disappointing data releases in the eurozone, with Italy entering into a technical recession and Germany, the regional powerhouse, only narrowly avoiding a similar fate.

SNL Image

French protesters have taken to the streets, highlighting economic discontent in the region.

Source: Associate Press

Annual growth in 2018 of 1.8% paled against 2017's 2.5%. The slowdown appears to be broad based with weakness in industrial output and the consumer sector. EU emissions tests badly hampered the German automotive sector, while violent anti-government street protests in France have hit domestic consumption, and for the entire region, global trade tensions are damaging supply chains.

Since the first quarter of 2018, the consensus opinion has been that the drags on European economic growth would be temporary, but Rosie Colthorpe, assistant economist at Oxford Economics, a U.K.-based global forecasting company, argues that contractionary fiscal policy at the height of the 2008/2009 financial crisis set output, both actual and potential, on a "permanently lower path."

Reduced capacity

"The eurozone economy is now operating close to its productive potential, even though it has lost the equivalent of Spain’s GDP compared to pre-crisis trends," Colthorpe wrote in a recent report.

Colthorpe argues that having allowed the capacity of the growth in the region to decline in crisis years by avoiding significant fiscal spending, governments now have little room to stimulate without causing inflation. "The euro area potential output growth rate has fallen to 1.5% from 1.8% prior to the crisis, so what would have been seen as sluggish growth is now in fact the new normal."

Wells Fargo cut its GDP outlook for the eurozone to 1.5% for 2019 and 1.4% in 2020, from 1.6% and 1.5%, respectively. "Even if the euro area avoids a near-term recession as we expect, it is hard to get particularly excited about the region’s growth prospects," wrote Erik Nelson, a macro strategist at Wells Fargo.

Colthorpe suggests the lost potential output stems from a "permanently lower labour participation rate, a large productivity shock and a lower capital stock as both governments and businesses slashed investment spending." She also acknowledges that growth in the run-up to the crisis may have been unsustainable, distorted by an "exuberant financial sector."

Monetary stimulus

While austerity took precedence over fiscal stimulus in much of Europe, the European Central Bank swung into action, cutting interest rates and introducing quantitative easing to boost business conditions. ECB President Mario Draghi has long pressed for fiscal policy to support the accommodative monetary policy.

David Owen, chief European economist at Jefferies, said it was then down to governments to boost the economy. The ECB "would turn around to the politicians and basically say, 'We bought you time, we stopped the system breaking apart. You didn't actually fix the roof when the sun was shining.' Germany is still running a current account surplus," Owen said in an interview.

The latest data from Eurostat shows that overall the eurozone is exporting more than it is importing amid weak domestic demand, recording a current account surplus of €20 billion in November 2018. In the 12-month period to November 2018, the total surplus was €353 billion, or 3.1% of GDP.

"The eurozone is running a current account surplus that is basically the same as the U.S. deficit," Owen said. According to S&P Global Market Intelligence data, the U.S. current account deficit was $449.5 billion in 2017. "One of our major themes has been that the eurozone current account surplus has been effectively supporting U.S. and U.K. bond markets. Half a trillion [dollars of] net buying of debt securities."

Oxford Economics calculates that every 1% of fiscal policy-induced decline in 2010 and 2011 GDP led to a 0.6% fall in potential output by 2016, and 1.3% by 2021.

"The lessons for the next downturn are clear: counter-cyclical policy should be more aggressive to prevent permanent output losses," Colthorpe said, but noted that a boost in fiscal spending now "is not potent enough to push the economy all the way back to its former path."

2018 US Property Casualty Insurance Market Report


S&P Global Market Intelligence’s 2018 US Property & Casualty Insurance Market Report offers a five-year outlook for the P&C sector, which should return to underwriting profitability for the first time since 2015.

Oct. 26 2018 — The federal tax reform President Donald Trump signed into law in December 2017 should help provide for an extended period of P&C industry profitability in 2018 and beyond as companies benefit from the lower corporate tax rate, but the impact is not limited to after-tax profitability. Actions by several prominent European-headquartered insurers to change the way certain of their U.S. business is reinsured materially impacted premium growth rates in the first quarter of 2018 and are likely to affect full-year results.

1 quarter does not a trend make

Historically strong results for the State Farm group in the first quarter
helped drive favorable comparisons in several key measures of underwriting profitability. To the extent the improvement continues for State Farm — the industry’s largest group based on direct premiums written — it could provide an additional tailwind for 2018 and beyond.

