What is DRILLER?
DRILLER is a cutting-edge analytics platform aimed at transforming the digitization and comprehensive analysis of insurance portfolios by effectively managing both structured and unstructured data. This solution significantly improves the understanding of the portfolio's resilience and the nature of claims. By utilizing its advanced features, it accelerates reserve releases, leading to reduced requirements for solvency capital and minimized capital costs. The innovative tool leverages artificial intelligence to perform in-depth evaluations of portfolios and claims, while also predicting potential adverse developments in claims through a sophisticated severity scoring mechanism. Furthermore, it enables the prompt identification of claims that may be either under-reserved or over-reserved. Users gain access to fully searchable documentation and claims, coupled with valuable insights into the structure of the portfolio. The tool excels in recognizing various elements such as characters, numbers, and sentiment while efficiently categorizing documents and identifying specific characteristics of claims. It also simplifies the process of reviewing and prioritizing critical claims that require urgent attention, all supported by automated analysis across the entire portfolio, thereby enhancing both operational efficiency and informed decision-making. In addition, the platform continually evolves to incorporate user feedback, ensuring it remains relevant and effective in meeting the dynamic needs of the insurance industry.
Integrations
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Company Facts
Company Name:
DGTAL
Company Location:
Germany
Company Website:
dgtal.io/products/
Product Details
Deployment
SaaS
Training Options
Documentation Hub
On-Site Training
Video Library
Support
Standard Support
Web-Based Support
Product Details
Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English