Indian banks handle an enormous range of financial activity each day, from routine customer transfers to complex cross-border movements. With this scale comes a higher risk of misuse, which makes strong transaction monitoring a core requirement. Regulators in India expect banks to track transactions with precision, evaluate unusual activity, and report concerns to the appropriate authorities.
A well designed monitoring framework helps banks understand customer behaviour, identify inconsistencies, and respond before risks escalate. It relies on accurate data, clear rules, reliable technology, and trained staff who can interpret alerts in context. This blog explains the main transaction monitoring requirements for Indian banks, how these expectations continue to develop, and what institutions can do to build a more dependable compliance structure.
Over the last two years, transaction monitoring has moved from a technical control to a board-level concern for Indian banks and NBFCs. Enforcement has made that shift in transaction monitoring requirements for Indian banks quite clear. FIU-IND has not hesitated to use its powers under the PMLA, including a high-profile penalty on a payments bank for serious weaknesses in monitoring and reporting around online gambling flows and suspected money laundering.
At the same time, RBI has sharpened its tone. The revised KYC Master Direction and related circulars emphasise risk-based due diligence and ongoing monitoring, and enforcement data shows that penalties are no longer limited to outliers. In FY 2024–25 alone, RB I(Reserve Bank of India) reportedly levied more than ₹50 crore in penalties across hundreds of regulated entities, with KYC/AML lapses featuring prominently.
The operating environment has changed just as quickly. UPI has become the dominant retail payment rail in India, now accounting for the overwhelming majority of digital transaction volume and processing tens of billions of transactions each month. That scale, combined with instant settlement, creates very little room for “slow” controls. NBFCs sit in the spotlight as well: RBI has repeatedly reminded them that they are full reporting entities under PMLA, with explicit expectations on risk profiling, continuous monitoring, and the use of appropriate software to generate alerts when behaviour deviates from a customer’s risk categorisation and updated profile. (Reserve Bank of India)
Supervisors, FIU-IND, and FATF reviewers are all converging on the same message. A monitoring programme is no longer judged only by whether a system exists. It is considered by coverage, the quality of scenarios, the evidence of a risk-based approach, how quickly genuine suspicion is escalated, and whether the bank can explain and defend its framework in detail.
At the top of the stack sits the Prevention of Money Laundering Act, 2002 (PMLA), supported by the PML (Maintenance of Records) Rules, 2005. Together, they define “reporting entities” (including banks and NBFCs) and require them to maintain records, verify customers, conduct ongoing due diligence, and furnish information on specified transactions to FIU-IND. (ICLG Business Reports)
The PML Rules spell out how transactions and identity records must be maintained and made available. They require records of both the financial activity itself and the underlying KYC/KYB documentation, retained long enough that the institution can reconstruct individual transactions if needed. (Financial Intelligence Unit) Although the Rules do not use the phrase “transaction monitoring system,” they clearly imply the need for a structured way to track and review customers’ activity against what the institution knows about them.
RBI’s KYC Master Direction translates those high-level obligations into operational expectations for banks, NBFCs, and other regulated entities. One of the core concepts is “ongoing due diligence,” which is defined as regular monitoring of transactions to ensure they are consistent with the customer’s profile, business, and risk rating, as well as the source of funds or wealth. (Reserve Bank of India)
The Direction requires a risk-based approach: customers are classified into risk categories, and the extent and frequency of monitoring must match that risk. It is not enough to apply the same rules to every account; higher-risk customers and products are expected to receive closer and more frequent scrutiny. For NBFCs in particular, RBI has gone further and “reiterated” that they must have appropriate software to monitor transactions and trigger alerts when behaviour diverges from the risk categorisation and updated profile of customers. (Reserve Bank of India)
FIU-IND is the central nodal agency that receives and analyses reports from reporting entities and shares intelligence with law enforcement. Under the PMLA framework, banks and NBFCs must submit several types of reports, notably: cash transaction reports (CTR), suspicious transaction reports (STR), non-profit organisation transaction reports (NTR), and cross-border wire transfer reports (CBWTR). (Financial Intelligence Unit)
The timelines matter. CTRs must generally be filed by the 15th day of the month following the reporting month, and STRs should be submitted promptly once suspicion is formed—commonly interpreted as within seven days of arriving at that suspicion. (Reserve Bank of India) These deadlines assume that transaction monitoring, investigation processes, and STR preparation are tightly connected; if your monitoring programme is slow or fragmented, meeting them becomes difficult.
