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Analytical Credit Risk Case Studies

Our credit and risk specialists leverage Credit Analytics, our suite of cutting-edge analytical models to provide you with credit risk insights and real-life case studies on the topics that are important to you and your business.

• on this page

Market Volatility

Customer risk, supply chain, industry assessment, transfer pricing.

We’ve recently experienced some of the most extraordinary events in our lifetime, a full year of the Russia-Ukraine conflict, global monetary interventions to fight one of the most significant inflations in recent history, and a continuing threat from global COVID containment policies that continue to disrupt supply chains today.

It goes without saying that the importance of monitoring and embedding macroeconomic factors into credit risk assessments is critical.

Read the results from our recent research where we assessed the credit risk of 22 industry sectors (Corporates and Banks) in the United States and compare historical trends based on the probability of default score generated by the RiskGauge™ Model, with forecasted trends based on this score conditioned with macroeconomic scenarios.

READ THE FULL REPORT

The Continued Evolution of Credit Risk in the European Union and the United Kingdom

Anticipate the Unknown: Insights to Turn Market Risks into Business Opportunities

European Industries Most Impacted by the Russia-Ukraine War from a Probability of Default Perspective

A Fundamentals Approach to Detect Early Signs of Private Company Credit Deterioration

Go Beyond Fundamentals to Uncover Early Signs of Private Company Credit Deterioration

Credit Score Implications of Russia-Ukraine War

Silicon Valley Bank: Uncovering Regional Bank Stress with Equity-Driven Credit Models

It’s different this time: a banking rhyme, how to assess risk appetite in trade credit, bed bath and bankruptcy using quantitative credit models to predict corporate defaults.

Christopher & Banks Corporation – tracking the early-warning signals of credit risk

Default Insights: Avianca Holdings S.A. - Tracking the early warning signals of credit risk

SAS AB Tracking the early-warning signals of credit risk

Car rental industry’s credit risk: a bouncy ride during the pandemic

Understanding Drivers of Credit Risk: Differences and Similarities in the Credit Risk Assessment of a Non-Financial Corporation via a PD Scoring Model

Tracking Credit Risk of a Major U.S. Retailer

In the past, only large financial institutions have ventured into deploying credit risk automation and workflow systems due to the volume of resources and investments required and the need to lock down processes. However, it is not uncommon today, to meet with a corporate credit risk officer who is looking to discuss the options, benefits, and risks of automating customer onboarding and credit risk management and monitoring processes.

Read about the risks and opportunities of credit risk automation here.

READ THE BLOG

Data That Delivers: Automating the Credit Risk Workflow

Machine Learning and Credit Risk Modelling

Managing Credit Risk Automation during Economic Uncertainty

Get a deeper view of your credit risk exposure.

Continuous financial health management of suppliers, minimizing counterparty risk in supply chains, gauging supply chain risk in volatile times, covid-19’s wake-up call for supply chain credit risk.

SEE THE FULL BLOG

Corporate Credit Risk Macroeconomic Recovery Projections Post-COVID-19

In the U.S., continuous government stimulus payments and efficient vaccine rollouts have further revived both supply and demand for goods and services. However, although public companies began publishing financial reports for the second quarter of 2021, the results did not show the full extent of the global recovery, due to the intrinsic lag effect of financial performance.

To help navigate these transition times, we used our Macro-Scenario model to analyze how the credit risk of public and private firms in the U.S. may change under different macroeconomic projections.

Highlights include:

• The degree of economic recovery in different industries is mostly driven by the characteristics of post COVID-19 positive macroeconomic projections.
• Energy, industrial products, and construction materials, as well as retail and media industries, exhibit the best recovery over the Q1 2022 outlook when compared with the baseline scenario.
• The real estate and construction materials industries also show strong recovery and transition in credit risk.

The Bankruptcy Outlook and a Trifecta of Factors: Global Risk, Inflation, Rising Rates

COVID-19: Company Fundamental Scars and the Path to Recovery in Asian Economies

Corporate Credit Risk Trends in Developing Markets An Expected Credit Loss ECL Perspective

Corporate Credit Risk Trends in Developing Markets: A Probability of Default Perspective

Uncertainties Impact Credit Risk in the European Union and the UK

How to Take Control of Intercompany Financing

A large accounting firm automates its credit assessments for transfer pricing, successfully navigating the complexity of intercompany financing, law firm leverages scorecard approach to support transfer pricing engagements.

Credit Risk Analysis Using EDA

• Conference paper
• First Online: 16 September 2022
• Cite this conference paper

• Prakriti Arora 14 ,
• Siddharth Gautam 15 ,
• Anushka Kalra 16 ,
• Ashish Negi 14 &
• Nitin Tyagi 14  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 490))

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Organizations or banks are providing funds to support people monetarily, keeping assets in return till the amount is repaid to the company with interest encounter loss at many instances when the borrower or the client fails to repay the loan appearing to be a defaulter. Also, when the firm disapproves the loan of an applicant who is likely to repay the sum, the loss is again withstood by the firm. Therefore, to avoid this loss, this research is performed deeply analyzing the factors using exploratory data analysis, affecting the trend of defaulters as well as non-defaulters, helping the firm recognize the defaulters, and disapproving their request to borrow. The exploratory data analysis is performed by visually performing univariate, bivariate, and multivariate analysis on almost all the aspects of the two credit history datasets. The patterns and learnings were noted based on the visual as well as statistical analysis to determine creditworthiness of a client.