While there is a risk of recency bias in reading too much into a single quarter’s worth of data, the industry was already positioned for improved underwriting results in 2018. The second half of 2017 saw elevated catastrophe losses as the United States was hit by three landfall-making hurricanes and an unusual spate of fourth-quarter wildfires in California. Projected results for 2018 and subsequent years, all of which show combined ratios of less than 2017’s total of 103.5%, assume a normal catastrophe load.

Auto repairs in progress

Competition will remain intense in certain non-auto business lines given ample reinsurance capacity, high levels of industry capitalization and a macroeconomic environment that remains characterized by relatively slow growth in gross domestic product. Though modestly higher business volume driven by that economic expansion will help offset downward pressure on premiums, the industry will be challenged to achieve profitable top-line growth.

Trends in litigation will increasingly weigh on underwriting results in several business lines, including professional lines and the Florida homeowners business. They also could lead to greater demand for coverage, particularly for new and emerging risks.

The macro view

A rising federal funds rate and 10-year Treasury yields that have reached seven-year highs bode well for an industry that has long been suffering from low interest rates. And the relief cannot come quickly enough after the industry’s net yield on invested assets slipped to a new low of only 3.03% in 2017. Though projected results provide for increasing yields from that floor, the improvement will still take place gradually and is unlikely in and of itself to materially impact how companies are underwriting business

S&P Global Market Intelligence client? Click here to login and read the full 2018 US Property & Casualty Insurance Market Report.

The projections reflect various assumptions regarding premiums, losses and expenses. They are a product of a sum-of-the-parts analysis of individual business lines that is informed by third-party macroeconomic forecasts, historical trends and recent market observations that include first-quarter 2017 statutory results and anecdotal commentary about market conditions. Projected results are displayed on a total-filed basis and are not intended for application to individual states, regions or companies. S&P Global Market Intelligence reserves the right to update the projections at any time for any reason.

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U.S. Insurance Market Report – Property & Casualty (June 2017)

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Credit Analysis
Four Early Warning Signs Of Public Company Credit Risk Deterioration


Co-Author: Hrvoje Tomicic

Oct. 24 2018 — A firm’s stock price is often thought to be a reflection of its expected future cash flow. Based on this idea, in 1974 Merton proposed a model for assessing the structural credit risk of a company,leveraging Black-Scholes’ options pricing paper.2 This model has become popular among financial and academic practitioners and is still employed to monitor the credit risk of public companies or for investment purposes.

Due to its market-driven nature, the model’s daily outputs are often plagued by unwanted noise that makes it hard to detect genuine signs of a firm’s impending credit risk deterioration.

At S&P Global Market Intelligence, we have developed PD Model Market Signals (PDMS), a statistical model that builds on the original framework proposed by Merton with further enhancements and refinements such as:

  • Model calibration: PDMS is calibrated based on the industry-sector long-term default rates observed in S&P Global Ratings’ historical database of rated companies3, thus anchoring the model outputs to stable reference levels.
  • Granularity: By capturing important business risk drivers, such as Country Risk Scores and industry risk components, and market-risk drivers such as CDS Market Derived Signals,4 PDMS provides greater insight into global public companies headquartered in different countries, or operating in different industries.
  • Noise reduction: We employ advanced statistical techniques to filter out potential outliers, thus generating cleaner and easier-to-interpret market signals.

How can you use PD Model Market Signals?

Based on this model, there are four early warning signs of imminent credit deterioration of the public companies under your surveillance. Below, we outline those key indicators and how to apply our PDMS model as a best practice approach for measuring credit deterioration.

1. The Probability of Default (PD) increases beyond a fixed level, based on our observed historical trends: Our model can be used to flag a company every time its PD passes the median or the bottom quartile of the distribution of defaulted companies. Figure 1, shows the historical behavior of the median and bottom quartile PD generated by PDMS for several hundred public non-financial companies that defaulted between 2003 and 2015, as they approached the default date. Half of the defaulters had a PD above 8%, a full twelve months prior to default, increasing to 15% at the default date. For a quarter of the companies that “went bust” (the “bottom quartile”), the PD goes from 16% (12 months prior to default) to more than 28% at the default date. Keeping in mind your own risk appetite, it is relatively straightforward to define reference points that can be used to generate timely alert signals that can trigger specific actions when breached in advance of a potential default.5

Figure 1: Median and bottom-quartile PD generated by PD Model Market Signals for non-financial (non-FI) public corporations that defaulted in the period 2003-2015, from twelve months prior to default to default date.

