Challenge: Recovery from third–party insurers
An insurance company’s claims department faced a frustrating manual process for recovering reimbursements from third–party insurers. The process was expensive and had weak control mechanisms.Solution:The Robot undertook reconciliations between the disparate systems. It generated chase letters as per defined dunning process and sent automatic emails to defrauders. The bot also performed cash applications in the case of received payments, then followed up by deploying a predefined report of the outstanding matters on a weekly basis.
- Faster recoveries
- Increased cash flow
- Low expense ratio
- Reduced cycle time
Challenge: Vendor payments by property insurer
- Improved service levels by converting to a 24 x 7 operation
- 50% reduction in operational costs
- 70% increase in productivity
- Reduced customer complaints
Challenge: Credit limit request underwriting
- Processing time dropped from 4–8 minutes to 2–11 minutes
- 40–50% reduction in cycle time
- 900 cases automated daily
- 440 hours per month saved
Challenge: Importing and Exporting from statements of account
The 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.
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.
- Implemented in 3 weeks
- ROI in 3 months
- 0% error rate
- 85% reduction in Process time
Challenge: Comparing financial reports
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 20minutes per document.
The Robot 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.
- Average handling time per report was reduced from 20 minutes to 2 minutes
- 100% accuracy in report comparison
Challenge: New Hire On Boarding
An Insurance company’s full manual process for on boarding new hires and entering updates to enterprise resource planning (ERP) required a lot of data to be entered to complete the new hire process. The existing workflow was time–consuming, error–prone, and required significant reworking.Solution:The automation automatically managed the new hire update in the ERP and read the details from Sharepoint, validated multiple fields and entered them back into different SAP screens.
- Significant productivity gains
- Reduced manual effort
- Decreased error rates
Challenge: Claims management and reconciliation
As a leading global reinsurer, the 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.
The Bots were implemented and performing tasks related to claimant screening, financial reconciliation, competency management, claims, expense clearing, document triage and claims creating and updated.
- 40–50% through put increase
- More than 49 full–time employees saved
- Error elimination
- Substantial reduction of wrongful claims