Best Bank Statement Analyser in India for Banks and NBFCs: 2026 Comparison

There is no single best bank statement analyser for Indian lenders. Perfios has the widest published format coverage and the deepest India deployment; ScoreMe and Precisa publish specific coverage numbers; FinBox publishes the most detail on fraud checks; YuSight goes furthest past parsing into spreading and a cited memo. The right answer depends on which of those you need.

Key facts

• YuSight reports 95.2% extraction accuracy, validated against a manual benchmark, and — the part that matters more for a credit team — carries the statement through to a spread, a computed ratio set and a fully cited credit memo rather than ending at a categorised transaction list.
• Perfios is the reference point in this market, and any honest comparison should say so. Its India bank statement analyser page claims support for "4000+ Document Formats" from "1000+ banks globally", "5Bn+" transactions processed, "10Cr Statements Processed per Year" and "Trusted by over 1,000 institutions" (Perfios, Bank Statement Analyser — India, retrieved 27 August 2026). No other vendor in this set publishes coverage on that scale.
• The fetch problem is mostly solved; the analysis problem is not. India's Account Aggregator network had fulfilled 538.32 million cumulative consents against 326.30 million linked accounts as at July 2026 (Sahamati, AA Ecosystem Dashboard). Choosing a tool on "can it fetch statements" is choosing on a solved dimension.
• Vendor accuracy claims are not comparable to each other. ScoreMe publishes ">99% Accuracy achieved in just 2 minutes"; FinBox publishes "96% detection accuracy" for fraud checks specifically, alongside an explicit disclaimer that fraud outputs are "probabilistic and indicative in nature". These measure different things on different denominators.
• Nobody in this set publishes list pricing. We checked every vendor's own site. Any comparison article that gives you a price per statement is quoting a number the vendor did not publish.

How we compared these platforms

This is the section most articles in this category omit, so here it is in full.

What we compared. Only capability claims that each vendor publishes on its own website: bank and format coverage, input channels (PDF, netbanking, Account Aggregator), fraud and tamper checks, categorisation, what the output artefact is, and whether the product continues past a transaction summary into financial spreading, ratio computation, bureau reconciliation or a credit memo.

Sources. Each vendor's own product, solutions and homepage. Where a vendor makes the same claim in two places with different numbers, we say so. Where a vendor publishes nothing on a dimension, we write "not published" rather than inferring a capability or a limitation.

Date. All pages retrieved 27 August 2026. Vendor pages change; re-check before a procurement decision.

What we could not verify.

• Pricing. No vendor in this set publishes list pricing. We have not guessed.
• Independent accuracy. No vendor in this set publishes a benchmark methodology, a test corpus description or a third-party audit of its accuracy figure. Every accuracy number below, YuSight's included, is self-reported.
• Coverage counts. "4,000+ formats" and "1,200+ formats" are counted by the vendor, using the vendor's own definition of a format. There is no shared definition and no way to reconcile the counts.
• Whether a claimed feature works on your borrower profile. A tool that handles salaried statements well may handle a proprietorship's mixed CC account badly. Only a pilot on your own files answers that.

Disclosure. YuSight publishes this article and is one of the ten platforms listed. We have written the competitor entries only from what those companies publish about themselves, and the "when to choose each" section recommends other vendors where they fit better.

One factual note on Perfios' published coverage. Perfios' India product page claims support for "4000+ Document Formats" from "1000+ banks globally". A Perfios resources-section blog post states that PDF statements are "tested across 250+ formats covering the top 40+ banks" and that "the algorithm has 90%+ accuracy in counterparty identification" (Perfios blog, Reduce the risk of bad loans, retrieved 27 August 2026). Both pages were live on the same date. The likeliest explanation is that the blog post is older and was not updated, and the gap is a maintenance issue rather than a claim about the product. We note it because it illustrates the general point: coverage figures on vendor sites are marketing artefacts with no shared definition and no audit, and a procurement team should ask for the bank list, not the number.

What should a bank or NBFC actually evaluate?

