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What is Risk Solved?

Risk Solved is a technology platform and services team focused on risk engineering data management and analytics for the insurance industry. Rather than selling a general-purpose analytics tool, it addresses a specific workflow: collecting, structuring and interpreting the risk data that feeds underwriting decisions.

Its stated audience is insurance organisations — insurers, MGAs, brokers and agents — plus the customers they serve. The value proposition is framed around underwriting profitability, which suggests the platform is meant to help underwriters see risk quality more clearly and price or select business accordingly.

Typical uses may include:

• Consolidating risk engineering survey data from many sources into a consistent format
• Producing analytics that support underwriting judgements and portfolio reviews
• Giving brokers and agents a structured way to submit risk information
• Serving clients across multiple regions, since the company describes global use

The main trade-off is specialisation. A dedicated insurance risk platform can fit established underwriting and risk engineering processes well, but it is not a general business intelligence product, so organisations wanting broad, cross-industry analytics may find it narrower than they need. Buyers should also confirm implementation effort, data-source integrations and commercial terms directly, as these details are not evident from the summary information.

How does Risk Solved help insurers increase underwriting profitability?

Risk Solved focuses on turning risk engineering data into something insurers can act on. Rather than leaving survey findings, loss-control reports and property data scattered across spreadsheets and inboxes, it centralises that information and applies analytics, which can support faster and more consistent underwriting decisions.

For insurers and MGAs, the practical benefits typically include:

• Better risk selection and pricing – structured risk data may reveal hazards or exposures that manual review misses, helping underwriters price more accurately.
• Reduced leakage – standardised data capture and workflows can cut re-keying errors and inconsistent assessments.
• Efficiency gains – automating data handling frees underwriters and risk engineers from administrative work.
• Portfolio visibility – aggregated analytics can highlight accumulation, concentration and emerging trends across a book.

Brokers and agents may use the same platform to submit cleaner risk information, which can speed up quoting and reduce back-and-forth. The trade-off is that value depends on data quality and adoption: if submissions remain incomplete or teams do not use the workflow, the analytical upside shrinks. It is best understood as a data-management and analytics layer that supports underwriting judgement, not a replacement for it.

What types of risk engineering data does Risk Solved manage?

Risk Solved focuses on risk engineering data rather than general insurance policy administration. Its platform is aimed at insurers, MGAs, brokers and agents, and their customers, so the data it manages typically sits between a physical risk assessment and an underwriting decision.

The types of risk engineering data described include:

• Survey and inspection data gathered during risk assessments of insured sites and operations.
• Risk improvement recommendations and the actions taken in response.
• Property and site characteristics, such as construction, occupancy and protection features.
• Underwriting-relevant risk information used to inform pricing and acceptance decisions.
• Portfolio-level analytics data, which aggregates individual risk records for trend and profitability analysis.

Because the emphasis is on data management and analytics, the value lies in standardising scattered engineering information so it can be searched, compared and reported consistently. That suits underwriting teams that need a clearer view of risk quality across a book of business, and brokers or agents who must submit and track risk details.

A trade-off is that a specialised risk engineering platform is not a full policy lifecycle system; it may need to integrate with existing underwriting or CRM tools. Pricing details are not stated in the available information.

Who can use Risk Solved's platform?

Risk Solved is designed for organizations involved in insurance risk assessment and underwriting. Its stated audience includes insurers, managing general agents (MGAs), brokers and agents, as well as the customers they serve.

Primary users

• Insurers and MGAs typically use the platform to centralize risk engineering data and support underwriting decisions, with the aim of improving underwriting profitability.
• Brokers and agents may use it to gather, organize and share risk information with carriers more efficiently.
• Policyholders and commercial customers can be involved where risk data collection and surveys feed into the underwriting process.

How use differs

Because the platform is global in reach, suitability depends less on region and more on whether an organization handles risk engineering data at scale. Smaller operations with limited data needs may find less value than larger carriers or intermediaries managing many risks. The main trade-off is between the efficiency gains of a shared data platform and the effort required to integrate it into existing workflows.

For official details, see Risk Solved.

What data analytics capabilities does Risk Solved offer?

Risk Solved is an insurance-focused risk engineering and data analytics platform. Its capabilities centre on turning survey, inspection and risk-engineering data into structured information that insurers, MGAs and brokers can use in underwriting and portfolio decisions.

Core capability areas

• Risk engineering data management: Capturing and organising survey and inspection data in a consistent structure, rather than leaving it scattered across spreadsheets and documents.
• Data analytics: Analysing that data to support underwriting decisions, portfolio review and risk selection.
• Underwriting support: Applying the resulting insight to underwriting workflows, with the stated aim of improving underwriting profitability.
• Global delivery: The provider says the solution is used internationally, serving insurers, MGAs, brokers and agents, and their customers.

Who it suits and trade-offs

It is typically suited to insurance organisations that already collect substantial risk-engineering data but struggle to analyse it consistently or at scale. The main appeal is combining data capture with analytics in one insurance-specific environment, which may reduce manual consolidation work.

The trade-off is that value depends on data quality and on integrating the platform with existing underwriting and policy systems. Smaller operations with limited survey data may find less benefit than larger, data-rich portfolios. Specific analytics techniques, model types and reporting options are not detailed in the supplied information, so those should be confirmed directly with the provider.

How does Risk Solved integrate with existing insurance systems?

Risk Solved is positioned as a data-management and analytics layer for risk engineering information, aimed at insurers, MGAs, brokers and agents. Its role is typically to sit alongside core insurance platforms rather than replace them, collecting, structuring and analysing risk data that those systems may not handle well on their own.

Likely integration patterns

• Data exchange: risk engineering and survey data can be moved between Risk Solved and policy, claims or underwriting systems through standard import/export or API-based connections.
• Complementary use: underwriting and portfolio teams may use it as a specialist analytics workspace, with decisions and outputs then recorded in the core system of record.
• Customer and broker input: because the stated audience includes brokers and their customers, some data may enter through shared submissions or questionnaires rather than direct system-to-system links.

Trade-offs

A dedicated layer can improve data quality and reporting consistency without a disruptive core-system migration. However, the practical depth of integration — real-time synchronisation versus periodic file transfers, and the range of supported platforms — depends on the specific connectors and configuration offered. These details are not stated in the available information, so they should be confirmed directly with the vendor.

For comparison, other insurance technology providers such as Verisk and Moody's also supply risk data and analytics to insurers, though with different specialisations.