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Credit Analysis

Beyond Amazon, Alibaba Leads Disruptive Innovation In Race To $1 Trillion Valuation

C&I Loan Growth Pops In Q2, But Tax Reform’s Role Remains Unclear

Banking

StreetTalk Episode 27: Looking For The Cream Of The Crop In Bank Stocks

Loans And Deposits Continue Uphill Climb At US Banks In June

Peeking Into The Future Without Staring At A Crystal Ball: Brexit Scenarios And Their Impact On Energy Firms’ Credit Risk

Credit Analysis
Beyond Amazon, Alibaba Leads Disruptive Innovation In Race To $1 Trillion Valuation

Mar. 20 2018 — The race to become the first trillion dollar company is heating up, with everyone paying close attention to the tech mega-caps — Alibaba Group Holdings Ltd. (NYSE: BABA) and Amazon.com Inc. (NASDAQ: AMZN).

Despite a lack of consensus over who will take the crown, one thing is evident: no two companies in the race are as neck and neck and as similar in business strategy and operations as Amazon and Alibaba. Both champion the e-commerce landscape in their specific countries – Amazon in the U.S. and Alibaba in China - and both have made their forays into new industries such as food and healthcare.

Wall Street is following these companies closely, with Alibaba slightly in the lead in terms of analyst recommendations. As of April 2, 2018, the Chinese e-commerce behemoth has received 37 buy ratings and just two hold, according to S&P Global Market Intelligence data. The average analyst price target of $226.44 suggests upside potential of roughly 23%. Amazon, in contrast, has received 31 buy ratings and two hold. The average analyst price target of $1,709.05 suggests upside potential of roughly 18%.

To keep a tally of the race, we used the RatingsDirect® Monitor, a data visualization portfolio monitoring tool that provides risk/return insights and helps track and analyze market movements for publicly-traded companies that are rated by S&P Global Ratings.

Figure 1: Tech Mega-Caps: S&P Issuer Credit Rating (FCLT) vs. 3M Stock Price Volatility (%)

Tech mega-caps: S&P Issuer Credit Rating (FCLT) vs. 3M Stock Price Volatility (%)

For illustrative purposes only.

At a market cap of $471.6 billion, Alibaba is not too far off from catching up to Amazon’s $700.7 billion cap. Alibaba stock’s price has observed a three-month price volatility of 40.1%, the largest among the tech titans and far surpassing Amazon’s 30.8%.

Although the higher volatility and lower S&P Global Ratings’ long-term credit rating present more risks for investors, Alibaba’s higher return on assets and lower P/E and leverage ratio suggest more opportunities for the Chinese e-commerce behemoth to grow and reach the $1 trillion valuation first.

Comparing disruptive levels of innovation

To compare the disruptive level of innovation in the various sectors that Amazon and Alibaba have entered, we selected comparable events between the two conglomerates and examined industry-level probability of default (PD) changes of the PD Market Signal Model, a structural model that calculates the likelihood of a company defaulting on its debt or entering bankruptcy protection over a one-to-five year horizon.

The war for groceries

Both Amazon and Alibaba have been stepping up their battle in the grocery business. Just last year, Amazon’s announcement to purchase Whole Foods Market Inc. for $13.7 billion shocked investors, with shares of some of U.S. food’s largest players – Kroger Co. Supervalu Inc., Costco Wholesale Corp., Target Corp., and Wal-Mart Stores Inc. – dipping on the news. The market perceived credit risk of the U.S. food retail industry also escalated. One week following the announcement, the U.S. food retail PD jumped from 3.73% on June 15, 2017 to 4.85% on June 23, 2017, or about a 30% increase in the industry’s probability of default.

Figure 2: U.S. Food Retail Median Market Signal Probability of Default: June 15, 2017 – June 23, 2017 (%)

U.S. food retail median Market Signal Probability of Default: June 15, 2017 – June 23, 2017 (%)

Alibaba also aggressively expanded its food footprint in 2017 with its rollout of new supermarkets under the Hema Xiansheng brand and its $2.9 billion investment in China’s largest hypermarket operator Sun Art Retail Group. Just this year, reports that Alibaba held early development talks with Kroger Co. left the Chinese food industry shaking. One week following reports of the discussions by Reuters and New York Post, China’s food retail PD increased 109.10% from 3.05% on January 23, 2018 to 6.39% on January 31, 2018. [i] [ii]

Figure 3: China Food Retail Median Market Signal Probability of Default: January 23, 2018 – January 31, 2018 (%)

China food retail median Market Signal Probability of Default: January 23, 2018 – January 31, 2018 (%)

The battle for pharma

Pharmaceuticals have been another potential battleground for the e-commerce giants.

