Insurance Data Sheet

Insurance Data Sheet

RPA Insurance Industry Overview

Experts estimate that current RPA technology can save insurers:

• 19% of the time where human expertise is currently required.
• 34% of employee time in the data processing
• 23% of stakeholder interaction time

 

Insurance Industry RPA Use Cases

• Claims Registration, Processing & Fraud Detection
• Underwriting & Pricing
• Policy Administration & Pricing
• Regulatory Compliance
• Responding to Queries
• Business Underwriting

Recovery from third-party insurers

 

Challenge

An insurance company’s claims department faced a frustrating manual process of recovering reimbursements from third-party insurers. The process was expensive and had weak control mechanisms.

 

Solution

The bot automates reconciliations between disparate systems.  It generates chase letters as per defined rules and then processes and sends automatic emails to defrauders.  The bot also enters data in the case of received payments and generates predefined reports of the outstanding matters on a weekly basis.

 

Results

• Faster recoveries
• Increased cash flow
• Low expense ratio
• Reduced cycle time

 

Vendor payments by property insurer

 

Challenge

An Insurance company’s claims unit had challenges in releasing vendor payments within agreed service-level agreements (SLAs). The process was operating in a dual-shore environment, which added to the complexity of the operation. The company identified the process as a major contributor to vendor attrition and customer dissatisfaction.

 

Solution

After a vendor invoice was received, the bot validates the eligibility of the claim against each line item of the invoice.  Each item is audited against a predefined validation process and exceptions were auto-routed, and part payments were released and the vendor e-notified.  Once approved, the balance payments were released.

 

Results

• Improved service levels by converting to a 24 x 7 operation
• 50% reduction in operational costs
• 70% increase in productivity
• Reduced customer complaints

 

Credit limit request underwriting

 

Challenge

A major Insurance company was struggling with their process for underwriting credit limit requests. The work required significant repetitive manual processing and a high cost of operation. Underwriters were manually collecting data from more than 20 screens and external sources before assessing the information.

 

Solution

 A bot was built to automatically collect, assemble, and present data on a dashboard for the underwriter to assess. This dropped the cycle and processing time, allowing the underwriter to focus on high-value customer interactions.  The automation also improved the quality of decisions and provided consistent validation and audit trails of the underwriting data.

 

Results

 Processing time dropped from 4-8 minutes to 2-4 minutes.

• 40-50% reduction in cycle time
• 900 cases automated daily
• 440 hours per month saved

 

Importing and Exporting from statements of account

 

Challenge

An Insurance company’s process for exporting and importing information from statements of account was cumbersome and slow. Employees had to manually process 50 transactions per day, every day, which took them about 10 minutes each time. The department used Excel, DATEV, and SAP on desktop to process the information.

 

Solution

The automation was built to handle the process by exporting the accounts’ statements from DATEV to the SAP system. This not only allowed employees time to focus on more meaningful tasks but also created a faster, more accurate response time to queries.

 

Results

• Implemented in 3 weeks
• ROI in 3 months
• 0% error rate
• 85% reduction in Process time

 

 

Comparing financial reports

 

Challenge

At the end of each quarter employees at a large insurance company had to compare current and historical financial reports. The process entailed printing the documents and manually comparing them line by line, wasting time and energy for hundreds of reports.  This manual process took an average of 20 minutes per document.

 

Solution

A bot was designed and built to compare the reports based on predefined business rules.  The automation extracted the data directly from the PDF’s and validated all fields and numbers before generating a summary report.

 

Results

• Average handling time per report was reduced from 20 minutes to 2 minutes
• 100% accuracy in report comparison

 

New Hire On-Boarding

 

Challenge

An Insurance company’s full manual process for onboarding new hires and entering updates to enterprise resource planning (ERP) required a lot of data to be entered manually to complete the new hire process. The existing workflow was time-consuming, error-prone, and required significant reworking.

 

Solution

Now the automation automatically manages the new hire update process in the ERP. It reads the details from SharePoint, validates multiple fields, and enters them back into different SAP screens.

 

Results

•  Significant productivity gains
• Reduced manual effort
• Decreased error rates

 

Claims management and reconciliation

 

Challenge

 As a leading global reinsurer, a company faced challenges across claims and reconciliation areas. The business processes were high-volume, low-value, error-prone manual checks and high-risk exposure tasks that needed increased accuracy or adaptability to process field values in multiple formats.

 

Solution

A Bot was implemented and performs tasks related to claimant screening, financial reconciliation, competency management, claims, expense clearing, document triage and claims creating and updated.

 

Results

•  40-50% throughput increase
• More than 49 full-time employees saved
• Error elimination
• Substantial reduction of wrongful claims

 

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