A Comprehensive Guide
ScienceSoft applies 10 years of experience in insurance software development and 33-year expertise in digital transformation to help insurance companies automate their business processes.
The Essence of Insurance Automation
Insurance automation aims to eliminate manual workflows across underwriting, billing, claim processing, policy updating, and other insurance-related processes.
Automated insurance systems rely on advanced techs (cloud, AI, big data, blockchain, etc.) to help insurers make their business operations more efficient and ensure the company’s sustainable growth.
- Key integrations: a CRM, payment gateways, accounting software, a BI solution, etc.
- Implementation time: 10–18+ months for a custom insurance automation system.
- Development costs: $200K–$4M+, depending on the automation scope and complexity.
- A payback period: 6–12 months on average.
Main Use Cases of Insurance Automation
Automate up to 80% of tasks and enjoy a 2–5x faster cycle with >99% accuracy of underwriting operations.
Drive >50% increase in the productivity of your insurance team and benefit from 3x faster policy creation, updating, and renewal.
Eliminate ~90% of manual tasks and decrease costs by up to 80% while getting a 2–3x faster billing process.
Employ cognitive techs to accept, verify, process securely and error-free, and settle claims in minutes rather than days.
Be 100% sure of your compliance with all insurance-specific legal requirements and data protection standards with real-time compliance checks and automated compliance reporting.
Rely on intelligent virtual assistants to process >50% of omnichannel customer inquiries and improve the SLA performance for key metrics by >20%.
Customer onboarding and pre-qualification
- Configurable self-registration forms for individual and corporate customers.
- Automated capture and validation of customer personal and business information using OCR, RPA, and AI technologies.
- Geography-based KYC/AML verification for customers.
- Automated customer pre-qualification against the pre-set internal requirements: age, location, income sustainability, owned asset value, etc.
- Data-driven customer segmentation by user-defined criteria: age, gender, lifestyle (for individuals), industry, location (for businesses), and more.
- Automated processing of insurance applications.
- AI-based assessment of customer risks based on the analysis of:
- Data provided by customers.
- Data available from third-party sources.
- The customer’s past insurance coverage and claims history, if any.
- User-defined rules for the insurance premium and coverage segmentation based on:
- The type of insurance policy.
- Customer creditworthiness, health risks, location, claim history, and more.
- AI-supported recommendations on optimal premium amounts and insurance limits for particular customers and customer segments.
- Customizable templates for various types of insurance policies: life insurance, health insurance, property and casualty insurance, etc.
- Automated policy generation and submission to customers (via email, messaging apps, or a customer portal).
- Automated policy update (customer data, coverage and premium terms).
- Rule-based policy renewal.
- Instant communication of policy updates to the policyholders.
- Template-based creation of customer invoices, including multi-currency and multi-language ones.
- Calculating a customer-specific premium and applying it to the invoice.
- Signing invoices using an e-signature.
- Support of multiple payment methods, including bank transfers, credit cards, checks, etc.
- Automated payment processing via the connected payment gateways.
- Real-time invoice tracking by status (sent, paid, due, etc.).
- Automated aggregation and processing of claims from a customer portal, emails, phone calls, etc.
- AI-based validation of claim-supporting documents: medical reports, accident reports, photos or videos of damaged property, etc.
- Automated identification of fraudulent insurance claims.
- AI-powered damage estimation and claims triage.
- Automated assignment of claim management tasks based on employees’ qualification, availability, location, etc.
- User-defined rules for claim approval or rejection.
- Calculating the due claim payment amount.
- Instantly communicating claim-related decisions to customers.
- Automated payment of approved claims.
Analytics and reporting
- Calculating and monitoring the essential metrics: underwriting, claim management, financial performance, workforce, etc.
- Configurable analytical dashboards for various user roles: sales agents, underwriting specialists, claim managers, financial analysts, etc.
- Automated generation of insurance reports.
- Scheduled and ad hoc report submission to the required legal regulators.
- Trend-based forecasting of insurance demand, revenue and expenses.
- AI-powered analysis of customer behavior.
Customer self-service portal
- Customer self-registration, managing and updating personal or business information.
- Template-based creation of insurance applications.
- Paying premium by a preferred payment method.
- Filing and submitting claims.
