Jul 22, 2024
Natural Language Processing (NLP)
NLP techniques can interpret unstructured text in loss run reports, such as notes and descriptions. It can help extract meaningful information, standardize terminology, and improve the consistency of data interpretation.
Machine Learning and AI
Machine learning algorithms can be trained to recognize patterns and anomalies in loss run data, automate the identification of key data points, and enhance the accuracy of data extraction and analysis.
Artificial Intelligence (AI)-Driven Insights
AI tools provide predictive insights and advanced analytics based on historical loss run data. These insights can aid in decision-making for underwriting, pricing, and risk management.
Magic Submission
Magic Submission is a purpose-built hyper-automation product designed to automate the end to-end ingestion and routing of submissions. Leveraging advanced technologies such as Generative AI (GenAI), Large Language Models (LLMs), Computer Vision (CV), Machine Learning (ML), and Data Science (DS), Magic Submission ensures seamless and efficient processing. This plug-and-play ingestion system requires minimal integration effort, enabling record breaking implementation times from initiation to production within just a few weeks.
Loss Runs
Magic Submission has introduced groundbreaking advancements in Loss Runs processing, effectively addressing the challenges of claims extraction. The platform seamlessly balances accuracy and speed, ensuring both can be achieved simultaneously. Capable of handling loss run reports from over 6,000 insurance carriers, each with its unique template, Magic Submission utilizes proprietary ML algorithms, Large Language Models (LLMs) to ingest any loss run template, regardless of its shape or format. The system can extract more than 180+ normalized entities in their raw format, tailored to be either line of business (LoB) agnostic or LoB specific based on customer requirements. This robust capability is further enhanced by comprehensive loss analysis, providing an end-to-end overview of the losses incurred by the insured.
Benefits of Automating Loss Run Reports Processing with Magic Submission:
Automating the ingestion and processing of loss runs through Magic Submission can offer several benefits:
1. Raw Extraction: Magic Submission offers raw extraction from given loss run reports.
2. Data Standardization: Ensures consistent formatting and terminology across loss runs as required, which could be LOB agnostic or LOB specific, depending on the client’s needs.
3. Pattern Identification: Can help to uncover hidden relationships and trends within the intricate and layered historical data of loss runs, providing deeper insights for better decision-making.
4. Improved Data Accuracy: Improved system accuracy of 95%+ with low touch and reduced errors associated with manual data entry.
5. Handling Variations: The loss run tool can manage the various formats and representations used in loss runs by 6000+ carriers and brokers.
6. Contextual Interpretation: Automation can interpret data contextually, like a human, producing more accurate data than even human interpretation.
7. Capability to Read Handwritten Information: Advanced automation tools can interpret handwritten notes.
8. Limited or No Need for Retraining: Magic Submission adapts to different loss run formats without requiring constant updates to the models
9. Faster Turnaround: Speeds up the processing of loss runs, leading to quicker quote generation.
10. Volume: No restrictions on the volume of data.
11. Security and Safety: Offers industrial-grade security and data privacy ensuring client data is not used by LLM for training purposes.
The complexity and variability of loss runs present significant challenges for manual processing. However, Magic Submission’s Loss Run capability offers solutions to standardize data, improve accuracy, and speed up processing times. By leveraging advanced technologies, the insurance industry can overcome these challenges and realize substantial benefits in efficiency and accuracy in the ingestion process thereby enhancing risk selection and improving the overall book of business.
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