According to an October 5, 2017 note published by Leerink Partners managing director Dr. Ana Gupte, Amazon is “hiring relevant talent and are in active discussions with mid-market PBMs [pharmacy benefit managers] and possibly even larger players such as Prime Therapeutics.” Following publication of the note, the U.S. drug retail PD escalated 22.55% from 16.16% on October 4, 2017 to 19.81% on October 12, 2017.

Figure 4: U.S. Drug Retail Median Market Signal Probability of Default: October 4, 2017 – October 12, 2017 (%)

U.S. drug retail median Market Signal Probability of Default: October 4, 2017 – October 12, 2017 (%)

Similarly, China’s drug retail PD jumped 90.67% from 1.55% on February 1, 2018 to 2.96% on February 9, 2018, following Alibaba’s February 2, 2018 announcement to partner with European pharma giant AstraZeneca PLC.

Figure 5: China Drug Retail Median Market Signal Probability of Default: February 1, 2018 – February 9, 2018 (%)

China drug retail median Market Signal Probability of Default: February 1, 2018 – February 9, 2018 (%)

The risks of innovation

In summary, our PD Market Signal model shows that Alibaba disrupts the short-term market perceived credit quality of firms more than Amazon does. The Chinese e-commerce behemoth is viewed by many investors as a proxy for China's consumer economy and growing middle class, whereas Amazon is not, and PD movements are reflective of this. As illustrated by our RatingsDirect® Monitor, Alibaba has a much lower leverage compared to Amazon, with a last-twelve-months Debt/EBITDA ratio of 1.4, compared to Amazon’s 2.9. Alibaba also has higher growth potential from the perspective of ROA and P/E. Alibaba’s ROA stands at 7.4%, compared to Amazon’s 2.4%. Further, Alibaba’s lower P/E ratio of 46.3, compared to Amazon’s 235.3, suggests that the Chinese firm may be undervalued.

Figure 6: Tech Mega-Caps: ROA (%) vs. Debt/EBITDA (x)

Tech mega-caps: ROA (%) vs. Debt/EBITDA (x)

For illustrative purposes only.

Figure 7: Tech Mega-Caps: ROA (%) vs. P/E Ratio (x)

Tech mega-caps: ROA (%) vs. P/E Ratio (x)

For illustrative purposes only.

Whether Alibaba will claim the $1 trillion title before Amazon, however, remains to be seen. A fast growing company, Alibaba faces significant challenges from China’s ever-changing business environment, including potential regulatory, litigation, and international expansion risks, as outlined in roughly 45 pages of the firm’s most recent annual report.

Despite the inherent risks, what sets Alibaba apart is its domination of China’s online marketplace, which is the single-largest in the world. Founder Jack Ma has also been faster than Bezos to expand his business lines. The use of Alipay, one of the world’s largest mobile payment platforms, and the firm’s roughly $350 million investment in Chinese electric-vehicle maker Foxconn Technology Group are just a few examples of the firm’s growing economies of scale.

[i] Alibaba, U.S. grocer Kroger had early business development talks: source. (n.d.). Retrieved March 01, 2018, from https://www.reuters.com/article/us-kroger-alibaba/alibaba-u-s-grocer-kroger-had-early-business-development-talks-source-idUSKBN1FE0EF

[ii] To battle Amazon, Kroger eyes Alibaba alliance. (n.d.). Retrieved March 01, 2018, from https://nypost.com/2018/01/24/krogers-answer-to-amazon-go-alibaba/

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Banking & Financial Services
C&I Loan Growth Pops In Q2, But Tax Reform’s Role Remains Unclear

Jul. 31 2018 — Business loan growth popped in the second quarter, but bankers are hesitant to attribute the jump to tax reform or a broader turnaround in business spending.

