The Leader in digitizing traditional APSs, EMRs, and all other underwriting evidence.
Enhance underwriting efficiency by providing a comprehensive abstract for formal and informal underwriting.
Streamline the process to complete Post Issue APS audits, and enable your team to complete more audits.
Determine which informals are likely to be placed so you can prioritize resources.
Access the data from prior APSs/Full files to build mortality models, analyze reserve levels, or evaluate mortality by impairment.
Empowering Underwriters Everywhere
TRANSFORM THE DATA
Our system quickly analyzes and classifies hundreds or thousands of pages within a medical record and transforms them into a focused dataset for analysis.
OBJECTIVE SUMMARY OF EVERY FILE
Consistency is critical in insurance decisions. DigitalOwl provides a systematic means of making both simple and complicated decisions by providing an unbiased, objective summarization of every medical record, every time.
We know decision time is of the essence. Whether your team is focused on speed-to-premium or turnaround times for claims, DigitalOwl provides you with tools to make faster decisions. Click here to calculate time and cost savings.
INCREASE EFFICIENCY AND SCALABILITY
DigitalOwl significantly reduces the time and expense of manually reviewing medical records, helping to free up your valuable Claim Analysts, Underwriters, and Clinical Experts to focus on more critical business activities.
OUR SYSTEM VS. MANUAL
DigitalOwl analyzed each case in 3-5 minutes.
Doctors analyzed each case in 3-4 hours.
In all cases, DigitalOwl found twice as many significant medical datapoints.
About Our Technology
EMPOWERING INSURANCE CARRIERS TO MAKE DECISIONS FASTER
Using our proprietary, purpose-built Natural Language Processing (NLP) platform that was developed exclusively for medical records, Underwriters and Claim Analysts can review a robust summary instead of hundreds of pages of complex medical information.
HERE’S HOW IT WORKS
By quickly and thoroughly analyzing the medical documents, including data from imaged records, DigitalOwl gets a deep understanding of the record no matter the quantity of pages analyzed. This understanding is then transformed into a focused set of medical data points in a meaningful, summarized format.
To fully analyze medical records, technology must understand the relationship between extracted entities. DigitalOwl’s NLP technology does that.