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Arora, P., Gautam, S., Kalra, A., Negi, A., Tyagi, N. (2023). Credit Risk Analysis Using EDA. In: Dutta, P., Chakrabarti, S., Bhattacharya, A., Dutta, S., Shahnaz, C. (eds) Emerging Technologies in Data Mining and Information Security. Lecture Notes in Networks and Systems, vol 490. Springer, Singapore. https://doi.org/10.1007/978-981-19-4052-1_56

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This case study aims to give you an idea of applying EDA in a real business scenario. In this case study, apart from applying the techniques that you have learnt in the EDA module, you will also develop a basic understanding of risk analytics in banking and financial services and understand how data is used to minimise the risk of losing money w…

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Folders and files, repository files navigation, credit_eda_case_study_upgrad.

This case study aims to give you an idea of applying EDA in a real business scenario. In this case study, apart from applying the techniques that you have learnt in the EDA module, you will also develop a basic understanding of risk analytics in banking and financial services and understand how data is used to minimise the risk of losing money while lending to customers.

Business Understanding

The loan providing companies find it hard to give loans to the people due to their insufficient or non-existent credit history. Because of that, some consumers use it as their advantage by becoming a defaulter. Suppose you work for a consumer finance company which specialises in lending various types of loans to urban customers. You have to use EDA to analyse the patterns present in the data. This will ensure that the applicants capable of repaying the loan are not rejected. When the company receives a loan application, the company has to decide for loan approval based on the applicant’s profile. Two types of risks are associated with the bank’s decision:

If the applicant is likely to repay the loan, then not approving the loan results in a loss of business to the company

If the applicant is not likely to repay the loan, i.e. he/she is likely to default, then approving the loan may lead to a financial loss for the company.

The data given below contains the information about the loan application at the time of applying for the loan. It contains two types of scenarios:

The client with payment difficulties: he/she had late payment more than X days on at least one of the first Y instalments of the loan in our sample,

All other cases: All other cases when the payment is paid on time.

When a client applies for a loan, there are four types of decisions that could be taken by the client/company):

Approved : The Company has approved loan Application

Cancelled : The client cancelled the application sometime during approval. Either the client changed her/his mind about the loan or in some cases due to a higher risk of the client he received worse pricing which he did not want.

Refused : The company had rejected the loan (because the client does not meet their requirements etc.).

Unused offer : Loan has been cancelled by the client but on different stages of the process.

In this case study, you will use EDA to understand how consumer attributes and loan attributes influence the tendency of default.

Business Objectives

This case study aims to identify patterns which indicate if a client has difficulty paying their installments which may be used for taking actions such as denying the loan, reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc. This will ensure that the consumers capable of repaying the loan are not rejected. Identification of such applicants using EDA is the aim of this case study.

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ESG, credit risk and ratings: part 3 - from disconnects to action areas

• 1 Executive summary
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Case study: HSBC Global Asset Management

2019-01-30T17:49:00+00:00

Case study by HSBC Global Asset Management 

Action areas:

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The investment approach

We believe that ESG issues can have a long-term material impact on company fundamentals, and that they are linked to opportunities and risks which financial markets may not price appropriately.

The integration of ESG factors within our investment process is led by the FI investment team and is not a standalone process. The team comprises 177 members who rely on the support of the Global Credit Research platform, comprising 46 sector and regional analysts including 11 ESG champions, and a separate team of ESG specialists who support the process by providing ESG data, sector knowledge and thematic research.

The current approach is the result of a process (see below) starting in 2002 with the launch of our first sustainable fund. We integrated ESG factors more systematically across our FI process starting in 2007, using external ESG data providers for our research and analysis.

ESG integration throughout the investment decision-making process

Source: HSBC Global Asset Management 

Taking the learnings from managing successful sustainable funds, backed by analytical research showing that considering ESG factors is beneficial to the investment process and rarely has a negative impact, we reviewed our process in 2017 and subsequently reinforced our ESG integration and engagement process. This involved the launch of a FI ESG thematic “university” to promote awareness, training and guidance on ESG subject matter, and recruiting a dedicated FI responsible investment advisor.

The investment process

The investment process starts with the selection of our investment universe, involving issuer-level screening in line with our controversial weapons exclusion policy and any other client or strategy exclusions.

We then consider the composite ESG score and summary for each issuer provided by our global ESG database, using data from third-party ESG data providers. The highest-risk names per sector (categorised by emerging and developed markets) are highlighted in the database and require a more detailed level of due diligence by the credit research team before any investment.

