About
Innowise has implemented RPA to automate claim processing, underwriting, pricing, fraud detection, regulatory compliance, and more. Our customer offers a diverse portfolio of insurance services, including auto, property & casualty (P&C), life, and commercial insurance. The company has become a trusted name in the insurance field, providing a wide range of solutions tailored to multifaceted needs for both individuals and businesses.
Challenge, approach, and impact
Challenge
Client faced insurance automation issues: errors in policy inquiries, manual claims, risk assessment, and admin. Managers labored over verifying data from police reports, damage photos, and medical records, leading to delays, inefficiencies, and fraud risks. Innowise was tasked with streamlining claims, fraud detection, underwriting/pricing, policy admin, compliance, and faster customer responses via RPA and AI
Claims registration
First, RPA developers automated claims registration/processing and fraud detection using OCR-based data extraction from police reports, damage photos, and medical records. AI algorithms then verified data accuracy, flagging inconsistencies for review. A centralized repository consolidated datasets, eliminating redundancy and turning fragmented info into actionable insights for reliable claims handling.
Underwriting & pricing
Using data integration tools, the team aggregated internal/external sources for risk evaluation and analysis. Advanced analytics on historical claims, losses, and patterns provided underwriting insights based on comprehensive client risk profiles. AI-driven ML models optimized premium calculations and revenue planning using customer claims and risk factors, aligning pricing strategies with risk appetite and market positioning.
Settlement automation
Besides adopting RPA for claims processing, underwriting, and pricing, we automated transactional tasks such as accounting, settlements, risk capture, credit control, and tax. RPA bots handled repetitive tasks by calculating settlement amounts, initiating payments, and updating policy records, speeding up settlements and reducing errors. They also monitored premiums, generated breach alerts, and froze transactions on credit limit violations, improving control and compliance.
Fraud Detection
RPA bots with machine learning analyzed policy applications and claims to detect fraud patterns and anomalies by comparing against historical data. Suspicious inconsistencies or deviations from trends were flagged immediately for specialist review. This triggered alerts to initiate investigations and actions, enhancing fraud prevention efficiency in insurance processes.
Regulatory compliance
RPA bots conducted comprehensive compliance checks, verifying policies, client details, and transactions against industry regulations. They authenticated client information like IDs and financial records via external sources, ensuring profile accuracy. RPA enforced data security with access controls, encryption, and GDPR compliance, monitoring sensitive data to prevent breaches and maintain privacy standards
How we built
Testimonials
Anonymous
“As the RPA Project Manager at Innowise for this insurance automation project, I am thrilled with the transformative results we delivered. Using Agile sprints, our team automated claims processing, underwriting, fraud detection, and compliance, achieving 27% faster claim registration and 34% more accurate pricing. The ML-enhanced RPA bots eliminated manual errors, streamlined paper-heavy tasks, and ensured GDPR compliance, boosting operational efficiency and allowing managers to focus on high-value work. This project exemplifies Innowise's expertise in driving business continuity and client success through intelligent automation“
Team structure
Client team
Karl
Product Manager
The client stakeholders were working closely with the team at Innowise Sp. z o.o
Agency team
RPA Developer
Production
RPA Business Analyst
Production
Solution Architect
Production
UiPath Orchestrator Administrator
Production
