Guide · for general insurance corporate brokers
AI tools for insurance brokers in India: a practical 2026 guide
By BimaAI team · Updated
The five jobs AI can take off a broker's desk
| Workflow | What the AI does | What to check |
|---|---|---|
| Drafting the RFQ | Extract insured details, sums insured, covers and clauses from a slip or expiring policy into the broker's RFQ template. | Works on scanned PDFs; outputs your own template; marks every field it changed. |
| Comparing quotations | Read each insurer's quotation against the RFQ and show, line by line, what was honoured, modified or declined. | Normalises Indian number formats; flags look-alike figures; does not rank insurers. |
| Checking the issued policy | Compare the issued policy or bond with the agreed quotation and list discrepancies to raise with the insurer. | Page-level evidence for each finding; drafts the endorsement request. |
| Explaining the policy | Translate a long wording into plain English and check it against the client's actual exposures. | Separates what the wording says from the tool's assessment; cites clauses. |
| Researching the insured | Build a short brief on the company being underwritten — operations, sites, risk signals. | Lists its sources; links findings to clauses the broker might add. |
What can AI do for an insurance broker today?
For corporate and commercial brokers, the strongest use of AI is reading and comparing documents — the slow, error-prone middle of every RFQ. Drafting the RFQ, comparing five insurer quotations and checking the issued policy against what was agreed each take hours by hand and are where most E&O exposure sits.
AI is weaker — and riskier — where it is asked to produce numbers or make the recommendation. Good broker tools keep premium and coverage maths in ordinary, deterministic code and leave the commercial decision to the broker.
Why India needs broker tools built for India
Indian RFQs bring their own formats: sums insured in lakhs and crores, the IIB tariff for fire and IAR rating, insurer wordings that differ from the market standard, and RFQ templates that each broking house maintains in Excel. A tool trained on US small-commercial workflows will miss most of this.
Ask any vendor to run a real Indian RFQ and two or three quotations through the product before you commit — and check whether ₹50 Mn, Rs. 500 lakhs and INR 5,00,00,000 come out as the same figure.
How to evaluate an AI tool for broking
Evidence: every finding should link to the page, clause or cell it came from, so you can verify it in one click.
Numbers: premiums, sums insured and limits should never be generated by a language model.
Neutrality: comparison tools should describe how quotations respond to the RFQ, not rank insurers.
Control: you should be able to edit any field and override any finding, with a note, before anything reaches a client or insurer.
Data handling: ask where documents are stored, who can access them, whether they are used to train models, and how shared reports expire.
Where BimaAI fits
Disclosure: this guide is written by the team that builds BimaAI. BimaAI is an AI workspace for general insurance corporate brokers in India covering all five jobs above across property, engineering, marine, liability and specialty lines. It drafts RFQs on your template, produces a Quotation Comparison Report, audits issued policies with endorsement-request drafts, explains wordings against client exposures and researches the insured — every output linked to its source.
You can try it with a 3-day preview on sample data: join the waitlist with your email and the link arrives within a minute.