Better Data and Prioritization Propels Growth and Profitability

The submission intake process is fraught with incomplete and inaccurate data. Pulling data from multiple inputs in varying formats bogs down the process and without the ability to cleanse and navigate data, underwriters are at a disadvantage. Adopting the TSIQ Submission Solution solves these challenges and provides clear benefits and competitive advantages for insurers.

TSIQ’s Submission Ingestion Solution is transforming underwriting using data science and third-party data to improve the submission process. This solution accurately and automatically captures all information, prioritizes opportunities, automates manual tasks, provides loss runs and account level loss history analytics. This helps streamlines broker communications and improves the underwriters’ ability to focus on the best business opportunities to improve growth and profitability.


TSIQ transforms underwriting from an art form to a data-driven profit driver. We provide better data acquisition earlier in your workflow to ensure better risk selection and more accurate pricing.


Helps underwriters prioritize and triage submissions by presenting a holistic view of the queue, applying appetite checks and exposing relevant factors to enable the underwriter to focus on the “right” kind of business. These high priority factors enable smarter prioritization.

Validates and enriches submission information by applying third-party data and assessing ingestion confidence, driving confidence in the data an underwriter operates on.

Stores all submission information whether it eventually binds or not. All data provided in the application process is valuable and holds the keys to critical insights into your business. This data asset enables producer analysis, risk assessment and a myriad of underwriting decision-making considerations critical to the process.

Improves operational efficiency by automating the submission intake process — ingesting all the information from submission emails, application forms, loss runs and other attachments, including structured and unstructured data. Data science techniques including OCR and NLP are used to convert unstructured data, including handwriting.

Streamlines broker communication by supplementing application information quickly and efficiently increasing brokers’ visibility into the underwriters’ risk appetite.

Reduces time it takes to ingest, analyze and triage submissions from days and weeks to minutes.

Helps underwriters grasp loss run data quickly and thoroughly both within an account and across all businesses.

Gives executives insight into broker performance and pipeline health to better manage the business for productivity and profitability.