Insurance

OCR & Handwriting Recognition for Insurance

OCR & Handwriting Recognition for insurance, built around the constraint that defines the sector: claims decisions need an audit trail and a consistent basis across assessors.

Regulations in scope
3
Systems we integrate
4
Typical first release
6 weeks

What changes when it is insurance

Orqent Labs digitises document archives with confidence reporting on every field, so you know which pages need a human and which do not.

In insurance, claims decisions need an audit trail and a consistent basis across assessors. That single fact reshapes how ocr & handwriting recognition has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is claims document intake and validation, usually integrated against policy administration. We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.

Deployed across regulated and unregulated sectors, with audit trails where the regulator expects them. You own the code, the models where they are open-weight, and the documentation to run it without us.

The sector constraints we design around

Defining constraint
claims decisions need an audit trail and a consistent basis across assessors
Regulations in scope
IRDAI regulations · DPDP Act 2023 · grievance redressal timelines
Systems of record
policy administration · claims management · CRM · actuarial platforms
Where we usually start
claims document intake and validation

OCR & Handwriting Recognition workloads in insurance

  • claims document intake and validation
  • underwriting file assembly
  • fraud triage
  • policy servicing requests
  • renewal outreach

What is included

  • Pre-processing for skew, noise and poor contrast
  • Multi-script recognition including Indian languages
  • Table and layout structure preserved, not flattened
  • Per-field confidence with a human review queue
  • Searchable archive output with the original attached
  • Accuracy measured on a sample you verify yourself

Questions from this sector

Can AI decide claims?

It can decide straightforward low-value claims within defined rules, and should assemble and recommend on everything else with a human deciding. The split is a policy decision you set, not one we make.

How much can claims cycle time improve?

Document intake and validation are usually the bottleneck, and automating them typically removes days. We baseline your current cycle before promising a figure.

Does it handle Indian languages?

Yes, Devanagari, Tamil, Telugu, Kannada, Malayalam, Bengali, Gujarati, Punjabi and Odia among others. Accuracy varies by script and scan quality, and we measure it on your material rather than quoting a brochure figure.

How accurate is handwriting recognition?

Highly variable. Neat, consistent handwriting reads well; mixed or cursive is much harder. We run a sample first and tell you honestly whether it is viable.

Can you process our physical archive?

Yes, working with scanning partners for the physical capture and handling the digitisation and structuring end.

OCR & Handwriting Recognition for insurance, worth a conversation?

Tell us the workload and the regulation it sits under. We will tell you what is realistic.

Or email bd@dtrasglobal.com · call +91 74118 77878