Source: S&P Global Market Intelligence (as of August, 1st 2018). For illustrative purposes only.
2. The PD is markedly different from the typical values of companies in the same industry/country peer group: When you have exposure to several companies in the same sector or country and their PD’s are all quite volatile, you still need to monitor and separate the “bad from the good apples”. Figure 2 shows the case of Noble Group Limited that defaulted in March 2018. Over a twenty-four month period prior to default, our PDMS model generated a very volatile PD that peaked above 30% on several occasions. This is even more significant when compared to the median, bottom quartile, and 10th percentile PD of companies in the same peer-group for the corresponding period. One suggestion to get additional insight is to set a threshold based on the bottom quartile or the 10th percentile PD so that whenever a firm’s PD exceeds the chosen threshold, the company is moved into a watch-list for further action. The converse would happen when the PD goes back within the “norm” range. This approach is also validated by the Key Developments reported for this company within the S&P Capital IQ platform, as shown in the callouts within Figure 2.

Figure 2: Market Signal PD (PDMS) of Noble Group Limited and median, bottom quartile and 10th-percentile PD of peer-companies listed in the Singapore stock exchange within the Trading Companies and Distributors sector.

Source: S&P Capital IQ Platform (as of August, 1st 2018). For illustrative purposes only.
3. The PD of a company exceeds its moving average: This third sign is important when analyzing stock markets, where moving averages are often employed to remove unwanted noise to more easily gauge short-term and long-term trends of a stock’s price. A firm’s PD can often be very volatile, but its moving average (over 30 or 180 days) is less eventful, and any time the short-term moving average crosses the long-term average, a warning signal is generated. Cumulus Media Inc., which defaulted in November 2017, is a good example (see Figure 3). As you can see, a more timely alternative would consider the actual PD value in relation to the 30 days moving average. For example, in the Cumulus Media Inc. example, the last time the PDMS was higher than the 30 day moving average was in August 2017.This additional intelligence would have potentially allowed for precious time to carry out further analysis or take an appropriate remediation action. In addition, in this case, checking key developments and news may have further provided signal confirmation, as shown in Figure 3.

Figure 3: Market Signal PD (PDMS) of Cumulus Media Inc. and its moving average PD (over 30 or 180 days) for the period September 2016 to November 2017.

Source: S&P Capital IQ Platform (as of August, 1st 2018). For illustrative purposes only.
4. The PDMS-implied credit score deteriorates more than the corresponding S&P Global Ratings’ issuer credit rating: Our approach becomes particularly powerful when the S&P Global Ratings’ issuer credit rating is non-investment grade and the PDMS implied credit score becomes (significantly) worse than the actual rating. This is exemplified in Figure 4 for the case of Bon-Ton Stores, which defaulted in December 2017. Here you can see that the implied credit score is compared to the rating from S&P Global Ratings. The combination of a weak issuer credit rating by S&P Global Ratings and a weak credit score implied by S&P Global Market Intelligence’s PDMS statistical model represents a “deadly combination” that should ring a very loud alarm bell; the S&P Capital IQ platform’s key developments call-outs complete the picture.

More generally, our internal analysis on non-FI corporates rated in the speculative grade range by S&P Global Ratings shows that whenever the PDMS-implied score is three or more notches worse than the actual credit rating, there is a 30% chance of a further S&P Global Ratings’ downgrade6 within 12 months. This helps confirm the versatility of this technique in generating actionable signals even for asset management purposes. We will follow with a separate white paper on how asset managers can use this model, and what happens when the PDMS implied-score sizably deviates from the S&P Global Ratings’ issuer credit rating.

What about the public companies that are not rated? One can still combine the PDMS output with the credit score generated by S&P Global Market Intelligence’s CreditModelTM, a quantitative model that uses company financials and other socio-economic factors to generate a quantitative credit score for a longer time horizon that statistically matches S&P Global Ratings’ issuer credit ratings7 for rated companies, but also covers unrated companies.

Figure 4: S&P Global Ratings’ issuer credit rating (ICR) and PD Model Market Signals (PDMS) implied credit score for Bon-Ton Stores, Inc.

Source: S&P Global Market Intelligence (as of August, 1st 2018).6 Key developments extracted from the S&P Global Market Intelligence’s Capital IQ platform. For illustrative purposes only.

Some will argue that looking at a firm’s stock price should be sufficient for most purposes, as its price already embodies all necessary market information. However, the main advantage of a structural model such as PDMS is to link the capital structure of a company to the uncertainty around a company’s future cash-flows, and to properly quantify the probability of default based on empirical evidence.

As a final remark, we stress that none of the techniques mentioned above will be infallible all the time, due to the unpredictable nature of default events. In general, a combination of multiple signals will achieve better performance, and should trigger further due diligence. For example looking at the company financials and their trend over time, comparing the focus company vs its peers, complementing the market-implied credit risk assessment with alternative statistical models (for example S&P Global Market Intelligence’s PD Model Fundamentals), and ultimately validating the assessment with news, key developments or alternative information.