Our fundamental research framework for all companies incorporates ESG analysis as specific inputs, including a business profile detailing components of management, governance and strategy, and liabilities (legal, social and environmental). This analysis highlights – firstly and most importantly – any potential negative impacts on the operating profile of the company and, secondly, financial metrics such as revenue and debt/EBITDA. This is supplemented with issuer meetings by the credit research team where further ESG questions specific to the issuer or sector are raised.

CRA reports and external ratings are one of many inputs into our credit analysis, but we do not rely solely on them; in fact, we produce our own proprietary credit ratings. However, we use external credit ratings to define investment universes for funds and mandates. They are also among the second-party certifiers of green bonds we use for green bond assessment.

The credit process ensures we only select issuers whose operating and financial metrics we are comfortable with and exclude those that are viewed as unreliable or have potential idiosyncratic risks. The credit analyst approves each issuer with oversight from the Global Head of Credit Research.

Credit analysts communicate directly with their investment colleagues globally at sector and country level as well as through groups such as the ESG Analyst Group that communicates and shares ESG sector-level research, investment views and engagement findings between analysts in the credit and equity teams. One of the group’s main outputs of 2018 was the production of 24 ESG sector checklists, summarising each industry’s ESG issues and suggesting engagement questions, enabling analysts to focus on the most financially-material dimensions for credit. We monitor engagement activities on a quarterly basis, covering the contact that we have with issuers to ensure that we raise ESG-related questions with them and share our findings across the investment platform. We also monitor funds’ ESG and carbon intensity scores, providing feedback into the portfolio construction process (see below).

One of the main challenges in integrating ESG factors in FI is data availability, partly due to the dominance of data providers using equity indicators. All ESG data needs to be mapped internally to our issuer universe. Coverage of unlisted or sovereign-owned enterprises has yet to be developed.

The development of the global approach to responsible investment

The investment outcomes

As part of the fundamental credit process, we require a full understanding of the balance sheet including any potential ESG risks that could impact cash flow, debt/EBITDA and other credit metrics. For privately-held companies, the required financial and ESG information is often unavailable or insufficient to complete a credit review. When this happens, we engage with the issuer, requesting information from the treasurer, CFO or investor relations team.

In a recent example concerning a European unlisted company (with an external credit rating of AA and a low governance rating by an ESG service provider), we were unable to confirm the existence of policies related to anti-corruption. This information was required to complete the liabilities (legal, social and environmental) component of our credit analysis and was potentially financially material due to the issuer’s high level of government-regulated income and involvement with government procurement. We contacted the company and spoke with the treasurer in 2017, when we requested the required policy. The company understood our requirements and agreed to disclose the policy. We were able to approve the credit and invest in its upcoming bond issue.

In another example, in the European unlisted market, a corporate with a complex financial structure and limited public disclosure meant we were unable to form a comprehensive view on the credit. This led to uncertainty about the potential for stable future cash flows and credit metrics. We attempted several engagements with company management to mitigate these concerns, which were unsuccessful and therefore further amplified our concerns. As a result, we felt that this risk was not being priced into the company’s bonds. Based on this limited information, we internally downgraded the credit, and informed the company that we would not be able to participate in any new issues unless it increased its willingness to engage with debt investors.

In both examples, we also considered carbon risk in our credit analysis. However, given the lack of carbon intensity disclosure data in the unlisted corporate market, we are unable to complete our carbon risk calculations and may be increasingly restricted in the size of positions we can hold.

Key takeaways

Although we have been integrating ESG in our investment process for many years, the PRI’s workstreams on FI and on CRAs has highlighted the requirements for clearer explanations of the investment process, particularly in how we consider ESG data and risks and opportunities in our credit research process, as well as the importance of issuer engagement.

Our recent enhancements have increased ESG knowledge and dialogue within the investment team, leading to better evidence of our ESG integration process to clients. We are also planning to introduce a public quarterly report on integrating ESG in FI to enhance our transparency.

Within our propriety tools, we can measure the outcome of our ESG integration through improved portfolio ESG and carbon scores. We believe this will lead to more sustainable risk-adjusted returns for clients in the long term.

Future plans include systematically embedding sector-specific ESG criteria directly into proprietary quantitative credit ratings. This will further enhance our ability to consider ESG data in the credit process.

Download the report

Shifting perceptions: ESG, credit risk and ratings: part 3 - from disconnects to action areas

January 2019

• Corporate debt
• HQ: Developed Markets
• Shifting perceptions: ESG, credit risk and ratings - part 3: from disconnects to action areas

Executive summary

Fostering CRA-investor dialogue

From disconnects to action areas

A transparent and systematic framework

Applying theory to practice

Next steps: connecting the dots.

Regional colour from the forums

Sovereign versus corporate credit risk

CRA examples

Investor case studies

Case study: AXA Group

Case study: BlueBay Asset Management LLP

Case study: Futuregrowth Asset Management

Case study: Legal & General Investment Management

Case study: Nikko Asset Management

Case study: NN Investment Partners

Case study: Nomura Asset Management

Case study: Triodos Investment Management

Case study: Aegon Asset Management

Case study: Caisse des Depots

Case study: Colchester Global Investors

Case study: Insight Investment

Case study: PIMCO

Case study: Templeton Global Macro

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