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IFRS 9 Impairment How It Impacts Your Corporation And How We Can Help

Power Forecast Briefing Examines How Three Key U.S. Power Markets Are Impacted by Retiring Capacity

Banking & Financial Services

StreetTalk Episode 28: Despite Investor Concerns, KBW CEO Sees More Big Bank M&A

Tesla Contemplates Going Private; But Who Is Going to Power Its Batteries

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

Credit Analysis
IFRS 9 Impairment How It Impacts Your Corporation And How We Can Help

IFRS 9 is a reporting standard for financial instruments that replaces IAS39 (the previous incurred loss standard) with the introduction of provisions for expected credit losses (ECLs) on all financial assets, such as those held to collect contractual cash flows, or held with the possibility of being sold.

The date for adoption was January 1, 2018 and is mandatory for public non-financial corporations (and financial institutions) across a number of jurisdictions outside the United States, including many European countries.

The two key changes introduced by the IFRS 9 accounting standard are:

  • Calculation and provisions must be performed on all affected financial assets, not just the impaired ones, as per the standard it replaces
  • New expected credit loss calculations

Additional challenges will be presented when making assessments for low default asset classes, and companies may find it difficult to access models and sufficient data history.

Impact for non-financial corporations

Non-financial corporations will have some material exposure to many of the financial assets that are defined under IFRS 9. These include investment portfolios, intercompany loans, lease receivables, contract assets, and trade receivables, as illustrated below and further explained in our webinar on IFRS 9 for non-financial corporates.

This, together with the need to assess losses on performing and non-performing assets, might have a material impact on the profit and loss (P&L) of such companies.

ECL calculations under IFRS 9

The IFRS 9 accounting standard introduces new expected credit loss (ECL) calculations that require more data and new models. The key requirements are:

  • Significant increase in credit risk (SICR): Expected loss needs to be assessed at each reporting period to identify a SICR since initial recognition
  • Explicit macro-economic forecasts need to be considered using factors such as the relevant GDP growth, unemployment rate, and stock market index growth figures
  • Credit risk metrics such as probability of default (PD), credit rating, credit score, and loss given default (LGD) need to be adjusted to point in time (PiT), versus through the cycle (TTC)
  • Calculations need to be extended over the lifetime of the assets for underperforming exposures, or in standardized calculations

General versus simplified approach

When performing ECL calculations for trade receivables, the company can choose to take a general or simplified approach (the company is presented with a choice between the two depending on the type of exposure).

  • The general approach uses the 12-month ECL calculation for performing assets (Stage 1 assets) and lifetime calculation for the assets whose creditworthiness has deteriorated since recognition (Stage 2 assets)
  • The simplified approach uses the lifetime ECL calculation for all performing and non-performing assets

The simplified approach can have a bigger impact on P&L expense, as all losses are calculated over the lifetime of the asset, while the general approach can have more impact on P&L volatility, as assets might move between stages incurring 12-month and lifetime calculations.

How S&P Global Market Intelligence can help

A best practice approach used by many financial institutions, which non-financial corporations can also use to comply with the new provision, is to use the existing TTC metrics and convert them into PiT metrics to reflect the current credit cycle, as well as include the required future macroeconomic considerations.

S&P Global Market Intelligence has developed models and tools to help your business undertake the relevant ECL calculations. These models can also be used to assess the creditworthiness of your counterparties and recovery of your exposure in the context of your core business process such as customer credit, supply chain risk, vendor management, and selection and transfer pricing.

The calculation method involves four steps:

  1. We calculate the TTC metric, i.e. the S&P Global Market Intelligence Fundamental PD, CreditModel™ score, for the concerned entity.
  2. We apply our macro-economic model, which weights user defined macro-economic scenarios to produce weighted average forecasted PDs.
  3. We apply a credit cycle adjustment, which converts the TTC risk metric into a PiT PD, leveraging the difference between observed default rates from S&P Global Ratings’ rated universe over last year versus over the past 30+ years.
  4. In addition, as a best practice, we also offer the option to incorporate market-based forward looking information. This is done by further adjusting the PD with the analysis of PD Market Signals country and industry benchmark trends over the past three months versus the past year.

In addition to this quantitative approach available on the Credit Analytics platform, we also offer scorecards that cover low default asset classes for PD, LGD, and point in time adjustments.