In practice, this framework creates a set of very concrete expectations for how Indian banks and NBFCs design and operate transaction monitoring in India.
When Indian supervisors talk about “transaction monitoring,” they mean a complete programme, not just a piece of software. Coverage is the starting point. Banks and NBFCs are expected to monitor all relevant products, channels, and customer segments: core banking, cards, UPI and other retail payments, trade and cross-border flows, digital-only products, co-lending arrangements, and fintech tie-ups. If a transaction can move value, supervisors will assume it should be in scope unless there is an apparent, documented reason for exclusion.
Beyond coverage, the emphasis is firmly on risk-based monitoring. Supervisors look for documented segmentation—by customer type, risk rating, product, geography, and sometimes behaviour—and a clear explanation of how monitoring intensity changes across that segmentation. A high-risk merchant acquirer, a UPI-heavy retail customer, and a wholesale borrower in a higher-risk jurisdiction should not be subject to the exact scenarios and thresholds.
Scenario and rule design is another area where expectations have matured. Examiners now ask to see the scenario library, rationales for each scenario, threshold-setting logic, and evidence that volumes and hit rates are tracked and reviewed. It is increasingly common for inspection teams to challenge both overly blunt thresholds (for example, a single cash deposit limit that applies to all customers) and overfitted ones that are hard to justify.
Critically, regulators are alert to “set and forget” monitoring. They expect periodic tuning, back-testing, and validation of scenarios and models, with results formally documented and taken through governance. That can mean sample testing alerts against historical data, using lookbacks to assess missed patterns, or challenging model features and performance at a validation committee. A monitoring programme that does not evolve as products, channels, and typologies change is unlikely to satisfy 2025 expectations. (Lawrbit)
If you want a concise one-page view of these expectations to take into your following internal review or audit meeting, it is worth downloading the RBI/FIU-IND TM controls checklist and using it as a conversation starter with your AML and risk teams.
Every monitoring discussion eventually comes back to data. Without reliable KYC/KYB information, risk ratings, and transactional data across systems, no rules engine or machine learning model will perform adequately. At a minimum, Indian banks and NBFCs need clean customer profiles (including beneficial ownership where applicable), risk classifications, and links between customers and the products they hold. That information must be consistent with the CDD and digital KYC frameworks you already operate. (Reserve Bank of India)
On the transaction side, the monitoring environment needs more than just amounts and timestamps. For India, that often includes device and IP data for digital channels, merchant category and acquirer information, UPI handles and linked accounts, channel-specific identifiers, and cross‑border metadata such as corridor, purpose codes, and counterparty details. Data from loan management systems, collection platforms, and NBFC portfolios should feed the same monitoring view, especially where third‑party repayments or unusual prepayments are early red flags. (AdunaData)
Many institutions find that designing the data model is the real work; once appropriately done, rules and models can be added and refined without re‑engineering the entire pipeline.
An India‑specific segmentation recognises that risk sits differently across retail, SME, corporate, NBFC borrowers, merchants, and aggregator models. A basic three‑tier low/medium/high classification may satisfy the letter of a policy document, but it rarely supports effective monitoring in practice.
For example, within retail, UPI‑heavy cohorts, cash‑intensive customers, and early‑tenure relationships behave very differently and warrant tailored thresholds. Within business banking, small traders, regulated professionals, and large corporate groups require different lenses. NBFC portfolios bring their own nuances: microfinance, vehicle finance, and consumer loans will not share the same indicators of suspicious behaviour, but all need to be visible to the monitoring team. (Reserve Bank of India)
A precise, documented segmentation helps you explain to RBI and internal audit why some customers are monitored more intensely than others and how changes in risk classification flow through to monitoring rules and models.
