Recent banking failures around the globe have exposed fundamental weaknesses in how financial institutions manage counterparty credit risk:
- The 2022 UK Gilt liquidity crisis showed how derivative hedging practices can amplify collateral calls and fire sales, turning market stress into a self-reinforcing cycle.
- Several recent financial failures and restructurings in the U.S. revealed how concentrated depositor bases, weak interest rates, and liquidity risk management can turn isolated shocks into system-wide bank runs.
- Private equity deal activity has shot up, with U.S. transaction value in the first half of 2025 being roughly 50% higher than the same period in 2024.
Larger transactions and increasingly complex structures such as co-investments, continuation funds, and leveraged buyouts create webs of interconnected exposures. For banks, this makes counterparty credit risk harder to measure, aggregate, and stress-test, raising the chance that shocks in one part of the system cascade across multiple institutions.
The common thread across these failures and market shifts is clear: counterparty credit risk (CCR-SA) is no longer confined to bilateral exposures that can be neatly modeled.
Instead, it is shaped by volatile markets, opaque private structures, and the rapid transmission of shocks across institutions. These dynamics expose weaknesses in traditional CCR-SA frameworks and set the stage for deeper structural challenges.
Why Volatile Markets Challenge CCR-SA Frameworks
Volatility magnifies exposures, interconnected private finance blurs traditional boundaries, and regulatory expectations continue to climb. Together, these forces are stretching CCR-SA frameworks beyond their original design and demanding more dynamic approaches to risk measurement, monitoring, and mitigation.
Leverage magnifies losses
Leverage can turn small market moves into outsized losses. When counterparties use borrowing or derivatives to increase exposure, they expose not just themselves but also the banks they trade with to sudden shocks.
Archegos Capital is a strong example: it built large positions through total return swaps that obscured its true risk across multiple banks. When prices fell, it could not meet margin calls, and the losses flowed back to its banking partners in concentrated form.
Leverage allows risks to build silently across desks and products, only to emerge suddenly when markets shift. Without strong aggregation and stress testing across the institution, banks are left vulnerable to being blindsided when leveraged counterparties default.
Growth of private finance creates hidden interconnections
Private equity, private credit, and infrastructure funds now interact with banks across multiple business lines. The same fund might appear as a borrower in subscription financing, a client in NAV-based lending, and a counterparty in derivatives hedging. Viewed in isolation, each relationship looks manageable.
The danger lies in how these exposures connect. When aggregated, they can form large concentrations that are easy to overlook in traditional reporting systems.
The web of linkages means stress in one area, such as a liquidity squeeze in a fund, can quickly spill into other parts of the banking relationship.
Counterparties can no longer be assessed transaction by transaction; they must be understood as part of an interconnected network of exposures.
Regulatory pressure is intensifying
Supervisory expectations for counterparty credit risk have increased in step with greater market volatility.
Under Basel IV, the standardized approach to CCR-SA has replaced earlier methodologies, requiring banks to incorporate more precise measures of netting, collateral, and potential future exposure.
Institutions must demonstrate that exposures are captured and reported with accuracy.
Even banks with advanced internal models remain subject to CCR-SA because the framework feeds directly into leverage ratio calculations. It places additional operational demands on risk functions already under pressure.
Meeting these requirements depends on robust data infrastructure, effective governance, and the ability to prove resilience under stressed conditions.
Structural Gaps in Counterparty Credit Risk Management
Against this backdrop, several structural gaps in how banks manage counterparty credit risk have become increasingly clear.
Gap 1: Siloed risk management and data aggregation failures
Many banks manage exposures within product or business lines, with loans tracked in one system, derivatives in another, and wealth products in a third. The fragmented structure makes it difficult to produce a consolidated view of total exposure to a single counterparty.
Some institutions have been unable to systematically identify and measure combined private equity (PE) credit and counterparty exposures because their CCR-SA processes are aligned to individual silos without an overarching perspective.
Each business line might view its exposure as acceptable, but collectively, they represent a significant concentration risk.
Regulators now expect institutions to integrate collateral and exposure data holistically. The PRA’s thematic review found that a number of banks were unable to uniquely identify and systematically measure their combined credit and counterparty exposures linked to the PE sector within their overall risk data.
The weakness is not limited to private equity but applies to any complex counterparty with multiple touchpoints across a bank.
Consequences were evident in 2023, when banks unable to quickly aggregate exposures to failing institutions struggled to understand their positions as markets turned against them.
