How Insurance Allocators Can Achieve Self-Service, Dynamic Reporting

Diversified portfolios and mounting data volumes are outpacing the reporting infrastructure most insurance carriers rely on. Investment teams are under pressure to deliver precise, on-time reports to boards, regulators, rating agencies, and external asset managers, and the systems behind those reports weren’t built for the complexity they now have to handle. If you’ve been frustrated with the quality and timeliness of your current setup, you’re not alone.

In a digitized world, generating a report should be easy and instant. Insurance asset owners are instead plagued by data problems: too much disparate data living in too many different systems, unstructured data that platforms cannot make sense of, no standardization, inconsistent formats, and inaccurate security masters. In a sector where good reporting and portfolio transparency equals a good reputation, real-time investment reporting, portfolio transparency, and look-through analytics are non-negotiables.

Drawbacks of common out-of-the-box reporting solutions

Many out-of-the-box investment reporting solutions are ill-equipped to handle the increasing complexity of modern multi-strategy portfolios that blend private and public asset classes. They often suffer from rigid informational latency and rely on manual workarounds. Latency – or slowness – and information asymmetry are dire adversaries in a digitized financial services world where trades and transactions occur in milliseconds. Data that is frequently out of sync with real-time market movements can cause expensive havoc.

“Asymmetric information can lead to market failures through adverse selection and moral hazard, distorting resource allocation.”ⁱ For insurers, that asymmetry shows up as the gap between what their systems report and what is actually happening in the portfolio. Cloud-based insurer data platforms and modern, API-driven architectures improve data flows and reduce latency and asymmetry.

Customization advantages of investment domain-native reporting solutions

Off-the-shelf tools have limited customization capabilities, so limited partners (LP) that buy them — whether endowments, pension funds, or insurers — get the same templates. Many legacy providers offer a single report template, such as a static PDF, that is sent to all investors regardless of their specific mix of investments or unique preferences. Insurers need to create reports that address their unique preferences and needs, since they operate in a heavier regulatory environment than private equity firms or endowments. Logic for reports is often hard-wired, making it difficult to generate reporting tailored for credit agencies, board members, or regulators. Custom reporting requires a modern data architecture capable of handling complex schemas and facilitating dynamic querying, the same architecture on which AI workflows and the broader asset management tech stack are built.

Agentic AI is going to play a key role in custom reporting tools, but only if that foundation is in place.

Insurance asset management needs dynamic reporting

The dream is to be able to ask an AI agent to tell us how well the asset portfolio matches the duration and cash flow profile of our liabilities or what the key drivers of performance (alpha vs. beta) are. We should be able to deliver a precise Own Risk and Solvency Assessment (ORSA) Summary Report to the state regulator in a couple of keystrokes. Reporting tools built for asset management enable users to perform real-time queries and interrogate the data dynamically. Different stakeholders can view the same data through different lenses: actuaries may need assets grouped by product line or segment for cash flow testing and asset-liability matching, while investment managers may want a view grouped by asset class or vintage year. Whether an investment team is examining fund performance across various time frames or producing a Risk-Based Capital (RBC) report, executing queries in real time allows them to produce routine regulatory filings in hours, not days.

Inherent in custom reporting are self-service capabilities that do not require coding. Risk and compliance teams can use self-service tools for the constant monitoring of RBC metrics and ratings agency requirements to ensure the firm remains within safe capital thresholds. They can also design templates for bulk-generated, pre-scheduled reports, including summaries for regulatory filings and the executive committee.

Reporting used to be manual and error ridden. Imagine manually wading through data attributes like issuers and capital structure, terms and conditions, pricing and valuation setup, classifications and hierarchies, credit and risk data, regulatory and compliance attributes, tax and accounting attributes, and of course basic identifiers. Custom and self-service reporting and analytics are made possible by the data foundation layer, which consolidates all reference and security data into a single, reconciled data store and automates data flows.

Managing private credit risk through better reporting and analytics

Speaking of latency, firms using older data systems find they cannot produce a new investor report in an hour. Instead, they face a series of meetings to discuss the development queue required to build a new analytics view. If the CEO wants to appraise the general account portfolio health at any given moment, the CIO should not have to grapple with a days-long data chase, all with little faith in the integrity of the resulting report. These are volatile times, so analysts and risk officers must both be able to gauge exposure to specific asset classes and drill down to the underlying exposures inherent in opaque alternatives like private credit.

Private credit accounts for around 35% of total U.S. insurer investments, close to 25% of UK insurer assets.ⁱⁱ The National Association of Insurance Commissioners (NAIC) and the SEC are zeroed in on containing private credit risk. The U.S. Treasury Department has just requested information from state insurance commissions and insurance firms about their business models and private credit investments.ⁱⁱⁱ Insurers need to shore up their risk assessment practices to keep control of their private credit exposure while tightening their reporting capabilities.