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TransactIQ · Risk Flags

Ten India-tuned risk vocabularies

Every transaction description is scanned against ten categorised risk word lists — each built for the Indian market, not ported from a global catalogue. The report returns, per category, the count, total debit, total credit, and the five most frequent matched terms, so a reviewer moves from pattern to evidence in one click.

Behavioural and lifestyle categories

Patterns a reviewer wants to see in context, not in isolation.

130+ terms

Gambling & betting

Fantasy sports platforms, poker apps, rummy apps, sports betting, and offshore casino operators active in the Indian market. The list is maintained specifically for India — many of the platforms that matter here do not appear in any global sanctions or risk list.

90+ terms

Predatory lending

High-cost short-tenure loan apps, including many that have been formally flagged or removed by Indian regulators. Detecting predatory-lender outflows on an applicant's statement is a strong signal of current or prior financial distress that a lender needs to see.

100+ terms

Alcohol

Brand names and retail outlet patterns. The raw signal is not a lifestyle judgement — it becomes useful when combined with spend magnitude, spend trajectory, and the applicant's own behavioural baseline.

45+ terms

Luxury overspending

Luxury brand names across fashion, watches, automotive, and lifestyle categories. A single purchase proves nothing; a pattern inconsistent with stated income is what the reviewer wants to see.

Indian & global platforms

Adult entertainment

Platform and subscription patterns. This list exists because the presence and recurrence of such transactions are signals some institutions are contractually required to surface — not because they carry an inherent credit implication.

Credit-risk and compliance categories

Categories that map directly onto an underwriter\'s or compliance officer\'s decision set.

Retail & platform patterns

Tobacco & controlled substances

Retail vendors, online platforms, and recurring patterns associated with tobacco and other restricted categories. Relevant for both credit assessment and certain insurance and employment-linked checks.

Exchanges, wallets, gateways

Cryptocurrency

Exchange names, wallet service providers, and crypto-fiat on-ramps active in India. The signal is directional — it tells a reviewer the applicant touches crypto flows, which affects tax, income verification, and sometimes regulatory posture.

Bounce & penalty markers

Financial distress

Cheque return charges, ECS bounce fees, minimum balance penalties, NPA-related entries, and recovery agent inflows. These are bank-internal markers that tell a direct story about the account's recent health.

EMI & BNPL markers

Over-leverage

EMI, BNPL, and debt-consolidation indicators. Combined with TransactIQ's obligation tracking and FOIR calculation, this surfaces applicants with layered obligations that are not always visible from a single EMI listing.

Hawala & shell markers

Suspicious patterns

Terminology associated with hawala networks, shell-entity naming conventions, and structured-transaction keywords. This list overlaps with the AML signal set and is maintained separately because it is specifically description-text based.

India-tuned, not translated

Indian bank statement descriptions are short, abbreviated, and often contain merchant aggregator IDs rather than brand names. A risk vocabulary that was written for US or European statement text would miss most of what matters here. TransactIQ\'s lists are authored and maintained for the way Indian banks, Indian aggregators, and Indian merchant systems actually print descriptions — including the abbreviations UPI VPAs, aggregator prefixes, and payment-processor strings that would otherwise hide the underlying counterparty.

For every category the report returns the count of matched transactions, the total debit exposure, the total credit exposure, and the top five matched terms. That is the working set a reviewer needs — a pattern summary and a direct path to the underlying rows. No black-box score, no lifestyle verdict. The call stays with the human who owns the decision.

See how the risk vocabulary reads on a real statement

Evaluating teams can request a walkthrough showing how each category surfaces in the report with counts, exposure totals, and the underlying transaction rows.

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