Gap 2: Ineffective stress testing due to data fragmentation
Fragmented data environments make aggregate stress tests difficult or unreliable. Most tests remain siloed and don’t capture portfolio-wide risks, and this compartmentalized approach to stress testing misses critical interdependencies.
A stress scenario that seems manageable in one unit may prove severe when credit risk exposures are aggregated.
The PRA expects banks to evaluate higher-than-observed default and loss correlations in periods of stress, but fragmented systems make this type of analysis almost impossible.
Modern stress testing frameworks need to account for wrong-way risk, correlation breakdowns, and the amplifying effects of leverage across interconnected counterparty networks.
When banks can’t aggregate data effectively, they can’t stress test effectively, leaving them vulnerable to scenarios their individual business unit models suggest they can handle.
Gap 3: Lack of objective credit insight and benchmarks
A further gap lies in the absence of robust credit judgment and benchmarking within CCR-SA management. Many teams lack clarity on counterparty credit strength, especially relative to consistent standards.
Without objective benchmarks for current vs. desired exposure levels, banks risk reacting to headlines rather than structured analysis.
The challenge is particularly acute for private and unrated counterparties, which now account for a growing share of exposures.
Traditional credit assessment relies heavily on public ratings, but these are unavailable for many private finance entities.
The absence of consistent benchmarks leads to uneven decision-making. One business line may accept a counterparty based on limited information, while another reaches a different conclusion using different criteria.
The result is operational inconsistency and difficulty for senior management in setting a coherent firmwide risk appetite.
Best Practices for Managing CCR in Volatile Markets
Banks and financial institutions can close structural gaps by adopting practices that strengthen visibility, consistency, and resilience in counterparty credit risk management.
Build a unified risk aggregation platform
Consolidate exposures across business lines, including private equity, derivatives, and collateral, to enable portfolio-level visibility and holistic stress testing.
This approach requires more than technology alone; it also demands organizational change to break down product-line silos that have traditionally shaped risk management structures.
A unified platform should capture not only current exposures but also contingent obligations such as undrawn credit lines, potential margin calls, and derivative positions.
The platform must support timely aggregation capabilities. In volatile markets, yesterday’s view may no longer reflect today’s risk profile, so systems need to recalculate exposures continuously and provide early warnings when concentration limits are at risk of being breached.
Enhance stress testing frameworks
Develop scenario modeling that spans counterparties, products, and sectors, with particular focus on stressed areas such as private equity. Stress tests should move beyond traditional historical templates to incorporate forward-looking scenarios that reflect structural shifts in markets.
The approach includes modeling situations where leveraged counterparties face simultaneous margin calls, where correlations break down and uncorrelated risks move together, and where liquidity constraints limit normal credit risk mitigation strategies.
Effective stress testing recognizes that historical loss patterns may underestimate the impact of today’s scale of leverage and interconnectedness.
Anchor decisions in objective credit insights and benchmarks
Introduce benchmarking frameworks that combine fundamentals, market-implied signals, and peer comparisons to provide consistent measures of counterparty strength. These frameworks should apply across both rated and unrated counterparties.
For private counterparties lacking public ratings, alternative sources of credit intelligence are essential.
Objective insights help avoid reliance on incomplete information and enable more disciplined credit judgment. Clear risk appetite statements aligned with these benchmarks ensure that decisions are consistent across business lines and are based on analysis rather than sentiment.
Invest in future-ready capability building
Ensure CCR-SA capabilities evolve in line with market structures, new product types, and supervisory expectations.
Future-ready capabilities include advanced analytics that can process unstructured data, machine learning models that can detect emerging risk patterns, and flexible technology that can integrate new data sources without major overhauls.
Talent is just as critical as technology. Risk teams need the expertise to evaluate increasingly complex counterparties, interpret alternative data, and apply advanced analytical tools effectively.
How Credit Benchmark Supports Counterparty Credit Risk Management
Credit Benchmark addresses these structural gaps by providing banks with consensus-based credit intelligence derived from the internal risk views of over 40 global financial institutions.
Credit Benchmark’s approach offers several critical advantages for counterparty credit risk management:
Extensive coverage of unrated and private entities
Credit Benchmark’s credit consensus ratings cover over 115,000 individual obligors, more than 90% of which are unrated by traditional credit rating agencies.
The coverage is particularly valuable for banks managing exposures to private equity funds, family offices, and other opaque counterparties that lack public ratings.
The consensus approach leverages the collective “skin in the game” perspective of banks actively lending to these counterparties.
Large sophisticated banks set their own internal credit risk ratings in order to manage the credit risk of the counterparties they lend to, and Credit Benchmark aggregates these views to provide an independent, market-informed perspective on credit risk.