- Notifications to customers about the application and claim status changes, expiring documents, etc.
- Instant messaging.
- AI-powered virtual assistant to help customers solve operational, technical, and security issues.
- (optional) A self-service insurance price calculator.
Security and compliance
- Compliance with KYC/AML and OFAC requirements, IFRS17, CCPA, CPRA, GLBA, SOC1 and SOC2, SAMA requirements (for the KSA), MCEV principles and GDPR (for the EU), NYDFS (for New York), HIPAA (for health insurance), other relevant global, local, and industry-specific regulations.
- Real-time compliance monitoring.
- Scheduled compliance reports.
- End-to-end audit trail of insurance activities.
- Permission-based access control.
- Multi-factor authentication.
- Insurance data encryption.
- (optional) Insurance data hashing, timestamping, and recording in the immutable blockchain ledger.
- For calculating the expected demand and data-driven planning of distribution and marketing activities.
- For informing the insurance teams about the planned promotions of particular insurance products.
For automated recording of insurance-related financial transactions in the general ledger.
For comprehensive insurance analytics and advanced visualization and intuitive reports.
Third-party data sources
For accurate risk assessment, insurance pricing, claim validation, and damage estimation.
- Internal systems of the local credit rating bureaus, medical information bureaus, department of motor vehicles, etc.
- IoT ecosystems of commercial customers, smart utility companies, telematics providers, connected-health providers, etc.
For fast and convenient customer interaction.
Mail services, messaging services, VoIP systems, etc.
Success Factors for Insurance Automation
ScienceSoft’s experience shows that a ROI for the insurance automation system can be achieved in 6–12 months on average. To maximize the solution’s value for the client’s internal processes and drive faster payback from insurance automation, we always cover the following important factors:
To eliminate manual workflows across the entire insurance cycle, from underwriting, through claim processing, to policy renewal.
To get data-driven risk assessment and optimal, risk-based insurance pricing, promptly identify insurance fraud, and more.
To process insurance-related data in accordance with up-to-date legal requirements.
Proper user training
To help insurance teams quickly learn how to apply automation to streamline their daily tasks.
From ScienceSoft’s experience, an insurance automation project for an upper-midsize company may cost around $200K–$1.5M. Large enterprises with complex insurance processes should expect to invest $1M–4M+.
The costs and timelines of implementing custom insurance automation solution vary greatly depending on:
- The number and specifics of insurance processes (e.g., underwriting, billing, claim management, etc.) to automate.
- Functional complexity of the automation system, including the implementation of features powered with advanced techs (e.g., blockchain for insurance).
- Performance, availability, scalability, security, compliance requirements.
- The scope and complexity of integrations.
- The number of user roles.
- The sourcing model (full outsourcing, team augmentation, or all in-house) and team composition.
Financial Outcomes of Insurance Automation
to achieve full payoff of investments in automation
Up to 50% increase
in the overall business efficiency and profitability
in operational costs, including labor and IT infrastructure costs
of financial losses associated with non-compliance and insurance fraud
Companies that need to automate complex or unique insurance operations.
Companies that want to get intelligent guidance on specific insurance-related decisions.
Companies that operate in multiple countries and need to comply with numerous local insurance regulations.
Companies that want smooth and cost-effective integration of insurance automation software with their legacy corporate tools.
Companies with large insurance teams that want to avoid a considerable subscription fee for off-the-shelf insurance tools, which scales as the number of users grows.
Companies that need advanced data security.
Companies that want to leverage smart contracts for insurance automation.
Companies that start their digital insurance journey and want to build their business software ecosystem around a comprehensive insurance automation system.
Insurance Automation with ScienceSoft
In insurance software development since 2012, ScienceSoft provides a full scope of required services to help insurance companies plan and introduce robust business process automation.
Depending on your needs, we can build your insurance automation system from scratch or based on a low-code platform (e.g., Microsoft Power Apps). Although the latter option offers less flexibility in terms of UX and UI design, it proved to bring 70%+ reduction in development costs.
ScienceSoft is a global IT consulting and software development company headquartered in McKinney, Texas. Since 2012, we design and build robust solutions to help insurance companies automate their business processes. Being ISO 9001- and ISO 27001-certified, we apply a mature quality management system and guarantee that cooperation with us does not pose any risks to our customers’ data security.