Coverage counts are the easiest thing to publish and among the least useful things to compare. Nine dimensions that decide whether the tool survives contact with a real credit file:

1. Coverage of *your* borrowers' banks, tested with your own statements — not a headline count.
2. Behaviour on scanned and photographed statements, which is where the accuracy gap between vendors is widest.
3. UPI narration handling. NEFT and RTGS carry structured remitter names; UPI often carries a VPA and little else. Ask for the accuracy split by rail.
4. Related-party and circular-transaction detection, which decides whether the turnover figure in your memo is real.
5. Tamper and fraud checks, and specifically whether the tool tells you why it flagged something.
6. Multi-account and multi-entity consolidation for group borrowers.
7. What comes out. A JSON of categorised transactions, an Excel summary, a scorecard PDF and a credit memo are four very different artefacts with four different amounts of analyst work left after them.
8. Traceability. Can an analyst click a number in the output and land on the source line? This is what an examiner asks for.
9. Deployment shape. API, on-premise, VPC, and where the data sits.

The ten platforms, from what each publishes

Perfios

What it publishes: "4000+ Document Formats" from "1000+ banks globally"; "5Bn+" transactions processed; "10Cr Statements Processed per Year"; "6+ Languages"; a "Built-in Fraud check utility" that flags "PDF and transaction manipulations"; a categorisation engine handling "more than 30 million narrations a day"; netbanking retrieval; multi-account analysis; customisable reports including salary and liability detail. Corporately: "1000+ Financial Institutions Worldwide", "18+ geographies", "2+ Bn Transactions Per Year", "500+ APIs", "1300+ Employees Worldwide". Product lines are grouped as Perfios Analyse, Verify, Protect and Lens.

Where it is strongest: breadth. If your portfolio spans many banks, many statement vintages and multiple countries, no other vendor here publishes comparable coverage. Perfios also has a separate CAM product that includes "Financial Spread", "Ratios", "Cashflow Summary", consumer and commercial bureau reports, GST and ITR-V (Perfios, CAM) — so the depth gap is narrower than a bank-statement-only comparison implies.

Not published: an accuracy percentage or SLA on the India bank statement analyser page; pricing.

ScoreMe Solutions

What it publishes: "1600+ Bank templates supported for over 300 FIs"; ">99% Accuracy achieved in just 2 minutes with near-zero errors"; "300+ Credit assessment checkpoints"; "100 Cr+" transactions analysed; "50% Cost efficiency achieved"; acceptance of "digital PDFs, scanned PDFs, and physical paper statements" (ScoreMe, Bank Statement Analyzer). Its solutions page lists a wider stack than bank statements alone: Bank Statement Analyzer, Financial Statement Analyzer, GSTR Analyzer, Integrated Analysis Solution, ITR & 26AS Analyzer, KYC & Compliance, Legal Data Analyzer and Bureau Data Analyzer (ScoreMe, Our Solutions). The Financial Statement Analyzer page adds "300+ Financial data points extracted", "100+ industries" and "600+ trusted data sources".

Where it is strongest: document breadth beyond bank statements, and explicit support for physical paper statements — a real constraint for branch-led lending.

Not published: the benchmark behind the ">99%" figure; whether the Financial Statement Analyzer computes a standard ratio set; pricing.

FinBox (BankConnect)

What it publishes: "150+ check types" and detection of "more than 15 types of fraud", with "96% detection accuracy"; "Detect 40% more transactions with advanced analytics"; "37% more non-salaried earnings uncovered"; "54% better income detection"; "71% users prefer sharing their financial information via Account Aggregator"; a named IIFL Finance case study claiming a "30%" cost reduction and "17%" higher MSME loan approvals; an InCred case study claiming "98% accuracy in fraud detection" and a "60% reduction in false positives" (FinBox, BankConnect; FinBox fraud page).

Where it is strongest: fraud depth, and honesty about its limits. FinBox is the only vendor in this set that publishes an explicit disclaimer that it "does not warrant or guarantee the completeness, accuracy, or detection of all fraudulent activities" and that outputs are "probabilistic and indicative in nature". That is a mark in its favour, not against it.

