How AI Is Changing Business Valuation and Financial Advisory in India
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A DCF draft that used to take a team three days to build can now be scaffolded in a few hours. Comparable-company searches that meant digging through databases by hand now run faster through AI screening tools. That’s the real change AI has brought to Indian valuation work — not a different kind of report, just a faster path to the first draft.
What hasn’t changed is who’s accountable for the final opinion. Where a valuation falls within the registered-valuer framework — under the Companies Act, 2013 or the Insolvency and Bankruptcy Code, 2016 — it has to be carried out by an appropriately registered valuer, following the applicable statutory and professional requirements. AI can compile the data and flag what looks unusual; it doesn’t hold that registration and doesn’t carry that responsibility. Here’s where AI genuinely helps in business valuation and financial advisory work in India, where it doesn’t, what changed in the regulatory framework through 2026, and what the RBI’s AI governance work means for anyone relying on these reports.
What AI Actually Speeds Up
The clearest gains are in the mechanical parts of valuation. AI-assisted tools can help pull historical financials, flag potential inconsistencies in revenue recognition, and run several DCF scenarios in parallel — work that would otherwise take a meaningful chunk of an analyst’s time. Comparable Company Analysis and precedent-transaction searches, once dependent on manually curated databases, can now run through screening tools that help identify potentially relevant comparables across large datasets faster than manual searching alone.
Some firms are starting to use computer vision to cross-check site photographs against depreciation schedules for asset-heavy valuations — plant, machinery, real estate. (Flag for fact-check: how widespread this actually is among Indian valuers isn’t something I could verify — treat it as an early trend, not standard practice, until confirmed.)
None of this changes the underlying valuation requirements. It changes how fast a valuer reaches a reviewable first draft — which frees up time for the part that actually matters to a bank, an NCLT bench, or a resolution professional: which comparable set genuinely fits, and which growth assumption is realistic for an Indian mid-market company.
Financial Advisory: Due Diligence, M&A and Risk Work
Financial advisory covers more ground than valuation alone — financial due diligence, M&A support, restructuring advisory, and risk assessment all sit under this umbrella, and AI has moved faster here partly because this work isn’t tied to a single statutory sign-off. AI-assisted risk models can help score counterparty risk using more variables than a traditional ratio analysis would cover — payment history, litigation records, filing patterns — useful groundwork for due diligence and transaction advisory.
Anomaly detection is where the difference is most visible. AI-based analytics can screen large transaction datasets for unusual patterns and potential related-party inconsistencies that warrant further investigation — the kind of thing that’s difficult to catch efficiently through sample-based manual review alone. In GST-related compliance and financial review work, this means potential issues surface earlier, while there’s still time to investigate them properly.
What Changed in Indian Valuation Rules Through 2026
This matters more in 2026 than it did a year ago, because IBBI substantially updated the valuation framework for insolvency cases this year. On 1 April 2026, IBBI issued Circular IBBI/RV/93/2026, notifying the International Valuation Standards (IVS) — as issued by the International Valuation Standards Council — as the applicable standard for every valuation conducted under the IBC, across CIRP, liquidation, voluntary liquidation, pre-packaged insolvency, and personal guarantor bankruptcy proceedings.
Weeks before that, on 25 February 2026, IBBI’s CIRP Amendment Regulations redefined ‘Fair Value’ to explicitly include the underlying synergies of a corporate debtor — moving valuation for resolution purposes away from a purely asset-by-asset view — and introduced a Coordinating Valuer to bring asset-class-specific valuations together into an overall enterprise figure. IBBI followed this on 15 June 2026 with a further circular on report standardisation and documentation requirements for valuations conducted under the IBC, reinforcing the Valuation Report Identification Number (VRIN) system that stakeholders use to verify a report’s authenticity.
None of this is AI-specific — it’s a broader push toward standardisation and stronger documentation in IBC valuation work. But it’s directly relevant here: if a firm uses AI to accelerate data compilation and anomaly-flagging, that AI-assisted layer still has to feed into a report that meets these documentation and format requirements. Treating AI output as a shortcut around that documentation, rather than an input into it, is where firms are most likely to run into trouble. (Some secondary sources describe additional specifics of the June 2026 circular — a fixed list of mandatory report items and a defined fair-value formula — that I could not confirm directly from IBBI’s own published text. Verify the exact requirements against the circular itself before citing specifics.)
RBI’s FREE-AI Framework: What It Actually Means
On 13 August 2025, the RBI released the report of its Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) Committee, chaired by Professor Pushpak Bhattacharyya of IIT Bombay. It lays out seven guiding principles — Trust, People First, Innovation, Fairness, Accountability, Explainability, and Resilience — across six pillars, with 26 recommendations for regulated entities. The committee’s own report projects AI could lift banking sector efficiency by up to 46%. (Worth treating that figure as the committee’s projection, not an independently tested outcome.)
This is a committee report, not a binding regulation. As of mid-2026, the RBI has said it’s still assessing the recommendations and expects to convert relevant parts into supervisory instruments — Master Directions and circulars — over time. That doesn’t mean banks and NBFCs have no AI-related obligations in the meantime: they remain subject to RBI’s existing rules on technology risk, data governance, and outsourcing, independent of whatever comes out of FREE-AI specifically. It doesn’t regulate IBBI-registered valuers at all.
