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Claims Processing Automation

A way to unlock up to a 30% reduction in claim handling costs

ScienceSoft applies 12 years of experience in engineering insurance solutions to introduce effective automation of claim management processes.

Claim Management Automation - ScienceSoft
Claim Management Automation - ScienceSoft

Contributors

Olga Vinichuk

Insurance IT Consultant

Alex Ramasheuski

Head of Enterprise Application Development, ScienceSoft

Automated Claims Processing: Key Aspects

Claims processing automation helps streamline and speed up the entire insurance claim cycle, from data intake to claim settlement and reporting. Rather than completely remove manual efforts, claims automation aims to minimize low-value tasks and free the employees for handling complex cases.

Automated claims processing software often relies on artificial intelligence (AI) to enable analytics-based claim decisioning, accurate damage estimation, and instant detection of insurance fraud. It helps optimize operational costs and ensure top-flight customer experience.

Custom claim automation systems can also employ advanced technologies like blockchain, IoT, and AR to introduce automated claiming capabilities for policyholders and support seamless loss adjustment and payouts across innovative insurance models like parametric, P2P, or PAYL insurance.

  • Necessary integrations: a customer portal, a policy administration system, accounting software, etc.
  • Implementation time: 9–15+ months for a custom claim management automation system.
  • Development costs: $200,000–$500,000+, depending on the automation solution’s complexity. Use our online calculator to estimate the cost for your case.
  • A payback period: <12 months. Calculate ROI for your tailored solution.

Main Claim Processing Tasks to Automate

Claim validation

Get fast and accurate claim verification with the help of RPA, natural language processing (NLP), and intelligent document processing (IDP) techs. Employ advanced analytics to instantly spot fraudulent claims and prevent illegitimate payouts.

Loss estimation

Harness the power of ML, big data, IoT, and computer vision to automatically collect and process contextual data on loss events, enable remote damage inspection in complex environments, and get precise data-driven damage assessment.

Claim settlement

Set custom flows and leverage intelligent automation (IA) to get profitability-based claim triaging, straight-through decisioning for standard claim cases, and quick payouts according to pre-agreed schemes.

Customer interaction

Rely on AI-powered virtual assistants to establish automated personalized customer interactions via the client’s preferred method of communication.

Did you know?

In its recent research, Capgemini names insurance claim processing among the primary BFSI automation use cases that deliver high value with a short payback. According to Accenture, while only 44% of claims executives say their organizations are mature in the use of automation and AI/ML, 80% believe that digital techs can benefit significantly each area of the claims value chain. Unsurprisingly, insurers globally accelerate investments in claim automation, with 65% planning to invest over $10M into cognitive automation by 2025.

How to Automate Claim Processing

Market-available insurance suite

Ready-made automated claims processing software

Custom claim processing system

ScienceSoft recommends

Essence

Implementing an all-in-one insurance software product that includes digital claim processing capabilities.

Implementing an off-the-shelf claims automation tool, which usually features RPA-based processing of claim documents, rule-based claim approvals, scheduled compensation payments, and automated loss reports.

Engineering custom claims processing automation software to get all necessary capabilities, support all required insurance models, and achieve 100% compliance with all relevant legal frameworks.

Pros

Establishing a cohesive insurance automation environment.

A quick and budget-friendly way to automate claims for insurance SMBs.

Fully tailored functionality. The ability to leverage advanced techs. On-demand scalability. Controllable security. Cost-effective integration with all necessary systems, including legacy software and IoT solutions.

Cons

High licensing/subscription cost due to a wide scope of covered insurance areas. Chances to obtain a large share of unnecessary features. Limited integration capabilities. Risks of vendor lock-in.

Pre-defined features and integrations. Customization to support specific insurance types can be costly or impossible. May not provide compliance with your local insurance standards. Security fully depends on the vendor’s cybersecurity practices.

Custom design requires additional time and investments.

TCO components

Setup costs + customization and integration costs + licensing/subscription fees.

Setup costs + customization and integration costs + ongoing subscription fees that scale with the number of users.

Upfront investments in software design and development.

Lower TCO in the long run.

Which Claims Automation Option Fits Your Needs Best?

Answer a few simple questions and find out whether you should go for a custom system or a pre-built tool.

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You can go with off-the-shelf automation software

Looks like market-available tools are a viable option to meet your claims automation needs. Turn to ScienceSoft if you need help with picking the optimal tools, their implementation, customization, or integration with your existing systems.

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You definitely should consider custom development

A custom claim automation solution will help you reap the unique benefits that market-available software cannot offer. Turn to ScienceSoft to get a detailed assessment of a custom system’s feasibility for your business situation.

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Custom claim processing software is your best choice

Looks like market-available automation tools don’t fit your specific requirements and won’t be able to provide the expected operational and economic feasibility. Turn to ScienceSoft to get a free consultation on custom claim processing software and receive cost and ROI estimates.