Not published: a bank or format coverage count; pricing.

Digitap.AI

What it publishes: a Bank Statement Analyzer API taking input via "Net banking", "PDF Upload" and "Account Aggregators"; "Sahamati certified TSP, working with major AAs"; "Categorization of UPI transactions"; "Best-in-class salary detection"; "Custom Scorecards"; an "Enhanced Fraud & Tamper detection module for PDF frauds"; and output as "Report in various forms (Excel, PDF, JSON, XML)" (Digitap, Bank Statement Analyzer API). Corporately it publishes "500+ Clients" and groups products as an Onboarding Suite, an Alternate Data Suite, TSP for Account Aggregator, Expense Manager, Bank Statement Analyzer and Data Enrichment.

Where it is strongest: the explicit UPI categorisation claim and the AA/TSP position. For a digital-first NBFC lending to thin-file borrowers where UPI is the dominant rail, that is the relevant capability.

Not published: bank or format coverage counts; any accuracy percentage; processing time; pricing.

Signzy

What it publishes: a bank statement analysis product under a "Credit" category, sitting inside a wider identity and compliance platform (Identity Verification, Business Verification, Background Check, Credit, Fraud Detection), with "1B+ Users Verified" and "500+ Global Companies". The bank statement analysis page is framed for the US market but states the product accepts "bank statement PDFs of all banks recognised by the RBI", can fetch "through netbanking or Account Aggregator API", segments "outflow and inflow transactions into categories such as rent, food, loans", supports "Multi Bank Statement consolidated Analysis", and returns a "BSA Scorecard PDF". It claims an "Average response time is less than 3s" (Signzy, Bank Statement Analysis).

One inconsistency worth noting neutrally: the same page claims "over 500 data points" in its headline area and "1,000+ data points" in its FAQ. Signzy's India stack page describes "KYC, KYB, vehicle RC checks, and more" and does not list bank statement analysis.

Where it is strongest: as an add-on where you already run Signzy for KYC/KYB and want statement analysis on the same contract and the same integration.

Not published: format counts; accuracy; India-specific BSA positioning; pricing.

Precisa

What it publishes: "1000+ Clients", "25+ Countries", "850+ Banks", "1200+ Bank Formats", "1500,000+ Bank Statement" and "51,00,00,000+ Transaction"; products spanning Bank Statement Analysis, GSTR Analysis, Credit Report Analysis, AML Analysis, Account Aggregator Integration, Forensic Investigation and API Integration; and "ML driven irregularities discovery, comprehensive categorisation of bank transactions & counterparty detection" (Precisa).

Where it is strongest: the combination of statement analysis with GSTR and AML on one platform, plus an explicit forensic-investigation positioning. For a lender whose main pain is fraud and cross-verification rather than volume, that bundle is coherent.

Not published: an accuracy percentage; processing time SLA; pricing.

Karza Technologies (now part of Perfios)

Karza was acquired by Perfios; the acquisition was reported on 16 March 2022, with Karza then serving roughly 450 customers across lending, banking, payments, insurance and fintech (PYMNTS, 16 March 2022). Deal value was reported at approximately $80 Mn by Inc42. As at 27 August 2026 we could not retrieve the standalone karza.in site; its TLS certificate had expired.

Practical reading: if a vendor list still shows Karza as an independent alternative to Perfios, that list is out of date. Evaluate the capability inside Perfios' current product lines.

Finezza

What it publishes: a Loan Origination System ("low-code"), a Loan Management System ("no-code"), Collection & Delinquency Management and Reporting & Analytics, aimed at "Banks NBFCs Fintech Companies". Published integrations include the four bureaus (CIBIL, CRIF, Experian, Equifax), payment rails, and "ICICI, IDFC, and 15+ major banks" (Finezza).

Where it is strongest: Finezza is a lending platform that includes statement analysis, not a statement analyser that has grown into a platform. If you do not yet have an LOS and LMS, that is a different and potentially better purchase.

Not published: bank statement format coverage, accuracy, or processing time; pricing.