1 “On the pricing of corporate debt: the risk structure of interest rates”, R.C. Merton, J. Finance 29, 449–70 (1974).
2 “The pricing of options and corporate liabilities”, F. Black and M. Scholes, J. Polit. Econ. 81, 637–54 (1973).
3 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD credit model scores from the credit ratings issued by S&P Global Ratings.
4 Fundamental credit risk analysis shows that country and industry risk capture importance risk drivers linked, for instance, to ease of doing business, level of corruption, industry barrier to entry, etc. S&P Global Market Intelligence broadly employs these scores that enhance the granularity of model outputs and statistical model performance.

5 Past performance does not predict future results. As such, statistical models are calibrated on companies that have and have not defaulted

6 By 1 or more notches, up to and including default.
7 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit scores from the credit ratings issued by S&P Global Ratings.

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Credit Analysis
Credit Analytics Case Study Poundworld Retail Ltd


Co-written by Elijah Harden, Risk Services

Aug. 29 2018 — Bankruptcy Summary

Poundworld Retail Ltd (Poundworld) is a discount store operator located in the United Kingdom that on June 11, 2018, while operating around 350 stores, filed for administration in order to work to find a buyer for the chain1. S&P Global Market Intelligence’s Fundamental Probability of Default (Fundamental PD) increased nearly fivefold from 1.69% (an implied credit score of ‘bb-’2), a level that was better than the median general merchandise store in the U.K., to 10.39% (an implied credit score of ‘ccc+’) between fiscal year (FY) 2015 and FY 2016. To summarize, the increased Fundamental PD is similar to a credit score decline from ‘bb-’ to ‘ccc+’. The following year between FY 2016 and FY 2017, the Fundamental PD increased nearly 72% from 10.39% to 17.84% (an implied credit score of ‘ccc-’).

As of the reporting date November 10, 2016 for the period ending March 31, 2016, 19 months before the company filed for bankruptcy, Poundworld fell into ‘ccc’ range and was unable to recover. Poundworld’s inability to recover was due to competing in an increasingly competitive discount retail environment where there was less foot traffic to traditionally populous town centers and exchange rate pressure due to importing goods while the pound was weaker than the dollar3. This resulted in increasingly narrow margins, higher leverage, and decreasing profitability.

Exhibit 1: Fundamental PD Escalation

Business Description

Poundworld operates a chain of discount department stores in the United Kingdom and sells products through its online shop. It offers food and drinks, cleaning and laundry products, health and beauty products, home products, garden and outdoor supplies, pet care products, electrical products, stationery items, toys, baby products, party and gift products, and leisure time products. Poundworld was founded in 1974 and is based in Normanton, United Kingdom.

Fundamental Probability of Default Analysis

The analysis of S&P Global Market Intelligence’s one-year Fundamental PD reveals Poundworld had consistent implied credit scores in the ‘single b’ range for 10 of its 13 reporting periods from FY 2005 to FY 20174. In the time after FY 2012 the volatility of the implied credit scores increased in response to the volatility of Poundworld’s net income. As recently as FY2015, Poundworld, with a PD of 1.69% (implied credit score of ‘bb-‘), sat in the top half of UK general merchandise stores. However, in FY 2016 the company fell into the worst 25% of its UK peers with a PD of 10.39% (implied credit score of ‘ccc+’), roughly a year and a half before filing for administration. Subsequently, in FY 2017, it approached the worst 10% of its UK peers with a PD of 17.84% (implied credit score of ‘ccc’). This shows a notable escalation in risk, both on an absolute basis and with respect to its peers.

The Fundamental PD as of August 16, 2017 for the reporting period ended March 31, 2017 (FY 2017) highlights business and financial risk were significant problems for the company with vulnerable and highly leveraged scores, respectively. The most noteworthy factors contributing to the increased PD were total revenue, profit margin (net income to total revenue), a ratio of how much of every dollar earned is kept within the company, and current liabilities to net worth, a measure of how leveraged the company is/how much debt is used to finance the business. Poundworld experienced a revenue growth rate decline of 57.15% between FY 2015 and FY 2016 from 22.32% to 9.56% with a subsequent decline of 40.88% ultimately ending with a profit margin of 5.65% by FY 2017. As revenue growth for Poundworld slowed, the company became exceedingly leveraged. The average current liability to net worth ratio between FY 2013 and FY 2017 was an extraordinary 667%, signaling the company was unable to pay off debt obligations that were due within a year. In addition to the increasing leverage, Poundworld was battling diminishing profit margins until they eventually became negative, with an average profit margin of -0.02% between FY 2013 and FY 2017. Poundworld’s illiquid position made the company particularly vulnerable to the other operating expenses which totaled approximately £9MM in FY 2016 and FY 2017, which only carried the company closer to the brink of bankruptcy.