Even so, FREE-AI’s emphasis on explainability, human oversight, and documented accountability is a reasonable governance benchmark for any firm using AI in financial work — valuation included — regardless of whether a specific rule requires it yet.
IBBI has been paying attention to this on its own side too. Its Registered Valuers’ Conclave in February 2025 included a session specifically on the use of AI and analytics in valuation — one of several sessions on the evolving regulatory and technological landscape for the profession, not an endorsement of AI as a standard methodology. ICMAI RVO now runs a certificate course on AI and analytics in business valuation for registered valuers — into its 23rd batch as of August 2026 — a practical sign of where the profession expects this to go.
Where AI Still Can’t Do the Job
AI models are only as good as the data behind them, and a lot of Indian mid-market companies have thin, inconsistent financial histories — exactly the gap a valuer’s judgment is supposed to fill. An unusual related-party loan might be a legitimate commercial arrangement or a genuine red flag; the model can flag it, but deciding which one it is still takes someone who understands the business.
More fundamentally, AI isn’t a regulated professional. It doesn’t hold a valuer’s registration, and it doesn’t carry the professional responsibility that attaches to a valuation opinion or a statutory report — that stays with the appropriately qualified person who issues it. Which “appropriately qualified person” means depends on the assignment: a Companies Act valuation, an IBC valuation, and a FEMA pricing valuation each sit under different rules and, in some cases, different categories of professional. AI doesn’t change any of that; it just changes how fast the underlying work gets done.
| Task | AI’s Role | Professional Responsibility |
| Data gathering | Pulls financials, flags anomalies | Validates the source data |
| Comparable search | Screens datasets for candidates | Determines what’s genuinely comparable |
| DCF / scenario modelling | Runs multiple scenarios | Selects and defends the assumptions |
| Final valuation opinion | No independent legal standing | Rests with the registered valuer under the applicable statutory framework |
A Practical Example
The following is based on an anonymised Sapient Services engagement; details are generalised to protect client confidentiality.
A manufacturing company in the Delhi NCR region came to Sapient Services for a financial due diligence report ahead of a bank-led debt restructuring — a two-week deadline, five years of financials across two subsidiaries, and inconsistent categorisation of related-party transactions.
AI-assisted document review helped flag related-party entries and cash-flow anomalies across the data set early in the engagement, well ahead of what manual sampling alone would typically allow within the same timeframe. That left more of the timeline for the actual valuation work — checking each flagged item’s rationale with management and building a narrative the bank’s credit committee could evaluate. The report was submitted on schedule, and the related-party section — the part AI review had surfaced first — did not generate additional queries during the bank’s review.
Where Firms Get This Wrong
The most common mistake is treating AI output as a finished valuation rather than an analytical starting point. An AI-generated number is not, by itself, a valuation opinion or a statutory valuation report — it still needs professional review before it means anything to a bank, a court, or a regulator. The second is feeding these tools unverified or confidential client data without controls; a confident-sounding wrong answer is worse than no answer, because it doesn’t look wrong. The third is assuming a generic AI system reliably applies India-specific rules — Ind AS treatment, FEMA pricing, IBBI’s evolving documentation requirements — without expert review. It generally doesn’t.
The fix isn’t complicated: use AI for the first pass, keep a documented record of what a human reviewed and why, and match the assignment’s professional and documentation requirements to its actual statutory purpose — a FEMA pricing valuation, a Companies Act valuation, and an IBC valuation aren’t the same exercise.
A Few Questions Worth Answering Directly
Can AI replace a business valuer in India?
No. Where a valuation falls within the registered-valuer framework under the Companies Act, 2013 or the IBC, it has to be carried out by an appropriately registered valuer. AI can assist with the data and modelling; it doesn’t hold that registration or the professional responsibility that comes with it.
Is the RBI’s FREE-AI framework binding on valuation firms?
No — it’s a committee report, not a regulation, and it doesn’t target valuers specifically. Even the banks and NBFCs it was written for aren’t yet bound by it as such, though they remain subject to RBI’s existing technology and data-governance rules regardless.
What changed in Indian valuation rules in 2026?
For IBC valuations specifically, IBBI mandated International Valuation Standards from 1 April 2026, redefined Fair Value to include business synergies, introduced a Coordinating Valuer role, and issued a further circular in June 2026 on report standardisation and documentation.
Does AI make valuation reports cheaper?
It can cut the time spent compiling data, which may shorten turnaround. It doesn’t reduce the professional review and documentation work a registered valuer still has to do — if anything, IBBI’s 2026 documentation requirements make that review more involved, not less.
Will a bank accept a valuation report that used AI assistance?
AI involvement isn’t the deciding factor either way. Acceptance depends on the lender’s own requirements, the valuation’s purpose, the methodology and evidence behind it, and the credentials of the professional who signed it.
What’s Actually Worth Doing Next
If your firm hasn’t started using AI in valuation or due diligence work yet, the sensible starting point isn’t a platform overhaul — it’s picking one repetitive task (comparable screening, or flagging related-party anomalies in due diligence) and testing an AI tool against it, with a human checking every output before it goes near a client or a report. That’s a small enough change to measure honestly, and it tells you fast whether the tool is actually saving time or just moving the work around.
If you need a valuation or financial due diligence report from a firm that keeps pace with both the technology and the 2026 regulatory changes, contact Sapient Services at +91 9540162888 or visit sapientservices.com.