Decentro

What it publishes: payments and banking infrastructure — Global Payment Collection, Ledgers, Multi-Currency Accounts, Escrow, Virtual Accounts, UPI, Payouts — plus a "Fabric" identity and compliance stack (KYC & Onboarding), a Credit Bureau API, and "Bytes", described as aggregating "financial data instantly, combining credit reports and KYC records". Scale claims: "$5 Billion Processed Annually", "240 Million+ API Transactions", "Trusted by 2000+ businesses globally" (Decentro, products).

Honest reading: Decentro's own product pages do not name a bank statement analysis product. It belongs on this list because it appears on other people's lists, and because its bank account verification, penny-drop, credit bureau and KYC APIs sit adjacent to statement analysis in most lending stacks. If you need statement parsing and categorisation, this is not currently the product for it, on Decentro's own description.

YuSight

What it publishes: 95.2% extraction accuracy validated against a manual benchmark; ~30 minutes to a first-draft Credit Assessment Memo; 100% of figures cited with one-click source verification; 1 Mn documents processed; 10 Mn credit journeys; modules covering Document Intelligence, Financial Spreading, Repayment Tracker (bank statement vs bureau), Bank Statement Analyzer, Bureau Analyzer and custom analyzers, with India and UAE coverage including AECB and CBRB bureau data.

Where it is different: scope after parsing. The Bank Statement Analyzer output is an input to a spread, a computed ratio set, a bureau reconciliation and a cited memo, in one platform with one audit trail. That is a difference in how far the workflow goes, not a claim that the parsing is better than Perfios'.

Not published: pricing; an independently audited accuracy benchmark.

Comparison table

All entries are from each vendor's own site, retrieved 27 August 2026. "Not published" means the vendor does not state it, not that the capability is absent.

Why a "99% accuracy" claim tells you less than it sounds

Here is the arithmetic every procurement team should run before accepting a headline accuracy figure. It is the reason two vendors quoting similar numbers can deliver very different amounts of rework.

Assume a bank statement with 340 transactions, and a vendor whose accuracy is measured per extracted field.

Per-field accuracy 99.2% Probability one transaction is fully correct 0.992 Probability all 340 transactions are correct = 0.992 ^ 340 ln(0.992) = -0.008032 -0.008032 x 340 = -2.731 e^(-2.731) = 0.0652 = 6.5% of statements arrive with zero errors

Now the same arithmetic at a higher field accuracy:

Per-field accuracy 99.9% 0.999 ^ 340 ln(0.999) = -0.0010005 -0.0010005 x 340 = -0.3402 e^(-0.3402) = 0.7116 = 71.2% of statements arrive with zero errors

What this means in practice. The move from 99.2% to 99.9% field accuracy looks like a rounding difference on a slide and is the difference between an analyst checking every statement and an analyst checking three in ten. So ask three questions of any accuracy claim: accuracy of what unit (field, transaction, or statement), on what corpus (clean e-statements or scanned ones), and against what ground truth (manual re-keying, or the vendor's own second pass).

Then run your own benchmark. Take 100 statements that reflect your actual mix — including the scanned ones, the CC accounts and the two banks your borrowers use that nobody has heard of — have a human key them, and measure at statement level. The number you get will be lower than every published figure, including YuSight's, and it will be the only number that predicts your rework.

When to choose each

Genuinely different answers for genuinely different lenders.