Learn More About Credit Analysis
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Watch: Power Forecast Briefing Examines How Three Key U.S. Power Markets Are Impacted by Retiring Capacity

Aug. 17 2018 — Steve Piper shares his analysis of spring and summer power market data plus forecast insights on the Desert Southwest, ERCOT, and PJM. Data and industry guidance is available through the Power Forecast solution on the Market Intelligence platform. The next guidance report will be released around mid-October 2018.

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Listen: StreetTalk Episode 28: Despite Investor Concerns, KBW CEO Sees More Big Bank M&A

Aug. 16 2018 — KBW President and CEO Tom Michaud discussed the disconnect between banks' strong fundamental performance and investors' trepidation toward to the group. The Street has also reacted negatively to a handful of big-ticket bank deals, but Michaud believes large bank M&A activity will pick up.

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Credit Analysis
Tesla Contemplates Going Private; But Who Is Going to Power Its Batteries


Giving investors a bumpy ride, in the last year alone Tesla’s stock fluctuated widely with a 52-week High/Low of 390/245

Tesla’s financials are far less shiny than its showrooms displaying state-of-the-art vehicles

Tesla’s financials are near rock bottom and any further deterioration of financial ratios will have a weak impact on already very high financial risk.

Aug. 15 2018 — Tesla, Inc. (Tesla) is anything but boring. It is revolutionizing the automobile industry with cutting-edge technology, sending cars to Mars, and baffling investors during unconventional earnings calls where Elon Musk, the firm’s CEO, openly argues with analysts. Giving investors a bumpy ride, in the last year alone Tesla’s stock fluctuated widely with a 52-week High/Low of 390/245. Now, the recent announcement that the Tesla board is evaluating taking the company private has perturbed the markets. But, what are the implications for Tesla’s creditworthiness if the company goes private, and how tight should creditors fasten their seatbelts?

Tesla’s financials are far less shiny than its showrooms displaying state-of-the-art vehicles. The company might be eco-friendly, but it is less investor-friendly as it is consistently reporting negative net income whilst piling up debt. Although details on how a possible buyout will be financed are still unknown, taking Tesla private will have a material impact on the credit quality of the company, and any additional debt will put more strain on its financials.

At S&P Global Market Intelligence, as part of the Credit Analytics suite, we developed PD Model Fundamentals (PDFN), which produce probability of default (PD) values over a one- to more than 30-year horizon for public and private corporations of any size. PDFN incorporates both financial risk and business risk to generate an overall PD value. This innovative approach captures, in a statistical PD model, important credit risk drivers and provides users with a well-rounded measure of credit risk, where different risk sources can be easily identified. Business risk encompasses the business and competitive profile of the company using factors such as country risk, industry risk, and company competitiveness. Financial risk is assessed using a number of financial ratios that cover all main credit risk dimensions.

From Public to Private

We assess the PD for Tesla using PDFN Public Corporates and compare it to the output of PDFN Private Corporates. Although the two models are analogous and share the same methodological approach, they are characterized by a slightly different “DNA”. An extensive analysis by S&P Global Market Intelligence demonstrated that the credit quality of public and private companies is driven by a comparable set of risk dimensions, but slight differences were identified in the financial ratios that provide the highest explanatory power to assess credit quality.

These differences reflect the inherent distinction between the two organizational types. Public companies must operate with a higher degree of transparency and are under constant scrutiny by investors, but enjoy more open access to capital markets. Private companies, on the other hand, are not required to disclose their financial information and can operate more freely, but are more restricted in their financing options, relying on private funding.

In Table 1, we compare risk drivers of PDFN Public Corporates and PDFN Private Corporates and estimate the one-year PD for Tesla using the last 12 months of data. The results of both models provide a consistent narrative. Tesla’s business risk is fair, but weak financials materialize in a very high financial risk, driving up the PD.

Estimated PD is notably higher if Tesla is treated as a private company, consistent with the notion that private companies have more limited access to capital markets should they need it to support their operations. PDFN also maps the numerical PD values to an S&P Global Market Intelligence credit score (i.e. ‘bbb’). These scores are based on historical observed default rates (ODRs) extracted from the S&P Global Ratings’ database (available on CreditPro®)1 . Similarly, the higher PD in the PDFN Private Corporates model is reflected as a one notch worse estimate of the credit risk score.

Table 1: Overview of PD Model Fundamentals and credit risk assessment of Tesla

Source: S&P Global Market Intelligence, as of August 8, 2018. For illustrative purposes only.