The year-over-year increase in commercial-and-industrial loans increased to more than 5% for all banks in June, the highest figure in more than a year, according to Federal Reserve data. Smaller U.S. banks — defined by the Fed as those outside the 25 largest banks — posted double-digit growth for all three months of the second quarter.

Those numbers were artificially inflated by banks' acquisition of $24.9 billion of C&I loans from nonbanks. Accounting for those one-time acquisitions, organic C&I loan growth for smaller banks was still robust at 7% in June.

Ever since Republicans passed tax reform at the end of 2017, business optimism has been high and bankers have been hopeful the sentiment will trigger a rebound in business loan growth. C&I loan growth was less than 1% when tax reform passed.

Though C&I loan growth enjoyed a significant bounce in the second quarter, several bankers were not declaring victory. Numerous bank executives attributed the jump to an increase in merger-and-acquisition activity, not increased business spending.

M&T Bank Corp. said M&A activity was hurting its average loan growth, which declined by less than 1% on a quarter-over-quarter basis. The bank's CFO said businesses are selling significant assets and using the proceeds to pay down their loans.

One bank did say tax reform was boosting loan growth. SunTrust Banks Inc. reported an increase in the second quarter for its average performing loans figure, a turnaround from the first quarter when the figure declined on a linked-quarter basis.

"I think we are starting to see some of that [benefit from tax stimulus]," said Chairman and CEO William Rogers Jr. in the bank's earnings call.

But Rogers appeared to be in the minority. Several bankers said it was too early to tell whether tax reform was playing much of a role in the C&I loan growth. JPMorgan Chase & Co. reported a 3% quarter-over-quarter increase in its C&I loans in the second quarter and attributed the gain to M&A financing, not tax reform.

"We've yet to see the full effect of tax reform flow through into profitability and free cash flow," Lake said during the bank's earnings call.

Some bankers, including JPMorgan CEO Jamie Dimon, pointed to brewing trade wars as potential headwinds to loan growth.

Tariffs and trade-related issues are "probably the primary concern that we're hearing from customers right now," said Comerica Inc. President Curt Farmer.

Jeff Rulis, an analyst with D.A. Davidson, said he was not even sure the second-quarter C&I loan growth figures represented a notable change.

"I'm not convinced we're seeing a turnaround or significant pick-up. You have to take into account seasonal pick-up, and the first calendar quarter is generally slow," he said.

There is an argument that tax reform might actually be dampening loan growth. Rulis attributed high payoffs to the mixed results across the sector with some banks reporting robust loan growth by taking market share, contributing to others' more marginal results. Businesses are having an easier time making those payoffs thanks to tax reform, which freed up capital to pay down debt.

"One of the disadvantages of tax reform is you've both lowered the corporate tax rate and repatriated assets to the U.S. That's given more liquidity to the borrowers," said Peter Winter, an analyst with Wedbush Securities.

Year-over-year increases for total loans were up modestly, as weak commercial real estate loan growth moderated the gains from C&I. The 25 largest banks, in particular, reported soft commercial real estate loan growth with year-over-year declines in March, April and May — the first such drops since 2013. Several banks reported an intentional pullback from the sector due to credit quality concerns. Some pointed to nonbank competition as being particularly aggressive on both pricing and deal structure.

"I think banks, for the most part, are showing more credit discipline coming out of the financial crisis," Winter said. "Quite honestly, we're nine years into this recovery, so I think that's a prudent thing to do."

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Listen: StreetTalk Episode 27: Looking For The Cream Of The Crop In Bank Stocks

Jul. 30 2018 — Joe Fenech, head of equity research at Hovde Group, discussed current bank stock valuations, the growing importance of deposits in valuing franchises and the market's increased skepticism toward M&A, including transactions that appear favorable for the buyer.

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Banking & Financial Services
Loans And Deposits Continue Uphill Climb At US Banks In June

Jul. 26 2018 — Average total loans and leases at U.S. commercial banks increased by $44.10 billion to $9.347 trillion in June, according to the Federal Reserve's July 13 H.8 report.

Loan growth was driven primarily by a $19.8 billion increase in commercial and industrial, a $9.4 billion jump in real estate and an $8.3 billion increase in commercial real estate.

Average loans and leases at large commercial banks increased $18.7 billion month over month, while average loans and leases at small commercial banks were up $21.7 billion. Loans and leases at foreign-related institutions increased by $3.4 billion.