• Choose Perfios if breadth of format coverage is your binding constraint — a large bank or a multi-country lender seeing every statement vintage in the market, or a portfolio where "the parser failed on this bank" is the recurring complaint. It is the market leader in India for bank statement analysis and publishes the widest coverage of anyone here. It is also the safest procurement answer, and for many committees that matters.
• Choose ScoreMe if you need more than bank statements from one vendor — financial statements, GSTR, ITR and 26AS, bureau and legal data — and if you still take physical paper statements at branches, which it explicitly supports.
• Choose FinBox BankConnect if fraud and income detection on retail and MSME digital lending is the problem you are solving, and you want a vendor that publishes what its checks cover and is candid that detection is probabilistic.
• Choose Digitap.AI if you are a digital-first NBFC on Account Aggregator rails with thin-file borrowers where UPI dominates the statement, and you want an API with custom scorecards rather than a UI.
• Choose Signzy if you already run it for KYC and KYB and want statement analysis on the same contract — the integration saving is real and worth more than a marginal feature difference.
• Choose Precisa if your priority is cross-verification and fraud forensics across statements, GSTR and AML rather than raw parsing volume.
• Choose Finezza if what you actually lack is an LOS and LMS. Buying a statement analyser to sit beside a spreadsheet-driven origination process solves the smaller problem.
• Choose Decentro for payments, escrow, collections infrastructure and KYC — not for statement parsing, which it does not currently name as a product.
• Choose YuSight if the bottleneck is downstream of parsing: your analysts get clean transaction data and still spend days building a spread, computing ratios, reconciling the statement against the bureau and writing a memo the credit committee can audit. That is the gap YuSight is built for, and it is a scope difference, not a parsing-quality claim.

If you are specifically evaluating against Perfios, the longer treatment is in Perfios alternatives for credit analysis. For the analytical work the tool is meant to support, start with the complete guide to bank statement analysis.

FAQ

Which bank statement analyser works best in India?

For raw format coverage, Perfios publishes the widest — 4,000+ formats across 1,000+ banks — and is the default answer for a large bank. For depth after parsing, into a spread, ratios and a cited memo, YuSight goes further. Those are different products for different bottlenecks.

Do analysers support all Indian bank formats?

None of them can honestly claim to. Coverage counts are self-defined and unaudited, and every lender has two or three banks that break the parser. Ask for the bank list rather than the number, and test your own statements before signing.

How is analyser accuracy benchmarked?

Almost always by the vendor, against its own corpus, with no published methodology. Nobody in this comparison publishes a third-party audit. Build your own 100-statement benchmark with human-keyed ground truth and measure at statement level, not field level.

Is Account Aggregator support a differentiator any more?

Barely. Most vendors here publish AA support and Sahamati had recorded 538.32 million fulfilled consents by July 2026. Treat AA as table stakes and spend your evaluation time on categorisation quality and what the tool produces at the end.

Does a bank statement analyser replace a credit analyst?

No. It replaces the retyping. Deciding whether a counterparty is a customer or a related party, and whether a turnover gap is tax or under-reporting, is judgement work that no tool in this comparison claims to do for you.

What about Karza — is it still a separate option?

No. Karza was acquired by Perfios, reported in March 2022, and no longer operates as a standalone alternative. If a comparison list still shows it separately, that list has not been updated.

Why does this article not include prices?

Because none of these vendors publishes list pricing, and inventing a number would be worse than leaving the column out. Pricing in this category is negotiated on volume, deployment model and contract length.

What should I ask for in a proof of concept?

A fixed set of your own statements, including scanned ones and at least one CC or OD account; statement-level accuracy against human-keyed ground truth; the categorisation split by NEFT/RTGS versus UPI; and a walk-through of how a number in the output traces back to its source line.

Does the tool need to handle multi-entity group borrowers?

If you lend to MSMEs, yes. Related-party circulation between group entities is the single largest source of inflated turnover, and a tool that analyses one account at a time will not see it.

Key takeaways

• Perfios leads on published coverage and is the safest choice when format breadth is the binding constraint; say so plainly rather than pretending otherwise.
• Every accuracy figure in this market is self-reported, self-benchmarked and measured on an undisclosed unit. Treat them as directional only.
• Coverage counts have no shared definition. Ask for the bank list, not the number.
• Field-level accuracy compounds badly across a 340-transaction statement. Measure at statement level or you will misprice the rework.
• The real dividing line between these products is not parsing quality; it is how far the output travels — transaction list, scorecard, spread, or an auditable memo.
• Run your own 100-statement benchmark. It is a week of work and it is the only number that predicts what your analysts will actually experience.

Related reading: what a credit assessment memo has to contain, financial spreading explained and reconciling the bureau against the bank statement.

Run one borrower through the analyzer — bring your hardest statement set, including the scanned ones, and compare the output against your own manual read.