iPipeline

Access to all your life insurance new business and underwriting data, in near-real time. Resonant® is an automated solution for the entire NB and UW process with a focus on improving the agent and customer experience, quicker entry into new markets and products, improvement in cycle times and placement ratios and in turn driving profitable growth. Now, Snowflake customers can access their Resonant® data directly in their Snowflake account.

Samples/Tables Included: Life Policy Details Requirements Details Activity Details Fields Included: ­- Cycle Time ­- Case Setup ­- Decision ­- Issue ­- Underwriting Status ­- Final Action ­- Cycle Stage ­- Issued ­- Pending ­- Completed ­- Application Completion Date ­- Policy Status ­- Product LOB ­- Product Group ­- Product Group Description ­- Product ­- Underwriter ­- Case Manager ­- Agent ­- Issue Age ­- Net Income Amount ­- Occupation ­- Face Amount ­- Total Risk Amount ­- Jurisdiction ­- Application Completion Method ­- Carrier Input Date ­- Home Office Receipt Date ­- Signed Date ­- Submission Date ­- Create Date ­- Underwriting Opened Date ­- Underwriting Decision Date ­- Submit For Issue Date ­- Underwriting Type ­- Created Date ­- Requested Date ­- Received Date ­- Fulfilled Date ­- Requirement Time ­- Evidence Time ­- Requirement Review Time ­- Reviewer ­- Requirement Code ­- Requirement Name ­- Requirement Category ­- Cycle Time Stage ­- Vendor ­- Activity Description ­- Activity Type ­- Activity Time ­- Completion Date ­- Create Date ­- Due Date ­- Assigned Participant ­- Agent Type ­- Activity Count Example Use Cases: How do cycle times and placement ratios compare between accelerated and traditional underwritten cases. e. ingest into your own applications, ie: Agent Portals) Pinpoint which segment of the underwriting process are impacting the cycle times Identify requirements that have the biggest impact cycle times, for example APS ordering and the actual impact on cycle times.

Create analytics to serve your field offices, agents, case managers and underwriters in near-real time, combine data with your other datasets.