Meanwhile, average total deposits at U.S. commercial banks increased by $56.4 billion in June, compared to a $35.4 billion increase in May. Total deposits were up $448.4 billion from June 2017.

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Credit Analysis
Peeking Into The Future Without Staring At A Crystal Ball: Brexit Scenarios And Their Impact On Energy Firms’ Credit Risk

Jul. 24 2018 — After so many years of living and working in London, two years ago I applied for, and was finally granted, British citizenship. Imagine my surprise when, a few weeks later, the UK European Union referendum took place and the majority of voters opted for Brexit!

As a dual national, both European and British, I feel twice the pain of an uncertain future and sometimes I wish I had a crystal ball.

While it is hard to predict how the whole separation process will pan out, S&P Global Market Intelligence offers a new statistical model that allows users to understand how firms’ credit risk on either side of the ocean may change under multiple exit scenarios. The Credit Analytics Macro-scenario model covers the United States, Canada and European Union countries plus the United Kingdom (EU27+1). In addition, the model can be run via the S&P Global Ratings’ Economists macro-economic multi-year forecasts, tailored for this specific model and updated on a quarterly basis.1

Figure 1 shows the Economists’ forecasts of the inputs used in our statistical model for EU27+1, for year-end 2018, 2019 and 2020.

Source: S&P Global Market Intelligence (as of June 2018). For illustrative purposes only. L/S ECB Interest rate spread is the spread between long-term and short-term ECB interest rates. Y-Axis is % of; GDP Growth, Stoxx50 Growth, Interest Rate Spread or FTSE100 Growth, depending on the correlating symbol as described in the key.

The expectation is for economic growth to slow-down in the EU27+1. This will be accompanied by progressive monetary policy tightening and a volatile performance of the stock market index growth. This view is aligned with the baseline scenario included in the European Banking Authority (EBA) and the Bank of England (BoE) 2018 stress testing exercise that “[…] reflects the average of a range of possible outcomes from the UK’s trading relationship with the EU”.2

Figure 2 shows the evolution of the median credit score of Energy sector (left panel) and Utility sector (right panel) large-revenue companies in EU27+1, obtained by running the economists’ forecasts via the Macro-scenario model.3 The median score for 2017 is generated via S&P Global Market Intelligence’s CreditModelTM 2.6 Corporates, a statistical model that uses company financials and is trained on credit ratings from S&P Global Ratings.4 The model offers an automated solution to assess the credit risk of numerous counterparties, globally. The scores are mapped to a numerical scale where, for instance, bb- (left panel, left scale) is mapped to 13.0; a deterioration by 1 notch corresponds to an increase of one integer on the numerical scales.

Figure 2: Evolution of the median credit score of Energy and Utility sector companies in EU27+1, based on S&P Global Economists’ macro-economic forecasts run via the Macro-scenario model.

Source: S&P Global Market Intelligence (as of June 2018). For illustrative purposes only.

Starting from 2017, we see a higher level of credit risk in the UK (red line) than in EU27 (blue line); in subsequent years, the median credit risk increases on both sides of the Channel but the “risk fork” between the UK and EU27 tends to widen up at the expenses of the UK, for both sectors.5

Despite the fact that the median credit score may not change sizably between 2017 and 2020, remaining below half a notch overall in all cases, it is worth keeping in mind that the probability of default (PD) associated with a credit score changes in line with the economic cycle, and thus increases (decreases) during periods of contraction (expansion).

In our model, we account for this effect by first mapping the credit score output to a long-run average PD; next we scale it via a “Credit Cycle Adjustment” (CCA) that looks at the ratio between the previous year and the long-run average default rate historically experienced in S&P Global Ratings’ rated universe.6 If we adjust the long-run average PD via the CCA, we can easily identify potential build-up of default risk pockets in different countries within the EU27+1 as time evolves, as shown in the animations within Figure 3. Green refers to a lower PD than 2017, orange refers to a higher PD than 2017, and red refers to a PD breaching a pre-defined threshold (4.5% for Energy Sector and 0.3% for Utilities sector).7

Figure 3: Potential pockets of default risk in Energy and Utility sector companies in EU27+1, based on S&P Global Economists’ forecast.

