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Custom Insurance Risk Management Software

ScienceSoft applies 12 years of experience in insurance IT and 35 years in data analytics to create robust solutions that help insurance businesses digitally transform their risk management operations.

Custom Insurance Risk Management Software - ScienceSoft
Custom Insurance Risk Management Software - ScienceSoft

Insurance Risk Management Software: Key Aspects

Insurance risk management software helps insurance companies identify and proactively address risks related to the insured subjects and assets, insurance service operations, and strategic business activities. Such software offers automated risk modeling, quantification, forecasting, and reporting.

Custom insurance risk management software can provide a 360-degree view of company-specific risk indicators and enable real-time evaluation of risk impact based on advanced statistical techniques. Custom solutions can also be powered with artificial intelligence to provide real-time risk analytics and data-driven guidance on the optimal risk prevention steps.

  • Implementation time: 9–15+ months for a custom system.
  • Development costs: $200,000–$600,000+, depending on software complexity. Use our free calculator to estimate the cost for your case.
  • Necessary integrations:

Why Opt for Custom Insurance Risk Management Software

Most market-available insurtech risk management tools fall under one of two large categories:

  • Customer risk management tools focus on evaluating client-side loss risks, planning loss reserves, and calculating policy prices. Such solutions cover the functionality of insurance actuarial software and may include loss risk monitoring capabilities.
  • Enterprise risk management solutions for insurance focus on recognizing and addressing risks across an insurer’s operational and strategic activities, including customer service management, financial management, and compliance management.

Custom software effectively tackles the limited functional scope of niche solutions and enables cohesive automation of insurance risk management workflows. All-in-one custom solutions can combine the required enterprise and customer risk features, allowing insurers to seamlessly leverage client risk projections for company-wide risk response planning.

Insurance Risk Factors Software Helps Control

ScienceSoft creates custom insurance risk management solutions tailored to each insurer’s needs. We deliver large-scale integrated systems for organization-wide risk management and specialized custom insurance actuarial software to address client-side risks across various insurance lines.

Depending on software complexity, you get the possibility to control the following risk factors:

Client-side risk factors

  • Insurance customer’s claims history.
  • Insured person’s health state, occupation, solvency, and behavior.
  • Insured asset’s characteristics, state, and performance.
  • Insurance business’ financial posture and operational practices.
  • Severity of external perils (natural disaster, traffic disruption, economic crisis, etc.).
  • Financial impact of potential loss events.

Insurance business risk factors

  • Insurance sales.
  • Loss ratio and compensation amounts.
  • The number of fraudulent claims.
  • Corporate financial performance (liquidity, profitability, capital reserves).
  • Employee productivity, turnover, and retention.
  • The number of compliance violation cases.
  • Reputation (CSAT, NPS, customer sentiment).

Key Features of Insurance Risk Management Software

Below, ScienceSoft’s consultants share a comprehensive list of features that would form the core of a multi-functional insurance risk management solution.

Depending on your needs, we may implement one of the functional blocks, a particular feature module, or the entire scope of features for customer and business risk management.

Insurance customer risk management

Risk data processing

  • Batch or real-time aggregation of customer-associated risk data from internal and third-party sources:
    • Data submitted by customers for underwriting (bank statements, proof of employment, medical history, etc.).
    • The insured asset characteristics (value, location, conditions, etc.).
    • Location-specific climate, geopolitical, demographic, and economic data.
    • A customer’s past insurance coverage and claims history.
    • FNOLs and claim-supporting documents (medical reports, accident reports, etc.).
  • Support for data in various formats: JSON, CSV, XML, PDF, text, digital images, recorded voice messages, streaming video, etc.
  • AI-powered data pre-processing (structuring, cleansing, enrichment) and validation (including cross-referencing with third-party sources).
  • Centralized storage of the collected data.
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Risk impact assessment

  • Scenario modeling and analysis (including ML-based analysis, what-if analysis, event tree analysis, fault tree analysis, failure modes and effects analysis, etc.) to determine:
    • Insurance risk probability under particular customer-side events.
    • The impact of different insurance risk factors on the associated loss events, e.g., how the insured property characteristics affect P&C loss probability or how the client’s health state affects mortality.
  • Monte Carlo simulations to predict and measure the impact of external uncertainty factors, such as accidents involving insured persons, natural disasters, geopolitical force majeure, changes in regulatory compliance requirements, etc.
  • Scoring the potential insurance risk impact based on custom insurance actuarial formulas.
  • Custom rules for individual and corporate customer segmentation by insurance risk classes.
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Risk pricing and loss reserving

