Human review of medical records is slow and not accurate enough, and Essential information is often missed – says Yuval Man, the CEO Of Digital Owl. Man explains that
Computers don’t get bored or tired, and they extract more meaningful medical information in a significantly shorter time.
DigitalOwl (formerly known as Legal Automation) developed an AI system for underwriters and claim analysts, primarily working with products such as Life, Disability, Workers’ Compensation, Accident, and Voluntary/Supplemental products.
DigitalOwl’s system reads, understands, and analyzes medical documents automatically and quickly. Using a state-of-the-art NLP engine, the system extracts the relevant medical information that is necessary for assessing risk or managing a claim. A deep understanding of the medical text creates a detailed and complete set of medical data points in a robust, summarized format for the underwriter or claim analyst, allowing them to focus their valuable time on making better decisions, faster.
* What does it mean to analyze a medical document?
Man: In the process of underwriting and claim adjudication, insurance companies frequently review the applicant’ s/insured’s medical records. It’s a labor-intensive and error-prone process.
The medical information helps insurance companies determine what level of risk applicants represent to the company to select and price insureds appropriately and to understand better the medical condition(s) that are causing someone to claim benefits.
* What benefits can an insurance company get from your product?
Man: DigitalOwl uses advanced AI and Natural Language Processing to understand the unstructured medical text. The system’s technology is ideally suited to reviewing high-volume, complex medical records.
Human review of medical records is slow and not accurate enough. Essential information is often missed. Computers don’t get bored or tired, and they extract more meaningful medical information in a significantly shorter time (3 minutes instead of 2-4 hours).
The high level of accuracy leads to more precise risk selection and claim management and thus better risk results, all while reducing costs and improving productivity, cycle times, and consistency.
* What companies are you currently working within Israel and abroad?
Man: We are currently working with Menora Mivtahim and the Phoenix insurance company in Israel, and conducting several pilots in the US.
* What investments were made in the company?
Man: We raised so far $2M, lead by Menora Mivtahim, Professor Amnon Shashua (Mobileye), and Fusion LA.
* Tell me about yourself and about other key figures in the company.
Man: The company was founded in 2018 by Yuval and Amit man (two brothers).
Yuval (CEO) is an Israeli lawyer that used to work as a Personal injury prosecutor, and Amit (CTO) is an experienced computer scientist.
The company participated in the first cohort of the Israeli security agency and Tel Aviv University accelerator “The Xcelerator”, and participated in the Fusion LA accelerator.