Energy Sector Utility Sector
Default Risk in Energy map Default Risk in Utilities map

Source: S&P Global Market Intelligence (as of June 2018). For illustrative purposes only. Green refers to a lower PD than 2017, orange refers to a higher PD than 2017, and red refers to a PD breaching a pre-defined threshold (4.5% for Energy Sector and 0.3% for Utilities sector).

With the Macro-scenario model, we aimed for a user friendly model, and took into account the strong economic ties within EU27+1, the existence of a common market and the circulation of a shared currency in the majority of the EU countries, in order to select a parsimonious yet statistically significant set of inputs (just imagine otherwise forecasting multiple macro-economic scenarios for 28 individual countries, over multiple years).8

Readers may wonder how the model differentiates the evolution of credit risk by country if it uses a limited set of aggregate macro-economic factors (e.g. EU28 GDP growth, etc.) across EU27+1. Nine separate sub-models were actually optimized, based on economic commonalities and historical evolution of the S&P Global Ratings transitions in those countries, to account for the existence of different EU “sub-regional” economies (for instance Nordic countries as opposed to Eastern European countries). For the UK, we went one step further, by explicitly including a market indicator, the FTSE100, as a precautionary measure given a potential “full decoupling” of EU27 and UK economies in the near future.

Well, so far so good, at least in the case of a “soft” Brexit! But what if we end up with a “hard” Brexit?

The EBA and the BoE 2018 stress testing exercise include a stressed scenario that “[…] encompasses a wide range of economic risks that could be associated with {hard} Brexit”.9 The scenario corresponds to a prolonged recessionary period, with negative GDP growth for several years and a generalized collapse of the stock markets, similar to what happened during the 2008 global recession. Unsurprisingly, the median credit score output by our macro-scenario model companies significantly deteriorates for both Energy and Utility sector. Figure 4 shows the build-up of potential default risk pockets and their evolution over time, under stressed economic conditions, depicting a bleak view over the length of time needed for a recovery of these sectors.10

Figure 4: Potential pockets of default risk in Energy and Utility sector companies in EU27+1, based on EBA’s and BoE’s 2018 stressed scenario.

Energy Sector Utility Sector
Default Risk in Energy map Default Risk in Utilities map

Source: S&P Global Market Intelligence (as of June 2018). For illustrative purposes only. Green refers to a lower PD than 2017, orange refers to a higher PD than 2017, and red refers to a PD breaching a pre-defined threshold (4.5% for Energy Sector and 0.3% for Utilities sector).

I do not have yet a crystal ball to predict the future, e.g. whether petrol will cost more or less, or whether I will be paying higher utility bills in the UK as opposed to (the rest of) the European Union, but S&P Global Market Intelligence’s Macro-Scenario allows gauging potential credit risk changes in individual countries, under a soft or a hard Brexit scenario. More in general, the Macro-Scenario model offers a quick, scalable and automated way to assess credit risk transitions under multiple scenarios, thus equipping risk managers at financial and non-financial corporations with a tool that enables them to make decisions with conviction.

Notes

1 The macro-economic forecasts will become available on the S&P Capital IQ platform from 2018Q4. S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence.

2 Source: “Stress Testing Exercise 2018” available at http://www.eba.europa.eu/risk-analysis-and-data/eu-wide-stress-testing/2018. The baseline scenario is the consensus estimate among EU27+1 Central Banks.

3 The results of this analysis depend on the portfolio composition. In addition, other industry sectors may react differently from the Energy and Utility sectors.

4 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.

5 The 2017 median score for the Utility sector is better than the score for the Energy sector, due to the inherently higher risk of companies in the latter.

6 An optional market-view adjustment is available within the macro-scenario model. In our analysis, we did not include this adjustment, for the sake of simplicity.

7 4.5% (0.3%) is close to the historical long-run average default rate of companies rated B- (BBB-) by S&P Global Ratings.

8 This is also one of the reasons we found it unnecessary to include oil price for the modelling of credit risk of the energy sector in EU27+1, as we found the stock market growth was sufficient.

9 Source: “Stress Testing Exercise 2018” available at http://www.eba.europa.eu/risk-analysis-and-data/eu-wide-stress-testing/2018. The baseline scenario is the consensus estimate among EU27+1 Central Banks. Curly brackets refer to the author’s addition.

10 We adopt the same colour conventions as in Figure 3.

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