With S&P Global predicting a potential credit downturn in late 2024, financial institutions face a complex risk environment shaped by heightened geopolitical tensions, the urgent need for decarbonisation, and rapid technological advancements. In such a volatile environment, robust credit portfolio stress testing has become more than just regulatory exercise, it’s a lifeline. However, the key to unlocking the true potential of stress testing lies in high-quality data, that enables accurate risk assessment, granular analysis, and timely responses to market volatility.
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Counterparty risk refers to the possibilities that the entity you are engaging with in a transaction (known as your counterparty) may fail to meet its obligations. The risk is not only limited to credit risk (failure to pay back a loan or money owned). It also involves settlement risks, operational risks, legal risks and reputational risks.
Imagine a manufacturing company A that needs steel from a supplier company B. They agree on a year-long contract, but counterparty risk looms. Company B could face financial trouble and go bankrupt, leaving Company A without steel. A fire at Company B's factory could halt production, disrupting the supply chain. Legal issues, like improper permits, could shut down Company B's operations. Even new environmental regulations could force Company B to break the contract to avoid losses. This shows how counterparty risk goes beyond just financial health, encompassing operational, legal, and regulatory factors that could disrupt the deal and harm Company A.
Assessing counterparty risks involves evaluating a counterparty’s creditworthiness, payment history and reputation. This involves multiple challenges like data-related, analytical, regulatory, and resource constrained difficulties.
To address the challenges of counterparty risk assessment a multifaceted approach is required.
It should include strong data management, advanced analytics, and a proactive risk culture. Here’s a list of best practices organisations can take:
1- Improve data infrastructure and governance.
Prioritise data quality and setting a data governance framework in place. Set roles, processes, policies and tools, and develop a centralised data repository with strict quality controls, and real- time data input to guarantee data accuracy and timely information. Ensure data cleansing, validation and enrichment techniques, i.e. enhancing existing data by supplementing incomplete data.
2- Employ risk mitigation strategies
Adopt a proactive approach to risk and conducting thorough due diligence on counterparties examining both financial and non-financial risks. Assess financial stability, creditworthiness, and reputation. Prevent overexposure by setting appropriate risk limits for each counterparty based on their credit rating and market volatility. Diversify counterparties across different jurisdictions to mitigate concentration risk and the impact of single counterparty default. Employ collateralisation and netting arrangements to give a layer of protection against counterparty risk. Continuously monitor counterparties and assess their risk profiles to discover any changes that may necessitate action.
3- Leverage advanced technology analytics and modelling
Invest in advanced statistical models, machine learning algorithms, data lakes, cloud platforms and AI-powered tools to improve data administration, analysis and reporting. Make use of alternative data (news, social media, web scraping) and metadata to gain a more comprehensive view of counterparties.
Perform regular stress tests and scenario analysis with diverse scenarios.
4- Adopt a comprehensive risk assessment framework
When adopting a risk assessment framework make sure it’s comprehensive and adaptable. Encompass all elements of risk (credit risk, legal, market, operational, and reputational). Examine each and every counterparty, transaction, and exposure. Continuously monitor and track counterparty risk profiles, and update accordingly to mitigate future risks and possible difficulties.
Thus, to improve and strengthen counterparty risk assessment, it is crucial to acknowledge the foundational importance of accurate, comprehensive, and reliable data. Limited public information, cross-border complications, data timeliness, inconsistent reporting, and language barriers all block the ability to obtain a clear picture of a counterparty's financial standing. To undertake a full assessment, organisations need data on financial performance, ownership structure, industry risks, and legal compliance. This frequently necessitates reliance on a variety of sources, ranging from credit bureaus to direct contact with counterparties. This data should be assembled into a centralised repository that acts as a single source of reference. Such integration improves analysis, makes compliance smoother, and helps provide a comprehensive perspective of risk.
With Cedar Rose, you can eliminate your reliance on multiple sources to gather the crucial data you need for counterparty risk assessment.
Our all- in- one risk and business intelligence subscription platform, CRiS Intelligence enables you to stay ahead of the market with real-time data insights. It offers a centralised hub that allows you to access data on millions of companies, accurately assess creditworthiness, identify shareholding and directorship structures, reveal ultimate beneficiary owners (UBOs), conduct AML/ CTF checks (Anti-Money Laundering/Counter-Terrorism Financing), request fresh investigations and conduct thorough due diligence with ease.
With real-time monitoring and customisable solutions that meet your needs, you can streamline risk assessment processes, ensure regulatory compliance, and confidently assess credit risk, and uncover hidden connections within your counterparty's network.
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