Bringing 11 years of experience in insurance software development, ScienceSoft delivers solutions for prompt and smooth automation of underwriting processes.
Underwriting Automation in a Nutshell
Underwriting automation is meant to eliminate low-value manual efforts across insurance application processing, risk assessment, premium calculation, policy issuance and renewal.
An automated underwriting system can be augmented with artificial intelligence (AI) to provide intelligent guidance on optimal insurance pricing and enable instant detection of insurance fraud.
- Key integrations: CRM, a customer portal, a claim management system, accounting software, etc.
- Implementation time: 9–12+ months for a custom underwriting automation system.
- Development costs: $200K–$500K+, depending on the solution’s complexity.
- Average payback period: <12 months.
Main Underwriting Areas to Automate
Employ AI, RPA, and NLP techs to get instant aggregation and 100% accurate processing of insurance applications and customer documents. <5% of processing tasks will require human involvement.
Leverage intelligent triaging and automated assignment of underwriting tasks to maximize revenue potential and drive high team’s performance.
Use advanced big data analytics and integrate your underwriting solution with multiple data sources to get precise assessment of customer-associated risks in minutes rather than days.
Apply AI to ensure efficient, fair, and competitive insurance pricing. Implement an innovative dynamic pricing model to drive up to 15% growth in revenue.
Drive the increase in customer satisfaction and maintain high retention rate by offering 95% faster issuing, updating, and renewal of insurance policies thanks to the end-to-end automation of a policy cycle.
Achieve 100% compliance of underwriting operations with the internal policies and required legal regulations with no manual hassle by applying regular automated compliance checks.
Key Features of an Underwriting Automation System
ScienceSoft creates automated underwriting solutions with unique functional capabilities tailored to each of our clients’ specific needs. Below, our consultants compiled a list of features that form the core of a comprehensive underwriting automation system:
Automated processing of insurance applications
- Automated conversion of paper application documents into a pre-defined digital format using optical character recognition (OCR).
- Support for various insurance application formats (PDF, XML, digital images, etc.).
- ML-supported data extraction from insurance applications.
- AI-based validation of insurance applications.
- Flagging the applications that contain missing, inaccurate, or contradictory data and automatically routing them for manual check.
- AI-powered triaging of insurance applications based on their expected profitability.
Task management automation
- Automated task assignment to the underwriters based on their qualification, availability, location, etc.
- Automated creation and updating of underwriting task lists.
- Rule-based prioritization of underwriting tasks.
- Configurable dashboards providing underwriters with an overview of assigned tasks, their priority and deadlines.
Automated risk assessment
- AI-powered evaluation and scoring of customer-associated risks (mortality risks, health risks, financial risks, property risks, driving risks, etc.) based on the analysis of:
- Data and documents submitted by customers (bank statements, proof of employment, medical history, etc.).
- Data obtained from the third parties (e.g., credit rating bureaus, medical information bureaus).
- (for existing clients) A customer’s past insurance coverage and claims history.
- User-defined rules for customer segmentation based on the risk score.
- Configurable insurance coverage terms for various customer segments (e.g., offering lower coverage amounts for clients with higher risk scores).
- AI-supported decision-making on the insurance application approval or decline.
Insurance pricing automation
- User-defined rules for automated segmentation of insurance prices based on:
- The type of insurance policy (e.g., applying a higher premium amount to the extreme sports insurance).
- Customer financial status, health status, location, claim history, etc. (e.g., charging higher premiums from smokers, customers from regions with high frequency of natural disasters, etc.).
- Scenario modeling and what-if analysis for various insurance pricing strategies.
- AI-supported calculation of the optimal insurance prices based on the analysis of:
- Customer-associated risks.
- Price elasticity of demand for each customer segment.
- Insurance product profitability.
- User-defined price optimization rules (e.g., keeping prices within specified thresholds).
- Automated communication of the estimated insurance price to the insurance agent and the customer.
- Automated generation of insurance policies.
- Automated multi-department policy approval workflow.
- E-signing of the insurance policies.
- Scheduled and ad hoc policy submission to customers.
- Insurance billing automation.
- Automated policy updating with the new policyholder data, coverage and premium terms triggered by the request from a customer or changes in the insurer’s internal policies.
Dynamic insurance pricing
- AI-enabled real-time calculation of optimal personalized insurance prices based on:
- A policyholder’s geographic location.
- Type of activity the insured is involved in and their health state.
- (for commercial insurance) Facility conditions and asset utilization.
- (for driving and carrier insurance) Driving behavior, traffic and weather conditions.
- User-defined triggers for the automated insurance repricing, e.g., change in a customer’s location or lifestyle, unsafe manufacturing or driving conditions, etc.
