Syndication and advisory

Before a mandate goes to market, see which lenders are demonstrably present in a sector, rating band or ticket size, from published rating annexures.

Guide Last reviewed 5 min read

On this page — 8 sections

For arrangers, transaction desks and debt advisers. A lender-indexed read of India’s rated credit, used before a book is built rather than after.

All figures as at 30 August 2026.


How do you find a company’s existing lenders before a mandate?

Rating press releases often carry a lender-wise annexure naming each lender on a borrower’s rated facilities. TatvaRatings parses those annexures across seven SEBI-registered agencies and indexes them by lender, so a loan syndication desk can read a borrower’s published lender set — dated, sourced, at sanctioned amounts — before the first call. Figures are floors, as at 30 August 2026.


The problem with a lender list built from memory

Every desk carries a working map of who lends where — assembled from relationships, from deals that closed, and from the last time somebody asked. It is real knowledge and it is also unevenly distributed, undated, and impossible to hand to a junior.

Meanwhile the rating agencies publish, with a minority of rating actions — 46.2% of them, measured as at 30 August 2026 — an annexure naming the lenders on each rated facility. That is a dated, sourced, borrower-consented record of which bank was named on which facility, at what sanctioned amount. It has been public the whole time. It is simply printed one borrower at a time, inside a PDF, across seven agencies.

TatvaRatings parses those annexures into rows and indexes them by lender.

179,857
Lender-exposure rows
1,501
Distinct lenders named
70,337
Rating actions
194,471
Rated facilities

Measured counts as at 30 August 2026. Floors, not totals — a lender absent from a result may simply never have been named in a published annexure.


What an arranger can read from it

Who else already lends to this borrower

Start with the name on the mandate. Read the lenders named on its rated facilities, the facility type each is on, the sanctioned amount as published, and the date of the action that published it. Where a lender appeared in an earlier action and not the latest one, that is a fact worth a question.

Which lenders are demonstrably present in this sector

Take a sector and a rating band. Read which lenders are named on rated facilities inside it, and on what facility types. This is not a view of appetite — appetite is not published. It is a view of where a lender has already been named, which is a different and more checkable thing.

Where a ticket size sits

Sanctioned amounts are published per facility per lender. Read the distribution of published amounts for a sector or a rating band, and a proposed ticket has a public reference set rather than an anecdote behind it.

How a consortium was assembled last time

For a comparable borrower, read the full named lender set on one action and how it changed across successive actions. Consortium shape is one of the few structural facts the annexure gives you directly.

A cross-agency view, in one place

A single borrower’s facilities may be rated by different agencies, and each agency publishes only its own book. All seven — CARE, CRISIL, ICRA, India Ratings, Acuité, Brickwork and Infomerics — are parsed into one schema, with borrower and lender identities resolved across the whole corpus.


An illustrative reading

Query: sector = commercial vehicle logistics; rating band = A− to BBB; lenders named on term loans.

Borrower Rating Lenders named on term facilities Action date
Northline Logistics LtdA−Four named lenders, ₹210 cr aggregate published21 Jan 2026
Meridian Textiles LtdBBB+Three named lenders, ₹85 cr aggregate published12 Mar 2026
Illustrative example — not real data. The borrowers, ratings, lender counts, amounts and dates below are invented. The structure of the output is not.

The output is a starting list of lenders with a documented presence in that shape of credit, each row traceable to the press release it came from.


How to read the output honestly

An arranger who overstates this data in a pitch will be corrected by the room, so the constraints belong in the working method rather than in a footnote.

A named lender is not a live position. Each row is a lender named on a rated facility at a point in time — a sanctioned amount as at the rating action date, not an outstanding balance and not a current position.

Presence is not appetite. The record shows where a lender has been named. It does not show what a credit committee will approve next quarter, and nothing here should be presented as though it does.

The list is a floor. Only 46.2% of rating actions publish a lender-wise annexure at all — 32,498 of 70,337, as at 30 August 2026 — because disclosure depends on the issuer’s consent. And the rated universe is a minority of any lender’s book. A lender absent from a query result may simply never have been named in a published annexure. The true position is larger, by a margin that is not estimated here.

The dates matter more here than anywhere else. A cooperating issuer’s rating is reviewed periodically rather than continuously, broadly once a year, so a typical record is a year or more old. Where an issuer has stopped cooperating and the rating has migrated to the issuer-non-cooperating category, the underlying information is older still. Read the action date alongside every row, and quote it alongside every figure.

Proposed and unallocated limits are flagged distinctly and should not be counted into a lender’s named position.


What it is not

It is market intelligence built from public rating disclosures. It is not exposure monitoring, not a system of record, and not a control for any process requiring a current or complete exposure position. It carries no regulatory status, no agency relationship, and no credit opinion of its own.

For a live syndication, it is the instrument that tells you who to call and what to ask them. The confirmation still comes from the call.


Getting to a first answer

Tell us the sector, rating band or borrower you would start from. We will tell you what the current corpus can and cannot answer for it.

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Tell us the borrower, bank or sector you would start from. We will tell you what the current corpus can and cannot answer for it.

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