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Key Features of a Claims Processing Automation System

In our insurance claim automation projects, ScienceSoft designs and builds solutions with functionality bound to each client’s unique claim management needs. Below, our consultants list the core features most commonly requested by our clients:

Claim data processing

  • Automatic aggregation of insurance claims from multiple channels: a customer portal, emails, phone calls, etc.
  • Automated data extraction from the First Notices of Loss (FNOL) and claim-supporting documents (medical reports, accident reports, photos or videos of damaged property, travel documents, etc.).
  • Support for claim documents in various formats: text, PDF, image, audio, video, and more.
  • Automated conversion of paper claim documents to a digital format using optical character recognition (OCR).
Read more

Claim validation

  • AI-powered claim validation against the insurance coverage terms based on the data provided by the policyholder or insurance agent and data from trusted third-party sources like medical information bureaus, police administration, GIS and telematics platforms, public fraud databases, etc.
  • Intelligent detection of fraudulent claims.
  • Rule-based routing of claims that contain incomplete, inaccurate, or contradictory data for manual check.
Read more

Claim decisioning

  • User-defined rules for claim approval or rejection, e.g., rejecting fraudulent, late, partially or wrongly disclosed claims.
  • AI-powered claim-related decision-making.
  • Instant communication of claim decisions to customers.
Read more

Claim triaging

  • AI-supported claim triaging based on the analysis of claim urgency, damage extent, injury severity, financial and reputational risks associated with non-settlement, etc.
  • User-defined rules for claim prioritization based on the claim date, claim amount, policyholder value, etc.
Read more

Damage estimation

  • Remote damage inspection and loss evaluation using AIoT and computer vision.
  • AI-powered damage assessment based on the analysis of claim-supporting documents and the relevant data from external sources.
  • Template-based creation of damage estimation requests and sending them to the relevant in-house experts (e.g., engineers, medical experts) or third-party damage assessment service providers.
  • Automatically calculating the due claim payment amount.
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Claim settlement automation

  • AI-based suggestions on the best-fitting damage handling service providers (e.g., particular healthcare organizations, car repair companies, etc.) to recommend to customers.
  • Automated claim payments (full, partial, split, recurring payments), including:
    • Compensation payments to policyholders.
    • Direct payments to the damage handling service providers.
  • Domestic and cross-border claim payouts.
  • Real-time monitoring of the claim settlement progress and claim costs.
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Claim prevention

  • AI- and IoT-enabled monitoring of real-time loss event risks based on:
    • Policyholder behavior, location, and health state.
    • The state of insured assets (physical and digital) and asset environments/markets.
    • Weather and traffic conditions.
    • Healthcare, geopolitical, and economic sentiment.
  • Real-time recognition of high-risk events.
  • Intelligent recommendations on the proper course of action for policyholders to prevent losses (communicated via an insurance app, email, or messaging apps).
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Task management automation

  • Automatically assigning claim processing tasks to the insurance team members based on their qualifications, availability, location, etc.
  • Automated generation of employee task lists with case-specific KPIs.
  • Rule-based routing of omnichannel customer requests to the appropriate claim specialist.
  • An AI-powered virtual assistant to handle customer interaction tasks: responding to simple inquiries, providing 24/7 support, routing customer requests to the relevant specialists, etc.
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  • Real-time calculation and monitoring of the essential claim metrics: claim volume by period, average time to settle a claim, average cost per claim, claim frequency, claim severity, loss ratio, etc.
  • Automated claim and loss run reports.
  • Scheduled and ad hoc report submissions to the required regulators.
  • AI-powered forecasting of claim costs (by period, customer, region, etc.) based on the analysis of the claim payment history, customer risks, force majeure risks (e.g., natural disaster risks), and more.
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Security and compliance

  • Compliance with NAIC, NICB, CCPA, CPRA, GLBA, FROI/SROI, COBC, OSHA, OFAC, local DCI requirements, SOC1 and SOC2, SAMA and IA 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.
  • End-to-end audit trail of claim management activities.
  • Role-based access control.
  • Multi-factor authentication.
  • Data encryption.
Read more

Get Effective Claims Management Automation

ScienceSoft’s team is ready to build a robust automated claim processing system to spur the increase in your claim management team’s productivity and reduce claim resolution costs.

