Document Verification in the Claims Settlement Process

The insurance industry is steadily entering a new phase of automation. This shift is not driven by following a “trend”, but by a very real operational challenge: manual document handling.

Every day, insurers receive thousands of files — scans, photos, online forms, emails, PDF attachments, and statements. Each of these documents must be reviewed, classified, verified, and manually entered into internal systems. Wherever manual work dominates, errors inevitably follow — and errors translate directly into cost.

Most documents processed by claims teams remain unstructured and highly heterogeneous.

At the same time, global data from reports by Conning and AllAboutAI clearly indicates the direction of change for the insurance industry:

• 84% of insurance companies are already using or actively implementing AI solutions

• Generative AI adoption in insurance has grown by ~100% year over year

• Organizations using AI in claims processing reduce handling time by an average of 59%

These figures show that document verification automation is no longer an “add-on”. It is a foundational capability that directly impacts processing speed, operational costs, and customer satisfaction.

Why do insurance document processes require automation?

Although insurers differ in scale and operational architecture, they face very similar challenges:

1. Fragmented digitization

Some elements of the process are digitized, but a significant volume of documents — especially photos, attachments, and correspondence — still arrive in formats that require manual processing.

2. Document diversity and inconsistency

Statements, photos, policies, invoices, powers of attorney, medical documentation — each document differs in structure, quality, and format.

3. Lack of a unified information flow

Documents circulate between systems, inboxes, portals, and external partners. Such complexity demands automated classification and validation to remain efficient.

4. Fluctuating claim volumes

Seasonality, weather events, and sales campaigns cause sudden spikes in document volume. Scaling teams manually is costly and inflexible.

5. Risk of errors and delays

Manual data entry is one of the most common sources of mistakes, SLA breaches, and compliance issues.

Why focus on medical claims processing?

Automation can be applied across many areas: BLS claims, correspondence without claim numbers, subrogation, e-delivery, policy notes, or partner inquiries.

However, medical claims processing stands out as a process that is:

• highly document-intensive,

• heavily regulated,

• costly to handle,

• critical for NPS and timeliness.

This makes it an ideal example of how IDP (such as SensID) can:

• handle multiple document types,

• extract data from unstructured sources,

• automatically classify and validate information,

• significantly reduce the operational workload.

Medical claims automation — step by step

From the insurer’s perspective, the goal is a fast assessment of claim validity during FNOL (First Notice of Loss) and confirmation of documentation completeness.

This is the stage where IDP delivers the highest value — reducing average assessment time, lowering error rates, and allowing claims handlers to focus on decisions rather than data entry.

What are the steps in this process?

Claimant identification

The system first verifies the person submitting the claim by checking:

• personal data,

• whether the person is the insured, injured party, or an authorized representative,

• entitlement to submit the claim.

Policy identification

Next, the claimant’s data is linked to the insurance policy to verify coverage. The system checks:

• policy number and status,

• coverage scope and period,

• potential exclusions.

Event information verification

Once policy and claimant details are confirmed, the system supports verification of event-related information:

• basic claim details,

• policy compliance,

• preliminary evidence analysis.

Medical documentation analysis

To support accurate decision-making, information can be automatically extracted from documents such as:

• medical history,

• discharge summaries,

• photos of test results,

• medical certificates (injury, incapacity for work, permanent impairment),

• documents confirming circumstances of the event.

SensID platform capabilities

The above workflow can be fully automated using SensID platform functionalities.

SensID delivers three key capabilities that significantly accelerate claims settlement processes:

Document classification

Each document is automatically assigned to the appropriate category (e.g. discharge summary, consent, invoice, power of attorney).

This allows the system to know exactly which fields should be extracted — critical both for accurate analysis and fast access to information during the early stages of the process.

Data extraction and validation

Each stage of claims settlement requires precisely defined data sets. SensID can be tailored to specific process requirements through a client-specific model configuration approach.

Extraction and validation modules enable accurate data capture from classified documents and cross-verification with other data sources, ensuring fast validation and correct claim assignment.

Built-in contextual chat

SensID allows users to query document content using a contextual chat, for example:

• “Who signed the medical certificate?”

• “Does the document confirm the period of incapacity for work?”

• “Are any liability exclusions mentioned?”

This significantly shortens analysis time, especially when dealing with extensive medical documentation.

Summary

Medical claims processing is one of the areas where automation delivers the fastest and most measurable ROI. With IDP:

• documents are automatically classified and analyzed,

• data is extracted and validated with high precision,

• errors and delays are reduced,

• FNOL processing can be accelerated multiple times over,

• operational teams can focus on substantive analysis rather than manual work.

This is the first and critical step toward building a scalable, modern claims settlement process — driven by data, not repetitive tasks.

Learn more about the capabilities of SensID.