- Instant notifications to customers on the insurance price updates.
Analytics and reports
- Real-time calculation of the essential underwriting metrics, such as insurance sales by period, new policies per agent, an average policy amount, underwriting speed, customer retention rate, etc.
- Template-based creation of underwriting reports.
- ML-powered forecasting of insurance demand, revenue, and expenses based on the analysis of customer purchasing behavior, risks, loss history, competitors’ prices, and more.
Security and compliance
- AI-powered detection of underwriting fraud.
- Full audit trail of underwriting activities.
- Compliance with KYC/AML and OFAC requirements, IFRS17, CCPA, CPRA, GLBA, SOC1 and SOC2, NYDFS cybersecurity requirements (for New York), SAMA regulations (for the KSA), MCEV principles and GDPR (for the EU), HIPAA (for health insurance), and more.
- Role-based access control.
- Multi-factor authentication.
- Data encryption.
Essential Integrations for an Automated Underwriting System
ScienceSoft recommends establishing the following key integrations to minimize human involvement in the underwriting operations and accelerate the underwriting cycle:
- For faster processing of insurance applications.
- To instantly inform the customers on the insurance approval or decline and speed up policy submission to the clients.
- To streamline policy creation and renewal.
- To keep the insurance agents up to date on the issued policies and due premium amounts.
- For data-driven planning of marketing and distribution activities.
- To consider a customer’s claim history when recalculating the insurance premium.
- For streamlined claim validation.
- To automatically record data on due payments in the general ledger and the accounts receivable ledger.
- To timely trigger insurance termination.
Third-party data sources
For data-driven risk assessment and pricing, real-time premium recalculation under a dynamic pricing model.
- Internal systems of the credit rating bureaus, medical information bureaus, social security administration, police administration, etc.
- IoT ecosystems of commercial customers, telematics providers, smart utility companies, etc.
For seamless omnichannel interaction with customers.
Mail services, messaging services, auto dialing systems, etc.
Underwriting Automation Costs and Financial Outcomes
From ScienceSoft’s experience, a custom automated underwriting solution of average complexity costs around $200K–$400K. Building a comprehensive underwriting automation system powered with advanced analytics may cost $500K+.
Want to know the cost of your underwriting solution?
The investments in the insurance underwriting automation typically pay off within 12 months.
Among the most notable financial benefits of underwriting automation are:
Up to 40% decrease
in underwriting costs, including labor costs and IT infrastructure costs
in revenue due to optimized insurance pricing and growth in capacity
NB! ScienceSoft can build your underwriting automation system from scratch or based on a low-code platform (e.g., Microsoft Power Apps). The latter option offers up to 70% development cost savings. However, it doesn’t allow introducing custom UX and UI design and provides limited room for advancing the solution’s performance.
So, How to Achieve Max ROI for Underwriting Automation?
Relying on 11-year expertise in insurance digitalization, ScienceSoft’s consultants defined a range of factors that help drive high payback from an automated underwriting system:
Maximized degree of automation
To free the underwriting team from the time-consuming manual tasks, such as processing insurance applications, scoring customer risks, generating and updating insurance policies, and more.
Leveraging versatile data from all the relevant sources
To calculate insurance prices with full insight into the customers’ financial risks, health risks, business specifics, lifestyle, location, and other available risk and profitability factors.
To get precise risk assessment and intelligent recommendations on the optimal personalized premium amounts and insurance coverage terms.
To prevent insurance fraud, sensitive data leakage and guarantee reliable protection against cyber attacks.
When to Opt for a Custom Underwriting Automation Solution
ScienceSoft’s experts recommend custom development in the following cases:
You need to automate complex or unique underwriting workflows, for example:
You want to employ advanced techs to power particular underwriting processes, e.g.:
You want smooth and cost-effective integration of underwriting automation software with all required systems, including legacy corporate tools.
You need a solution that provides compliance with necessary legal regulations, including local insurance regulations.
Underwriting Automation with ScienceSoft
In insurance software development since 2012, ScienceSoft provides full-scale consulting and development services to help establish effective underwriting automation.
Underwriting Automation for a Global Insurance Carrier
ScienceSoft designed and built underwriting automation software for one of the world’s fastest growing insurance organizations with over $30B in assets and underwriting capacities in 120+ countries. The solution provides robust automation of business-specific underwriting processes, including:
- Customer risk assessment.
- Personalized premium calculation.
- Quote generation.
- Policy issuance and updating.
- Underwriting compliance monitoring.
- Fraud detection.
ScienceSoft is a global IT consulting and software development company headquartered in McKinney, Texas. Since 2012, we help insurance companies implement robust underwriting automation. 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.