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Data scrutiny is at the core of significant risk transfer growth

June 10, 2026

As SRT use grows in popularity, regulators are taking a closer look at the quality of banks’ data.

For banks, the center of gravity in securitization is shifting dramatically.  Firms are flocking to the fast-growing significant risk transfer (SRT) market, with synthetic securities that reduce the capital they’re required to hold against loan portfolios. Significant risk transfer and synthetic structures are soaring in popularity for good reason: The combination allows banks to offload their portfolios’ credit risk without selling the underlying loans. However, they still require regulatory approval.  In order to secure regulators’ blessing for SRT transactions, banks need to prove they’re offloading risk. That means gathering data from across credit, finance and treasury systems, much of which is fragmented and hard to find within their organizations.  As significant risk transfers (also known as credit risk transfers) grow in popularity, more banks are discovering that a solid data foundation is the key factor for defensible SRTs. <h3>Why significant risk transfers are growing so fast</h3> Significant risk transfer is a strategic response to regulatory and balancesheet realities. Formalized with Basel II in the mid-2000s and then clarified under Basel III after the 2008 financial crisis, the transactions enable banks to transfer the riskiest portions of their loan portfolios to external investors through instruments such as derivatives or guarantees. Their popularity is a direct response to the growing risk environment for banks. Macroeconomic shocks and structural shifts have rocked the banking sector over the last decade. In 2026, we’re seeing more change driven by geopolitical upheaval, rapid inflation and oil-price shocks. Meanwhile, interest rates continue to swing, affecting everything from loan pricing to asset liability management. SRTs are often seen as a win-win: Banks retain their client relationships while freeing up capital. By allowing banks to segment, price and transfer risk more precisely, the transactions support broader client coverage while safeguarding capital.  The surge in adoption is a testament to SRT’s effectiveness in aligning risk management with economic imperatives and regulatory requirements. Nowhere is the shift to SRT more visible than in Europe. Supported by a supervisory framework from bodies such as the European Central Bank, the region has enthusiastically adopted synthetic risk transfer, with the number of transactions <a rel="noopener noreferrer" href="https://www.bankingsupervision.europa.eu/press/speeches/date/2026/html/ssm.sp260324\~2b54f795e3.en.html" target="_blank">jumping 45%</a> from 2024 to 2025 as more banks seek SRT. <h3>How to get significant risk transfer ready for regulatory scrutiny </h3> Yet executing significant risk transfers in a way that stands up to regulatory scrutiny remains a high bar—and getting higher. As a result of the growing share of credit risk being absorbed by nonbank investors through SRT deals, the European Central Bank is paying increasingly close attention, <a rel="noopener noreferrer" href="https://www.bloomberg.com/news/articles/2026-03-19/ecb-tells-banks-to-identify-the-leverage-providers-on-srt-deals" target="_blank">seeking to better understand</a> who is holding the risk. That scrutiny is shifting the focus from the mechanics of SRT deals to the data that sits beneath them. Meeting SRT requirements depends on ensuring the strength of the frameworks and data that underpins them. Banks must be able to consistently identify, measure and aggregate the underlying risks with a level of granularity that many still struggle to achieve. Outsourcing risk becomes much harder to defend. <h3>Two key data questions for financial institutions</h3> Chief risk officers and other banking leaders have two key concerns to address: <ol> <li>Can you prove exactly what risk was transferred? Significant risk transfer requires granular answers. Which exposures are included and excluded? How are defaults and prepayments tracked? Is the data consistent across credit, finance, treasury and structuring teams? While data completeness and lineage are critical, banks’ SRT data chains are often fragmented, crossing origination systems, risk systems and accounting systems. If any drift occurs due to, say, small reconciliation differences or timing mismatches among the systems, then the portfolio no longer matches what was modeled, and the resulting inconsistencies can impact whether the risk has genuinely been transferred. Worse, the gradual misalignment can be exacerbated by factors such as missing or inconsistent loan attributes. The data stakes are high. Banks that can’t reconstruct the risk stack can find themselves unable to defend the significant risk transfer to the regulatory authority. </li> <li>Does the loss data stand up under stress? SRT approval hinges on banks’ ability to verify whether losses will move to investors in adverse conditions. To make that happen, banks need reliable historical default and recovery data and precise calibration of stress tests. But SRT portfolios often suffer from a structural issue: They have strong performance data for normal conditions but limited evidence for how newer portfolios will perform in adverse environments or economic downturns. Loss behavior has to be inferred rather than observed, creating a dangerous gap for banks looking to execute SRT trades. Without accurate data on loss behavior, banks risk signing off on significant risk transfers that only work in calm markets.</li> </ol> <h3>Data: A key success factor in significant risk transfer</h3> Data has become the basis for regulatory approval of significant risk transfer. As the strategy continues to grow in popularity, more banking executives face concerns about whether they’re making capital decisions based on weak, fragmented data. Chief risk officers, in particular, struggle with increasingly pointed questions around significant risk transfer: Do they have the data to make SRT credible in the eyes of regulators? What gaps in data, governance and risk infrastructure limit their organization’s ability to meet SRT requirements and take advantage of its benefits? In our next blog, we will examine how regulatory frameworks such as STS and CRR, together with principles like BCBS 239, are shaping that answer and what banks need to put in place to turn risk transfer into a reliable, scalable capital management tool. The authors would like to thank Rajiv Mohapatra and Sathyanarayanan Palaniappan for their contributions to this blog.

Anshuman Choudhary

Senior Partner - Consulting

Anshuman brings over 25 years of experience in the financial services industry, with deep subject matter expertise in risk management, capital markets and wealth management. He has successfully led and delivered strategic initiatives across diverse geographies, including North America, the UK, Benelux, Nordics, India and Singapore. His global experience and domain knowledge make him a trusted advisor in navigating complex financial landscapes.

Chidambaram Ramasamy

Manager – Consulting, Governance, Risk & Compliance

Chidambaram specializes in banking and financial services, focusing on risk management and regulatory reporting. With expertise in market risk and liquidity risk, he partners with organizations to design and implement scalable regulatory reporting solutions, supporting compliance, transparency and effective risk management across the enterprise.

Surianarayanan A

Manager – Consulting, Governance, Risk & Compliance

Surianarayanan is a seasoned professional in risk management and regulatory compliance, with expertise in Basel implementation and digital transformation for BFSI clients. He has led innovative projects like AI-driven stress-testing frameworks and advanced risk tools, helping organizations optimize efficiency and navigate complex regulations.

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