Source: S&P Global Market Intelligence as of July 19, 2018. For illustrative purposes only.
Note: Current Liabilities to Net Worth ratio in FY 2017 is actually -1317%, but the model assumes the worst possible profile and assigns the value of 10842%

Source: S&P Global Market Intelligence as of July 19, 2018. For illustrative purposes only.

1 Unless otherwise noted, all information sourced from the S&P Capital IQ platform as of July 24, 2018.
2 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD scores from the credit ratings used by S&P Global Ratings.
3 Source: Financial Times, Poundworld files for bankruptcy, as published on June 11, 2018.
4 Source: S&P Capital IQ platform as of July 24, 2018.

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Credit Analytics Case Study The Bon-Ton Stores, Inc

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Credit Analytics Case Study: Carillion Plc

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Opinion: Look Outside the US for Insurance Blockchain Projects

Aug. 28 2018 — Despite a wealth of conceptual applications for blockchain, U.S. insurers do not appear as engaged with the technology as their counterparts overseas. But if initiatives in Europe and Asia prove successful, U.S. insurers may plunge more deeply into the blockchain waters.

There is no shortage of thought experiments around how blockchain — and distributed ledger technology more broadly — will revolutionize the insurance industry. These include smart contracts, fraud detection, claims prevention, proof of insurance and product authentication. Insurers overseas have made significant progress with blockchain technology, including a consumer application for flight delay insurance and a commercial platform for marine insurance. But activity on the part of U.S. insurers is less apparent.

Conference calls provide a useful barometer for a company's interest in blockchain, as they indicate that executives are thinking about it. When startups try to introduce new technology, one of the common hurdles they cite is a lack of commitment from those with decision-making power at incumbent institutions.

When we published research in April on how U.S. financial services companies are using blockchain, we found roughly 40 transcripts since the start of 2015 from publicly traded U.S. banks that mentioned "blockchain," versus only three from insurance underwriters. Publicly traded banks greatly outnumber insurers in the U.S. But insurers also lagged broker/dealers and asset managers in terms of transcripts, and those sectors each have fewer publicly traded companies than insurance. For this piece, we expanded our transcript analysis to include global insurers, which offered a wealth of information. Many more European insurers discussed their projects than companies in other regions, despite there being about half as many publicly traded insurers in Europe as in the U.S. and Canada region.

One project that caught our attention in the European market was Axa's Fizzy. The flight insurance product uses smart contracts written to the Ethereum blockchain and automatically pays a claim if a passenger's flight is delayed more than two hours. Axa launched Fizzy in September 2017 and at the time offered coverage for only a few routes a day. As of mid-June 2018, Axa had expanded the app to 5% of worldwide routes. But merely the fact that it launched is noteworthy, as many projects from other companies, both in and outside the insurance realm, remain in proof-of-concept mode.

Ping is king

While European insurers collectively discussed blockchain on the most number of conference calls, Chinese insurer Ping An Insurance (Group) Co. of China Ltd. took the top spot in our ranking of individual insurers.

Ping An considers blockchain one of its five core technologies, as executives mentioned during an investor day in November 2017; the others are biometrics, big data, artificial intelligence and cloud computing. One of its main initiatives was the creation of a blockchain-as-a-service platform, which provides services to small and medium-sized enterprises that want access to the latest technology.

Come together

While they might not be as forthcoming about their internal projects, a number of U.S. insurers have discussed their membership in consortium initiatives. One of these is The Institutes RiskBlock Alliance, or RiskBlock for short, which works with underwriters and brokers to develop blockchain applications specifically for the insurance industry. Europe is also home to a consortium that has been generating buzz: Zurich-based B3i. Short for Blockchain Insurance Industry Initiative, B3i began as an industry collaboration but in March announced that it was becoming an actual legal entity, incorporating itself as B3i Services AG.

The bottom line

While it is possible that U.S. insurers are more secretive about their blockchain plans than other industries, they are more likely taking a wait-and-see approach. The fact that insurers in other areas of the world are experimenting with the technology and even launching apps supports this assessment.

Right now seems like a make-or-break moment for distributed ledger technology, as projects across multiple industries are going from proof-of-concept to live implementations. Perhaps if those bear fruit it will compel U.S. insurers to further embrace the technology.

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