What-if Analysis

PDFN is equipped with analytical tools such as contribution analysis, which allows users to identify drivers of risk in absolute or relative terms, and sensitivity values, which help users assess how susceptible the PD estimate is to the underlying changes of risk drivers. In Figure 1, we rank the absolute contribution and the sensitivity of risk drivers in PDFN Private Corporates. Financial risk factors (blue circles) are important contributors to the PD estimate, as denoted by their absolute contributions. However, the sensitivity of the PD to additional changes of financial ratios is low. In the language of a statistical model, Tesla’s financials are near rock bottom and any further deterioration of financial ratios will have a weak impact on already very high financial risk.

In comparison, the absolute contribution of business risk factors (red circles) is mixed. Some, like efficiency and size, already significantly contribute to the credit score, whilst the impact of country and industry risk remains minor. Importantly, however, the sensitivity of business risk factors is high, implying that any deterioration of these factors will have a meaningful impact on the credit score.

Figure 1: Overview of absolute contribution and sensitivity of credit risk drivers for Tesla

Source: S&P Global Market Intelligence (as of August 8, 2018). For illustrative purposes only.

To probe possible effects of Tesla going private, we conducted a hypothetical sensitivity analysis of Tesla’s credit score. Using PDFN Private Corporates, we assessed the impact of an additional $10bn of debt financed at a current market rate of 7.4% yield to maturity (YTM) on Tesla’s 2025 bond (to carry out a full buyout Tesla might need up to $70bn). This amount of additional debt would double the current debt level and, correspondingly, increase interest expenses. We adjust affected financial ratios accordingly, whilst keeping other financials (such as revenues) unchanged. The increase in the estimated one-year PD is demonstrated in Figure 2. Although the increase in debt is considerable in nominal and relative terms, the effect on the estimated PD is minor. In other words, Tesla already has a sizeable amount of debt, is low on cash, and its debt service capacity is severely restricted, all resulting in very high financial risk.

Tesla’s credit score is highly sensitive to adverse changes in business risk factors. For example, deterioration of market conditions in the automobile industry and increased country risk can significantly affect Tesla’s creditworthiness. By additionally adjusting country risk and industry risk for one category (country risk from ‘aaa’ to ‘aa’ and industry risk from ‘moderately high risk’ to ‘high risk’), we can gauge the effect of such adverse changes in the business risk environment. Although absolute contribution of these two factors is low, their high sensitivity results in a substantial increase of the estimated PD, as depicted in Figure 2.

To get a final comprehensive assessment, we scale the stressed PD 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. In that manner, PDFN long-term or Through-the-Cycle (TTC) PD is further adjusted upwards to reflect the actual Point-In-Time (PIT) PD of the business cycle.

Figure 2: Credit risk profile of Tesla

Source: S&P Global Market Intelligence (as of August 8, 2018). For illustrative purposes only.

Bottom Line

PD Model Fundamentals enables a comprehensive overview of a company's creditworthiness. The combination of both financial risk and business risk factors supports an in-depth review of a company's credit risk profile to identify and distinguish the main sources of risk. The model inputs can be easily adjusted to perform sensitivity analysis for selected financial ratios or to conduct a comprehensive stress-test exercise using a fully-adjusted set of financials. Applying an additional Credit Cycle Adjustment overlay helps clients adjust long-term risk assessments provided by statistical models for the current PIT within the business cycle to serve their research purpose or to comply with new accounting requirements, such as IFRS 9 and CECL.

As for Tesla, its batteries are running low, and a strong and continuous supply of fresh financing will be vital on the road ahead to provide sufficient room and time to materialize its projects and turn a profit. Currently, financial risk is already high and a supportive business environment allows Tesla to carry on without slowing down. However, high sensitivity to changes in business risk factors means adverse changes could stop Tesla dead in its tracks. This bears an important lesson should Tesla's board choose to take Tesla private and strain its financials further, disregarding the risks of adverse changes in the business environment.

S&P Global Market Intelligence leverages leading experience in developing PD models to achieve a high level of accuracy and a robust out-of-sample model performance. The integration of PDFN into the S&P Capital IQ platform allows users to access a global pre-scored database with more than 45,000 public companies and almost 700,000 private companies, obtain PD values for single or multiple companies, and perform a scenario analysis.

Learn more about S&P Global Market Intelligence’s Credit Analytics models.

1S&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.

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

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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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