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Korra, an open software-as-a-service (SaaS) platform for property and casualty (P&C) reinsurance and insurance-linked securities (ILS) transactions, has launched Korra Deal Analysis, an application designed to assess the quantitative and qualitative characteristics of casualty, non-catastrophe property and specialty reinsurance opportunities.
The platform enables ceding insurers and reinsurers, managing general agents (MGAs), fronting carriers and reinsurance brokers to structure and price transactions and produce formal risk and investment reports for prospective capital providers.
- Korra has introduced Deal Analysis, an application for analyzing, structuring and pricing casualty, non-catastrophe property and specialty reinsurance and insurance-linked securities (ILS) transactions.
- The platform combines AI-powered data extraction, actuarial techniques and hierarchical Bayesian models to assess prospective losses, transaction structures and investor returns.
- Reinsurance brokers, MGAs, cedents and capital providers can evaluate internal rate of return (IRR), multiple on invested capital (MOIC) and downside risks, with analytics carried forward into ongoing portfolio monitoring.
ILS investors and collateralized reinsurers can use the same analytical framework to evaluate submissions based on investment measures such as internal rate of return (IRR) and multiple on invested capital (MOIC), rather than relying exclusively on traditional insurance accounting metrics such as the combined ratio.
The application also incorporates transparent, back-tested stochastic models to assess the probability of adverse loss scenarios and the potential financial consequences for participants in a transaction.
Korra combines actuarial modeling with reinsurance deal structuring
Korra Deal Analysis brings together loss projections, reinsurance structures, collateral requirements, capital arrangements and investment returns within a single modeling environment.
The application allows brokers and capital providers to adjust assumptions, compare alternative transaction structures and examine the range of potential financial outcomes before determining whether a proposed transaction is viable.
Structuring and evaluating an ILS transaction requires understanding not only what losses may look like, but how they develop over time, flow through the deal structure, and affect each party’s economics.
Kyle Safran, Head of Data Science at Korra
“Deal Analysis brings those pieces together – loss modeling, reinsurance structure, collateral requirements, capital structure, and investor returns – in a transparent modeling environment where reinsurance brokers and capital providers can test assumptions, compare alternative structures, and understand the distribution of potential outcomes. This gives teams an iterative and explainable way to price risk, structure transactions, and assess deal viability.”
The application uses artificial intelligence to extract information and historical loss triangle data from reinsurance submissions, reducing the manual work involved in preparing historical claims experience for analysis.
Users can examine historical performance through Korra’s proprietary graphics library and access its industry performance database to compare datasets or blend industry experience with individual portfolio information.
Bayesian models support loss projections and investment analysis
Once historical data has been processed, Deal Analysis enables users to generate prospective loss estimates using traditional actuarial methods or Korra’s hierarchical Bayesian models.
The Bayesian approach produces probability distributions of future loss ratios, allowing users to examine a range of potential underwriting outcomes rather than relying solely on individual point estimates.
Korra said its Bayesian loss models are based on published, peer-reviewed methodologies and are designed to accommodate the limited historical information often available from MGAs.
The models incorporate prior assumptions informed by industry data, helping users develop loss projections when the underlying portfolio has relatively little claims history.
After completing loss modeling, users can assess alternative reinsurance and capital structures and calculate projected investor returns, including MOIC and IRR.
The resulting analysis and forecasts can be incorporated into investor-ready reports that present the assumptions, transaction economics and potential outcomes in a consistent format.
As alternative capital takes a larger share of reinsurance, brokers and investors need better tools to evaluate risk and transaction economics.
Meredith Barnes-Cook, Senior Principal at Datos Insights
“Platforms that bring actuarial modeling, deal structuring, and investor reporting into one environment make these transactions easier to assess, compare, and explain.”
Korra extends transaction analytics into portfolio monitoring
Deal Analysis is designed to retain the information generated during the initial evaluation after a reinsurance or ILS transaction becomes active.
Historical data, modeling assumptions and analytical results remain available within the Korra platform as claims experience develops.
This allows transaction participants to monitor deal and portfolio performance, reassess valuations as new information becomes available and incorporate updated analysis into renewal decisions.
The approach is intended to connect the initial underwriting and investment assessment with subsequent transaction management, rather than treating deal evaluation as a separate process completed before binding.
Risk originators and capital providers are ultimately looking at the same underlying risk from different perspectives, yet much of the analysis still happens through disconnected spreadsheets, static reports and manual workflows.
Umair Rasool, General Manager of Korra
“Deal Analysis gives both sides a more transparent and repeatable way to model risk, evaluate transaction economics and align on deal terms. By bringing those workflows together on the Korra platform, we’re creating a stronger analytical foundation for connecting risk with capital.”
