What if you could proactively and automatically assist your policy holders to reduce their exposure to loss?
App Orchid for Insurance
Predict outcomes and mitigate losses by integrating ALL relevant structured and unstructured data.
Insurance companies have an overwhelming amount of data that resides in multiple systems across the enterprise. A vast amount of this data is unstructured, residing in Document Management Systems that cannot be accessed without signiﬁcant resources. It is virtually impossible to identify correlations and trends such as causes for loss or cross-selling opportunities for customers that could have a valuable impact on risk mitigation, compliance and revenue growth.
The App Orchid platform helps Insurance companies create AI powered apps that predict outcomes, mitigate risk and reduce losses. The platform combines structured and unstructured data from all relevant enterprise systems and external data such as social media to identify relationships, trends and patterns not possible before. Over time the platform can predict, make recommendations and automate processes to dramatically improve efficiency and mitigate losses.
App Orchid Insurance Solutions in Action
Extract Insights from Unstructured Documents
Extracting entities, subscription % of certain coverages, etc. from structured and unstructured documents, across the enterprises’ entire dataset, just by asking simple language question for various use cases.
Automate Quotations and other processes easily
Utilizing enhanced NLP to automate quotations or other processes such as customer compliance tracking just from information sent and received in a plain text email and attachments.
Improve Accuracy of Actuarial Analysis
Combine unstructured documents like compliance, regulations, corporate filings, market rules, regional mandates with risk analytics for superior risk profiling and evaluation.
Bolster Catastrophe Risk and Damage Analysis
Incorporate historical weather patterns, news, research reports, and social media, into risk calculations for potential catastrophes, price coverage or prudent levels of reinsurance.
Reduce Number and Value of Claims
By unifying structured and unstructured data across historical claims, flag and prioritize potential claims before they occur, allowing companies to proactively warn customers of exposure.
Incorporate Individual Underwriter “Tribal Knowledge” into a Standardized Underwriting Process
Incorporate individual assessor “tribal knowledge” into predicting and assessing risk, creating a uniform assessment metric across the entire underwriting process.