Automated Insurance Case Processing

An insurance case can move through a website while still depending on people for assessment and approval. Azki’s published motor-claim journey is an instructive example: customers identify the insurance type and parties, submit policy and accident information, and provide further details. An expert then contacts the customer for vehicle assessment. The described payment stage follows the expert’s calculation and the injured party’s approval. This documents a digitally coordinated service with explicit human involvement. s1

For readers encountering claims about automation, the central question is therefore which task the software performs. Collecting information, extracting it from documents, checking it against policy conditions, and authorizing a payment are distinct activities. Their separation is visible when Azki’s expert-led description is read alongside Kavan’s advertised document-processing functions. s1s2

Kavan, an Iranian insurance technology vendor, describes optical character recognition, or OCR, for reading documents and images. Its published functions include identifying services, applying contractual coverage and tariff rules, calculating claims, flagging suspicious patterns, and passing approved results to a finance unit. It also advertises operational dashboards for following case status. These are vendor descriptions of capabilities; inspected material did not establish their performance in a named insurer’s production environment. s2

The following diagram summarizes that advertised sequence. It should be read as a functional map of one vendor’s description, rather than a universal Iranian insurance procedure. In particular, a handoff to finance does not itself demonstrate that payment has been executed or received. s2

Kavan’s advertised document-processing sequence

The arrows describe advertised information processing and referral functions. They do not establish automatic approval, successful payment, or deployment across the Iranian insurance industry.

Iran’s Electronic Commerce Act provides historical legal context for electronic records: the text hosted by WIPO recognizes electronic evidence and connects its evidential weight to security methods. Its personal-data provisions also address consent, specified purposes, and the accuracy of stored information. These provisions explain why document integrity and personal information belong in an account of insurance automation. They do not establish the current legal requirements for a particular claims engine. s3

A defensible assessment of automation would need deployment evidence, error measurements, and a clear account of who reviews disputed results. Those materials were not verified here. The supported conclusion is narrower: publicly described Iranian workflows combine digital intake, specialist assessment, and advertised rules-based processing in different ways. s1s2