Litigation Search API for Banks and NBFCs

Lending Risk · API Integration

Updated for 2026 · Claw Editorial

A bank or NBFC that lends without checking a borrower’s litigation history is taking on risk it cannot see: a pending recovery suit, a cheque bounce case, or a SARFAESI action against the same person or entity, sitting quietly in a court record that nobody looked up. Doing that check by hand does not scale once you are processing hundreds or thousands of loan applications a month. This page explains why litigation search belongs in the underwriting pipeline as an API call, not a manual step, what such an API needs to get right for lending specifically, and how it fits alongside the due diligence and monitoring work banks and NBFCs already do.

01Why litigation history matters before you lend

Litigation history is a direct signal of credit risk. A borrower or guarantor with a pending recovery suit, a cheque bounce case under Section 138 of the Negotiable Instruments Act, a SARFAESI proceeding, or a matter before a Debt Recovery Tribunal is telling you something about their repayment behaviour that a credit score alone will not show.

It is not just about the individual

For business loans, the check has to go wider than the applicant: co-borrowers, guarantors, directors, and the borrowing entity itself can each carry litigation exposure that affects the overall risk of the deal. Missing one name in the chain can mean missing the one case that mattered.

It matters after disbursement too

The check is not a one-time gate at onboarding. A clean borrower today can pick up a new case next quarter, and lenders that only check at origination have no way of catching that early warning signal during the loan tenure. That makes ongoing monitoring, not just a one-time report, part of the same problem.

02Why manual court search does not scale

Checking one name against Indian court records by hand is possible. Checking it for every loan application, every month, across a growing book, is not.

• Volume: a retail or SME lender processing hundreds of applications a day cannot have staff manually search court portals for each applicant, each guarantor, and each co-borrower.
• Turnaround time: digital lending decisions are often made in minutes or hours. A manual court search, or a verification report that takes days to come back, does not fit that window.
• Common names: India has a huge number of people sharing the same or very similar names. A search that matches only on exact spelling will miss genuine hits when a name is recorded with a variant spelling, and will throw up false positives when it matches the wrong person entirely. That is a name-matching problem, not just a data problem, and it is why phonetic name matching matters so much for this use case.
• No structured output: a human-read court record or a PDF report is fine for a one-off check, but it does not plug into a loan origination system (LOS) or credit decision engine. Underwriting automation needs structured, machine-readable data, not a document someone has to open and read.

For a lender, litigation search is not a report you read once. It is a data feed that has to sit inside underwriting and keep watching after the loan is disbursed.

03What a lending-grade litigation search API needs to get right

Not every court-data tool is built for a lending workflow. For banks and NBFCs, five things matter most.

• Speed: results need to return fast enough to sit inside a real-time or near-real-time credit decision, not after it.
• Coverage: which courts the API actually searches, and for what time period, decides whether a check is genuinely useful or just gives false comfort.
• Name-tolerant matching: proximity and phonetic matching reduce both missed hits (false negatives) and wrong-person hits (false positives), which matters at scale because both types of error cost money, one in bad loans and the other in wrongly rejected good borrowers.
• Structured, integrable output: a proper API returns structured data your LOS or underwriting engine can consume directly, not just a document to read.
• Bulk and repeat search: the ability to check many names at once, and to run the same check again later for portfolio monitoring, not only a one-time search at onboarding. See our guide to bulk litigation search and monitoring in India for more on that.

Evaluate any option against these five before looking at price or brand.

04Where litigation search fits in the lending workflow

Litigation search is not a single step. It shows up at three different points in a loan’s life, and each one has a slightly different requirement.

The first two stages are about a single, fast check per applicant. The third is a different shape of problem entirely, a scheduled bulk check across an entire existing book, and it needs to be designed for that from the start rather than bolted on later.

For the specific job of confirming whether a given person has any cases at all before you go deeper, see our guide on how to find all cases against a person in India.

05The landscape today

Litigation and court-record checks for lending sit at the intersection of two different kinds of vendor, and it is worth knowing both exist before you choose.

One kind is the background-verification and legal-BI category, built for exactly this lending use case. Perfios, for example, offers a legal search / litigation intelligence product aimed at banks and NBFCs, positioned around searching case records across a large number of Indian courts to support borrower risk profiling as part of credit underwriting. Other verification providers offer similar court-record-check APIs aimed at background screening more broadly, spanning employment, tenancy, and lending checks alike.

The other kind is legal-research and case-search platforms, built primarily for lawyers doing case-law research and citation work, which is a different job even though the underlying court data overlaps. Not every tool that searches court records is built with a lending workflow, structured API output, and bulk monitoring in mind, so it is worth checking that specifically rather than assuming any court-data provider fits.

This is a fast-moving space and coverage claims should always be verified directly with the vendor before you rely on them for underwriting decisions.

06How to choose

Start from the workflow, not the vendor list.

If your priority is fast, automated checks at onboarding for individual and SME borrowers, weight speed and name-matching accuracy heavily, since that is where false positives and false negatives cost the most. If you lend to larger corporate borrowers or need appellate-level visibility, High Court and Supreme Court coverage, with reliable citations, matters more than sheer breadth of every district court. If you already have a book to monitor, confirm the provider supports scheduled bulk re-checks and alerting, not just one-off lookups, before you sign anything.

Whichever way you lean, ask for a sample structured response before committing, since that tells you more about real integration effort than a feature list does.

07Where Claw fits

Claw is an all-in-one legaltech platform for Indian advocates, law firms, and corporate legal teams, combining AI-based case search, an AI legal assistant (Legal GPT), case management, and compliance automation across all Indian courts and tribunals.

Claw offers API access to its court and litigation data, so banks and NBFCs can bring litigation checks into their own loan origination and underwriting systems instead of running searches by hand. For the case-search job this covers, Claw’s database spans the Supreme Court (1950 to 2026) and 25 High Courts (1980 to 2026), across 1.5 billion+ case records and 30 crore+ judgements, with results typically returned in under 5 seconds. Name-tolerant matching, including proximity and phonetic matching, is built in, which directly addresses the common-name problem described above.

That coverage is strongest for Supreme Court and High Court level litigation, appeals, and SARFAESI or DRT matters that have moved up to a High Court, which matters most for larger exposures and corporate borrowers. Banks and NBFCs that also need visibility into district courts, tribunals, and lower forums for an existing book get that through Claw’s separate case management coverage of 8200+ courts, including auto case updates and alerts, which is better suited to ongoing portfolio monitoring than a one-time search.

Technical specifics such as authentication method, request limits, and API pricing for this use case are best confirmed directly with Claw’s team, since these depend on integration scope.

08Sources and further reading

Referenced in this guide:

• Perfios (legal search / litigation BI for lenders): perfios.ai
• Claw: clawlaw.in

Coverage and pricing details for third-party vendors change over time and should be confirmed directly with each provider before relying on them for a live underwriting decision.

09Frequently asked questions