Rule-based and ML-supported calculation of the expected loss amounts based on:

  • Existing liabilities.
  • Historical claim frequency and severity.
  • Past claim payouts and expenses related to claim investigation and settlement.
  • Calculating personalized and segment-specific insurance premiums based on the requested policy terms, customer risks and profitability, loss probability, region-specific taxes, and more.
  • Calculating loss reserves under various reserving methods: distribution-free chain-ladder method, Bornhuetter–Ferguson method, average cost per claim method, etc.
  • AI-based suggestions on the optimal loss reserves based on the analysis of historical and expected losses, premium and investment income, costs of unforeseen events, reinsurance coverage, and more.
  • Real-time monitoring of the current vs. planned loss reserve budget utilization.
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Prescriptive loss risk mitigation

  • AI- and IoT-enabled assessment of loss event probability based on:
    • Policyholder location, behavior, and health state.
    • The insured asset and asset environment state.
    • Weather and traffic conditions.
    • Healthcare, geopolitical, and economic sentiment.
  • Real-time detection of high-risk events.
  • Intelligent suggestions on the proper course of action for policyholders to prevent losses.
  • Instant communication of risk mitigation steps to customers via an insurance app, email, or messaging apps.
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Enterprise risk management for insurers

Risk monitoring and analysis

  • Automated calculation of quantitative key risk indicators (KRIs).
  • Rule-based and AI-powered evaluation of qualitative KRIs.
  • Configuring multi-level (low risk, moderate risk, high risk) insurance KRI thresholds based on:
    • AI-powered exposure analysis and suggestions on the appropriate risk limits.
    • User-defined rules (e.g., keeping potential risk impacts within certain tolerances).
  • KRI analysis and real-time spotting of high-risk events.
  • Automated risk segmentation and prioritization for handling based on the impact severity (expected financial losses, operational delays, etc.).
  • Intelligent root cause analysis to determine the reasons behind the changes in particular insurance KRIs.
  • Predictive analytics for risk trend identification.
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Risk mitigation

  • Collaborative creation of insurance risk mitigation strategies and plans.
  • AI-based suggestions on the appropriate risk prevention measures, e.g., optimal insurance product pricing, loss reserving, cash reallocation between the insurer’s bank accounts to meet liquidity needs, task reassignment to handle urgent issues.
  • Automated enforcement of risk mitigation steps (can involve insurance smart contacts to get full traceability of risk responses).
  • Configurable timelines for the implementation of risk mitigation steps depending on the risk priority.
  • Real-time monitoring of the risk mitigation progress and effectiveness.
  • Instant messaging for the insurance teams to collaborate on risk management activities.
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Risk governance

  • Assigning particular risk control tasks to the best-fitting insurance specialists based on their role, qualification, schedule, etc.
  • Configurable multi-department approval workflows for core insurance risks, KRIs, risk limits and exceptions.
  • Permission-based access to particular pieces of risk information.
  • End-to-end audit trail of user activities.
  • Real-time monitoring of the insurance risk management compliance with the internal risk management policies and legal standards, such as ISO 31000, NAIC, NICB, SOX, IFRS17, NYDFS (for NYC), GDPR and Solvency II (for the EU), IA and SAMA (for the KSA), HIPAA (for health insurance), and more.
  • AI-based detection of employee fraud and non-compliance.
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Risk reporting

  • Automated reporting of the required insurance KRIs, risk trends, risk management activities, compliance, and more (by period, location, insurance portfolio, etc.).
  • Customizable report templates for various insurance risks: underwriting risks, claim fraud risks, financial risks, regulatory risks, etc.
  • Support for multiple visualization types for risk analytics, including interactive tables, risk matrices, risk trees, risk heat maps, multi-dimensional charts and graphs.
  • Configurable risk dashboards for various roles: financial analysts, HR experts, compliance auditors, etc.
  • Scheduled and ad hoc risk report submission to senior management and legal authorities.
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Bring Risk Management to the New Level with Tailored Software

ScienceSoft is ready to design and build a reliable solution to boost the efficiency and accuracy of your insurance risk management workflows.