This insights piece is by Alex Babin, CEO of Hercules
Over the past decade, Delegated Authority (DA) has evolved from a supporting channel into a dominant market force. Data from Oxbow Partners reports that premiums more than doubled from £10.4bn in 2018 to £22.1bn in 2023, driving DA’s share of the Lloyd’s market from 30% to over 40%. As market conditions soften, this trajectory is set to accelerate, with projections suggesting DA will exceed 45% of total market premium by 2027. This shift represents a fundamental move towards a model where the ability to deploy capacity through specialist partners at scale is the ultimate competitive advantage.
While this growth creates significant opportunities for expansion, it also introduces a critical challenge: the need for robust compliance and operational control. As premium volumes surge, the operational backbone — particularly bordereaux management— has failed to keep pace. Processes remain manual, reactive, and fragmented, creating friction at a time when moving toward a softening market, where margins are tight and scrutiny is high. What was once accepted as a cost of doing business now represents a material risk to performance.
To succeed, the market must evolve to a new operating model – Delegated Authority 2.0 – supported by modern AI-powered technology that improves the accuracy, speed and visibility of portfolio performance. In this new era, disciplined data management, continuous oversight, and forward-looking insight are embedded as core non-negotiable capabilities for every participant in the value chain.
Delegated Authority Under Pressure: Key Challenges Ahead
The DA market currently faces a convergence of pressures that legacy systems simply cannot sustain:
Regulatory Compliance. Under Lloyd’s requirements, insurers are now required to prove operational resilience testing, and the move toward Core Data Record (CDR). Meeting these benchmarks requires a level of real-time oversight that manual spreadsheets cannot provide.
Data Quality and Integration. A lack of standardization across the market results in massive inefficiencies. Many insurers still struggle with the “bordereaux bottleneck,” where the flow of accurate data between underwriters, brokers, and cover holders is
delayed by weeks or even months. This lack of integration results in information that exists within the ecosystem that exists within the ecosystem but is inaccessible for real-time decision-making.
Risk Management and Oversight. Without real-time visibility into what is being bound at the point of underwriting, all parties are exposed to heightened risk which can be costly to unwind.
Talent and Expertise. While the need for DA expertise has never been greater, skilled professionals are in high demand and are often hindered by fragmented manual workflows. When experts spend their time on repetitive data entry and spreadsheet reconciliation, their technical underwriting value is squandered on administrative tasks rather than strategic portfolio management.
Addressing these challenges requires a shift away from reactive data processing towards a proactive, technology-enabled strategy. By embracing advancements within the field of AI, insurers can significantly enhance accuracy while reducing the operational cost of DA business.
The goal is to provide underwriters and analysts with tools to enhance the work they do. When data is ingested and validated automatically, your experts can use that to better understand the risks and value of their portfolios.
Rebuilding the Framework: The Three Pillars of DA 2.0
Modernizing DA operations requires a fundamental transition from processing data to managing portfolios. This transition is built on a practical framework of three core pillars:
1. Front-End Validation
Modernization begins at the point of entry. By implementing digital portals or API-driven validation at the cover holder level, insurers can enforce contract certainty in real-time. If a risk violates a territorial limit, includes an excluded class, or breaches a liability limit, the system flags it before the policy is bound. This “Clean In” approach removes the retrospective “cleanup” phase entirely, ensuring that every line of data entering the ecosystem is compliant from day one.
2. Removing Operational Friction
Every manual touchpoint in a DA workflow is a potential point of failure. Modernized platforms automate the ingestion and harmonization of disparate data formats. By removing the need for MGAs, brokers, and carriers to manually transform spreadsheets, organisations can significantly reduce their expense ratios. This shift allows the broker to concentrate on being a strategic advisor.
3. Continuous Auditability
Under DA 2.0, the annual audit evolves into a continuous process. With real-time visibility into binder performance, all parts of the DA value chain can spot trends as they happen, moving to a more dynamic approach to underwriting and risk management.
AI and the Future of Portfolio Visibility
While AI is often dismissed as a buzzword, its application in DA 2.0 is both specific and transformative. We are moving beyond basic automation into Augmented Ingestion and Validation. AI now enables the ingestion of large volumes of unstructured data such as scanned policy documents and complex property surveys, mapping them into structured formats at pace with high accuracy.
Beyond ingestion, machine learning models can improve Anomaly Detection, flagging patterns that may indicate premium leakage, potential fraud, or highlight potential improvements in operational resilience. The objective is not to replace the underwriter, but to augment their work with real-time, portfolio-level transparency, and insight. By enabling management by exception, AI allows underwriters to focus their human judgement on non-standard risks, significantly increasing the volume of business they can effectively oversee.
Conclusion: Transparency as a Competitive Edge
To maintain its global standing, the London Market must reform outdated DA processes. Delegated Authority 2.0 is more than a technology upgrade; it is a fundamental mindset shift. MGAs, brokers and carriers must deliver data discipline as a core part of their value proposition, reflecting the Lloyd’s guidelines around the Core Data Record. By increasing control and insight at scale, we can turn oversight from a regulatory burden into a competitive advantage, ensuring that the DA channel remains a sustainable, profitable engine for future growth.
About the author: Alex Babin is CEO of Hercules, an AI platform for complex workflow automation in industries with high transaction volumes and strict business rules. For Insurance, the Hercules platform handles the heavy lifting in underwriting, policy servicing, and claims, ingesting and validating large, messy submissions so your teams don’t have to. Visit: https://www.hercules.ai/insurance
Be the first to comment