1. Incomprehensible Volumes

Service providers and insurance payers are burdened by the overwhelming volume of documentation involved in processing pre-authorization and claim requests. 

2. Gaps In Claims Automation

In healthcare, according to McKinsey only 10% of medical record review is automated, leaving most of it to manual review. On the insurer side, each claim takes 40 minutes and costs an average of $15 to process.

3. Difficult to Transfer Knowledge

AI models are getting increasingly more intelligent these days but the insurance claims processing realm is incredibly nuanced and contextualized for AI models to completely take over. As it stands today, the final approval of claims permutations can successfully and accurately be achieved only by the human professionals. 

4. Human-Centred Approach

The gap with existing Claims automation solutions is the lack of empathetic interactions with customers in dire life situations. It is still an on-going challenge for insurance organizations to implement an efficient AI automation with a human-centered approach.

Payout Delays & Customer Dissatisfaction

Manual claims pre-processing and validation is time-consuming, demanding on resources, and ultimately delays payouts and reduces customer satisfaction.

Increased Chance of Fraud

Varying approaches and training across business units may cause errors in claims classification and validation increasing rework, demand on resources and the chance of fraud.

Misfiling & Retrieval Issues

Human errors may cause misplaced or incomplete information, complicating future retrieval, audits, lititgation and customer churn risk.

Scalability & Cost Concerns

Staff shortages, increased turnover and expertise gaps hinder growth and elevate operational costs.     

50%

reduction in claim  settlement time & processing costs

5%

forecasted chance of error in claim assessment

100%

more claims processing capacity without growing the team