Real-world independent perspective
Credit consensus ratings are based on the anonymized and aggregated internal risk views from banks with actual exposure to these counterparties.
It differs fundamentally from traditional “issuer-pays” rating models and provides an unbiased, real-world market sentiment perspective on credit risk, not just analytical assessment without financial commitment.
The methodology’s transparency and the involvement of multiple contributing banks provide evidence of strong governance and model validation processes that align with regulatory guidelines.
Continuous peer benchmarking and early warning tracking
Credit Benchmark’s consensus data is dynamically refreshed every week, enabling timely identification of potential credit risk changes.
Banks and FIs can implement proactive risk management frameworks that can identify emerging risks before they become acute problems.
The continuous benchmarking aspect helps banks compare their internal views against market consensus, providing external validation for internal credit decisions.
It’s particularly valuable for regulatory purposes, where supervisors expect banks to validate their internal models against external benchmarks.
Integration across the client risk management lifecycle
Credit Benchmark’s data can be seamlessly integrated into existing risk management workflows to support various stages of the client lifecycle, from customer onboarding and new client approvals to annual reviews and portfolio management.
The breadth of the consensus dataset, including publicly unrated buy-side names, also allows the client to better monitor the credit of their members’ clients.
Thanks to this integration capability, banks can build more comprehensive CCR-SA frameworks that can track counterparty risk throughout the entire relationship lifecycle, not just at origination.
Case Study: How Credit Benchmark Helped CDCC Strengthen CCR Management
Canadian Derivatives Clearing Corporation (CDCC), the central clearing counterparty for exchange-traded derivatives in Canada, leverages Credit Benchmark’s consensus data to enhance its counterparty risk management capabilities.
As Acting Director of Financial Resilience Risk Vladimir Levtsun notes: "Credit Benchmark's data has contributed to directly strengthening our ability to manage counterparty risk and enhance internal reporting, leading to more confident, proactive risk decisions."
CDCC uses Credit Benchmark’s data to harmonize credit assessment across different participant types, with particular value derived from insights into private and unrated entities that traditional rating agencies don’t cover. The data helps CDCC refine decision-making processes, manage counterparty exposures more effectively, and strengthen risk oversight capabilities across its network of more than 30 clearing members.
Building a Resilient CCR-SA Framework for 2025 and Beyond
CCR-SA management in volatile markets must be integrated, data-anchored, and governed with clear accountability.
Siloed processes and reactive decisions are no longer adequate for today’s interconnected counterparties and fast-moving liquidity conditions.
Firms that unify exposure aggregation across business lines, strengthen forward-looking stress testing, ground decisions in objective credit benchmarks, and invest in future-ready people and technology will maintain a steady risk appetite while markets shift.
Credit Benchmark’s consensus-based intelligence supports this shift by providing independent, comprehensive insight on rated and unrated names that can be embedded across the CCR lifecycle.
Institutions that treat CCR as a strategic capability, not a compliance chore, will navigate uncertainty with greater confidence and create room for disciplined growth.
To explore how Credit Benchmark can help with counterparty credit risk management, book a demo today.
FAQs
What is the difference between counterparty credit risk vs credit risk?
Credit risk is the broad risk that a borrower will fail to repay a loan or meet debt obligations. Counterparty credit risk (CCR-SA) is a specific type of credit risk that arises from derivative contracts, trading relationships, and other bilateral agreements where each party has obligations to the other.
CCR-SA includes additional complexities like replacement risk (the cost of replacing a defaulted contract) and settlement risk (the risk of non-delivery during settlement).
Why is counterparty credit risk important for banks and financial institutions?
CCR-SA is critical because it can lead to significant unexpected losses, as seen in the Archegos collapse. Unlike traditional credit risk where exposure is clear, counterparty credit risk can fluctuate based on market conditions and is often interconnected across multiple business lines.
Poor CCR-SA management can lead to concentration risks, regulatory sanctions, and reputational damage. In today’s volatile financial markets, effective CCR-SA management is essential for maintaining financial stability and regulatory compliance.
How do credit and counterparty risk affect overall portfolio stability?
Credit and counterparty risks can create dangerous concentrations that threaten portfolio stability, especially when exposures are not properly aggregated across business lines.
In stressed market conditions, correlated defaults among counterparties can amplify losses beyond what individual risk assessments might suggest.
Effective management requires understanding not just individual exposures but also how they interact during market stress, including correlation breakdowns and liquidity constraints that can prevent normal risk mitigation strategies.