Essential Integrations for an Automated Claims Processing System

Integrating claim processing software with the relevant back-office and third-party systems helps achieve a higher degree of automation and instantly access the required claim-related data. ScienceSoft recommends establishing the following integrations:

Essential Integrations for an Automated Claim Management System - ScienceSoft

  • Customer interaction channels (a customer portal, email services, messaging services, a business phone system, etc.) - for instant claim aggregation and facilitated claim status reporting to customers.
  • Policy administration system - for streamlined claim validation.
  • Third-party data sources (internal systems of medical information bureaus, police administration, etc.; social media) - for data-driven claim decisioning and damage assessment.
  • Tracking solutions (IoT ecosystems, computer vision systems, and asset monitoring software of the insurer, commercial customers, third-party telematics providers, etc.) - for fast and precise damage estimation.
  • Vendor management software - for prompt selection of optimal health and repair service providers to recommend to policyholders subject to damage.
  • Accounting system - for automated recording of claim payment transactions in the general ledger.
  • Financial planning and analysis software - for accurate planning of claim handling expenses.
  • Business intelligence solution - for comprehensive claim analytics and reporting.

Success Factors for Claim Process Automation

According to McKinsey, RPA-enabled process automation alone can bring up to 200% annual ROI. Additionally, covering the following important factors will help you drive even higher payback from automating your claim management operations.

AI-powered analytics

To leverage no-touch claim processing, instantly detect fraudulent claims, and rely on intelligent decision-making.

Integration with multiple data sources

To verify claims and evaluate damage with full insight into the claim case details, customer behavior, and external conditions.

System scalability

To smoothly process abnormally large volumes of claims caused by external factors (e.g., claim handling during natural disasters or spikes of the COVID-19 pandemic).

ScienceSoft’s Insurance IT Consultant and Business Analyst

Expert advice

To avoid penalties for non-compliance and reputational damage, make sure your automated claim processing system meets the legal framework and can be easily evolved to adopt frequent changes in regulatory requirements.

ScienceSoft’s Featured Claim Automation Projects

What Our Clients Appreciate about ScienceSoft

What stood out was ScienceSoft's proactive suggestions for cost-saving architecture design and tech stack solutions. Their input ensured we stayed within budget without compromising on software quality.

We are impressed with ScienceSoft’s pragmatic project management, quality-first mindset, and transparent communication. They are strongly motivated to deliver maximum value with their services.

Thanks to ScienceSoft, we achieved our project goals on time and within budget. They provided high-quality service and valuable tech insights that aligned well with our vision and specific needs.

Claims Processing Automation Costs

Implementing claims automation for a midsize insurance company may cost around $200,000–$500,000+, depending on the scope and complexity of an automated claim processing system.

Below, we provide the approximate cost estimations based on ScienceSoft's experience in claim management automation projects:

$200,000–$400,000

Development of a custom automated claims processing software of average complexity.

$500,000+

Building a comprehensive custom claim processing system powered with advanced techs.

NB! If you don’t have specific requirements for the UX and UI design, ScienceSoft suggests building your claim processing automation system based on a low-code platform (e.g., Microsoft Power Apps). Our experience shows that this option helps reduce the development cost by up to 70%.

Key Benefits of Automated Claims Processing

Faster claims processing

Automation drives around an 80% reduction in claim processing time, enables insurers to cut the turn-around time for claims recovery by over 30%, and helps establish 85%+ faster claim reporting flows.

Accurate fraud detection

According to the FBI, 5–10% of non-health insurance claims are fraudulent, costing more than $40 billion annually for US insurers alone. Employing IA for claims validation can help insurers achieve 95% accurate fraud detection and avoid financial losses.

Higher back-office efficiency

Automated claims solutions offer straight-through processing for more than 50% of claim cases, eliminating lower-value claim specialists’ tasks and bringing a 25–35%+ increase in the team’s productivity.

Reduced operational expenses

By automating claims, insurers benefit from around a 30% decrease in claim processing costs due to removed operational waste and better team performance. Employing an AI-powered solution can bring over a 70% increase in claims process cost efficiency.

Enhanced customer experience

Digital claims systems cater to claimants’ needs more precisely so that customers can get convenient self-service options, 24/7 support, and faster claim resolution. For insurers, this means delivering better customer experiences and achieving a 10–15-point increase in CSAT.

Claims Processing Automation with ScienceSoft

In insurance software development since 2012, ScienceSoft provides comprehensive consulting and engineering services to build robust automated claims processing solutions.

Claim management automation consulting

We create a detailed concept of your claim processing automation system and provide expert advice on the use of advanced techs. You also receive an implementation roadmap with cost and time estimates and get expert advice on legal compliance.

I need this!

Implementation of automated claim processing

We cover end-to-end development of a claims automation solution or revamp your existing claim processing tool. You benefit from fast implementation and excellent software quality. Also, you get smooth integration with all the required software and hardware.

I need this!

What makes ScienceSoft different

We achieve project success no matter what

ScienceSoft does not pass mere project administration off as project management, which, unfortunately, often happens on the market. We practice real project management, achieving project success for our clients no matter what.

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About ScienceSoft

About ScienceSoft

ScienceSoft is a global IT consulting and software engineering company headquartered in McKinney, Texas. Since 2012, we have been helping insurance companies implement effective claim processing 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 clients’ data security.