AUDIT REPORT
Streamline the review of post-issue audits
Save time and resources by streamlining the review of post-issue audits with AI. Our platform provides auditors with an extraction of key APS findings in a succinct report so your team can quickly filter and identify the cases with potential misrepresentations.
3 Biggest Advantages
DigitalOwl’s Digital Audit Report (DAR) streamlines the review of post-issue audits by providing auditors with an extract of key APS findings so the underwriter/auditor can quickly filter to find cases with potential misrepresentation
For the potential misrepresentation cases, DigitalOwl’s Digital Underwriting Abstract (DUA) helps the underwriter/auditor quickly find detailed (360 degree) information for impairments/tobacco/BMI requiring further review
Resulting in significant time savings, allowing your underwriting team to:
-
Work on new business applications
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Complete more PIAs to better monitor mortality slippage
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Work on R&D
WHAT WILL YOUR UNDERWRITING TEAM DO WITH THE TIME SAVED?
Our DAR helps speed up the Post Issue Audit process by automating the APS review and highlighting the most common misrepresentations:
Tobacco Use
Significant Medical Conditions such as Diabetes or Cancer
BMI
A Better Way to PIA
Better manage mortality at a lower cost
Is your company completing Post-Issue Audits (PIAs)? Or, perhaps you need to be doing them but don’t have enough staff?
DigitalOwl has a better way to PIA!
Accelerated Underwriting and Simplified Issue products allow carriers to fulfill customer’s need for insurance more quickly, but new underwriting solutions require monitoring for higher than expected mortality slippage. PIAs provide valuable data to your Underwriting and Actuarial team, but at a high cost. Many carriers recognize they need to implement a program - or increase the number of audits - but simply can’t hire enough staff to meet the need.
DigitalOwl’s Digital Audit Report (DAR) extracts the key data your Underwriting/Audit team needs to review APS data quickly by highlighting only those needing closer review. This allows the underwriter to spend more of their time reviewing those with potential misrepresentation rather than spending hours reading APSs on healthy applicants.
Cost Example (Estimate Time)
Underwriting Auditor reviews the DigitialOwl DAR with 100 PIAs. Using the DigitalOwl’s DAR, the auditor can quickly determine APSs which are clean versus those with potential misrepresentation. Of the 100 cases, if 70 are clean, this means the underwriter then only needs to complete a deep review on 30 APSs. DigitalOwl’s DUA helps the Underwriter/Auditor to quickly locate the required information.
CURRENT PROCESS WITHOUT AUDIT REPORT
Task | Time Per APS | Total Time |
|---|---|---|
Manually reviewing 100 APSs | 30 minutes | 50 hours |
30 cases which need
further review | 20 minutes | 10 hours |
Total hours spent for a post-issue audit = 60 hours
USING DIGITALOWL'S AUDIT REPORT
DigitalOwl produces the DAR on the 100 cases
Task | Time Per APS | Total Time |
|---|---|---|
Reviewing 100 APSs automatically with Audit Report | 7-8 minutes* | 12 hours |
30 cases which need
further review | 10 minutes | 5 hours |
Total hours spent for a post-issue audit = 31 hours
*less time per APS is needed because the DUA is used
Total time saved = 17 hours
Time reduction of 72%
Valuable time savings that can be deployed to new applications or to increase the number of PIAs completed. Although there are variations in this example, it is clear the impact – and time saved – with post-issue audits and the underwriter’s time.
Here’s How We Do It
Our artificial intelligence (AI) technology has been taught to understand the instances of each medical term and our natural language processing (NLP) combines this technology with context. The goal is to increase efficiencies in a PIA by providing underwriters with the needed information at their fingertips and at the same time, build a more accurate infrastructure for insurance carriers to correctly insure their customers.
Case # | Tobacco Last Entry | Tobacco Type | BMI | Significant Impairments | Vascular Disease | Cardiovascular Disease | Endocrine | Cancer | Substance Abuse Treatment |
|---|---|---|---|---|---|---|---|---|---|
1 | 1/21 | Current: Cigarettes | 36 | 2 | Type 2 diabetes | Melanoma | |||
2 | 3/20 | Never Smoked | 27 | 0 | |||||
3 | 5/22 | Current: Vaping | 23 | 0 | |||||
4 | 2/21 | Former Smoker | 22 | 0 | |||||
5 | 3/22 | Never Smoked | 40 | 3 | Peripheral vascular disease | Ischemia, Hypertrophy | Type 1 diabetes |