Once the data and segmentation are in place, the scenario library carries most of the weight. For Indian banks and NBFCs, an effective library usually covers:
Scenarios should be written in plain language with a clear statement of what the bank is trying to detect, why the scenario is relevant, and how thresholds were selected. Over time, additional scenarios can be added for typologies specific to your franchise, such as misuse of co‑branded cards, unusual behaviour in BNPL portfolios, or particular risks in gold or property‑backed lending.
Machine learning models can sit on top of, or alongside, this library to identify behaviour that falls between the cracks of manual rule design. In practice, many institutions start with models that score customers, accounts, or merchants on relative risk and then use those scores to prioritise alerts or refine thresholds, rather than replacing rules entirely.
A monitoring programme without clear ownership will drift. Leading banks and NBFCs tend to formalise roles around at least three elements: who owns the overall TM framework, who designs and maintains rules and models, and who approves changes.
In many setups, the first line (operations, fraud, or business risk) proposes new scenarios, the second line (compliance / AML) challenges and refines them, and a formal committee signs off rules and models after reviewing evidence from testing. Change logs capture what was changed, why, who approved it, and when it went live, with links to test results and MI. Internal audit then reviews both the design and the operation of the framework on a periodic cycle.
The governance model does not need to be complicated, but it needs to be visible. When inspectors ask, “Who is accountable for transaction monitoring in India, and how do you ensure it stays current?”, the answer should be backed by minutes, change records, and performance reports rather than informal practices.
Suppose you want to see how these governance and design principles translate into an actual system view. In that case, it can be helpful to look at a dedicated transaction monitoring software implementation.
Transaction monitoring is only the first half of the obligation. The other half is turning alerts into well‑founded STRs and CTRs that reach FIU‑IND within the required timelines and contain enough detail to be useful for intelligence and investigation. (Financial Intelligence Unit)
In most banks, alerts feed into an investigation workflow that includes at least two levels of review before an STR decision. Level‑one analysts examine the alert, pull additional information, and document whether there is any plausible explanation for the activity. Level‑two reviewers—often more experienced investigators or AML officers—look at borderline cases, challenge weak rationales, and decide whether suspicion is established. Once that point is reached, the case moves to the Principal Officer or FIU cell for final STR decision and filing.
Timelines are tight. Because STRs should be filed within a short period after suspicion is formed, backlogs in the alert queue, poor triage, or fragmented systems can quickly put you offside. The monitoring setup should therefore support prioritisation (for example, by risk score or potential impact), automated population of STR fields, and ready access to supporting documents such as KYC files, account statements, network diagrams, and internal correspondence.
CTRs are more mechanical but still rely on good monitoring and data quality. If large cash transactions are not adequately captured, categorised, and reconciled, you may end up with inaccurate or incomplete CTRs. Given that FIU‑IND expects reporting entities to maintain their records in a way that allows reconstruction of individual transactions, gaps in CTR files can trigger broader questions about your data and monitoring environment. (Reserve Bank of India)
For both STRs and CTRs, clear written procedures, escalation paths, and role definitions are essential. Many of the weaknesses identified in enforcement actions have less to do with the idea of monitoring and more to do with how alerts, investigations, and reporting are stitched together in practice.
Supervisors rarely publish exhaustive lists of transaction monitoring failures for individual institutions, but themes repeat across inspections, enforcement orders, and market commentary. A non‑exhaustive set of recurring issues looks like this: (LexisNexis Risk Solutions)
Each of these weaknesses is fixable. They do, however, require clarity on ownership, investment in data and systems, and a willingness to treat transaction monitoring in India as a living framework rather than a one‑off implementation project.
For many banks and NBFCs, the most useful outcome of a review is a simple list of “must‑haves” that can be translated into action plans. The items below are not exhaustive, but they capture the core of what RBI, FIU‑IND, and internal audit will expect to see in a credible transaction monitoring programme in 2025 and beyond:
If you want a structured way to turn this checklist into workstreams and action items and see how this looks in an actual TM system, book a demo with one of our product experts.
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