The Harsh reality

Current claims automation strategies are ineffective

INPUT

Existing Claims Data

Ingested over voice, fax, or static web form, current claims data is unstructured, nonstandardized, and imprecise.

ERROR

Automation Failure

The existing approach of feeding AI the same data humans use to process claims leads to failure.

machine learning 101:

Garbage In, Garbage Out

Machine learning is only as good as the data you give it.

Even bleeding edge AI struggles with unstructured data.

Currently, claims data is highly unstructured.

The assured Solution:

Better Data From the Start

Assured's FNOL ingestion platform gathers structured data directly from the claimant, enabling AI to succeed downstream.

Structured

No more big unstructured text fields—only intelligently chosen multiple choice questions, and carefully constructed libraries.

Broad

A combination of intelligent questions and artificial intelligence gathers more data than a phone specialist ever could.

Precise

By controlling how, when, and in what form the data is ingested, Assured creates an audited information space that empowers adjusters and AIs to better detect fraud.

Data Enrichment

Often, the data directly supplied by the claimant isn’t enough to correctly and reliably adjudicate a claim. This requires the adjuster to search for and consolidate many different data sources in a time consuming and imprecise process.

Assured solves this problem, and then takes it one step further.

By integrating more than 50 external data sources, and then intelligently surfacing the most pressing data points to the adjuster, Assured enables better informed and more consistent decisions to be made in record time.