Digitap AI Solutions
Digitap.AI Enterprise Solutions Private Limited · Other
Digitap AI Solutions is an India-focused credit report analytics API that pulls bureau reports and bank statements, then returns structured risk data that lenders can plug into underwriting decisions.

About Digitap AI Solutions
What Is Digitap AI Solutions
Digitap AI Solutions is a set of APIs and dashboards built by Digitap.AI Enterprise Solutions, a Bangalore company that sells financial data tools to banks, non-bank lenders and fintech apps. The credit report analytics API sits between a lender and the credit bureaus. It fetches a customer's report, parses the raw file and returns fields a loan engine can read without human help.
The product matters most in a market where bureau files still arrive as dense PDFs or nested JSON. A credit analyst can spend ten minutes reading one report, and a high-volume lender processes thousands a day. Digitap shortens that step by turning tradelines, repayment history and enquiry records into clean variables, then layering a credit risk scorecard on top.
The limits are worth knowing up front. This is an India-only product, sold through demos and contracts rather than a signup form, and it has no free plan. Lenders also stay responsible for consent, for the policy they build around the data and for the final approve or decline call.
Getting Started
- Book a demo through the Digitap site and describe your lending use case, expected monthly volume and the bureaus you need.
- Sign the contract, complete KYC for your company and receive sandbox credentials for the API.
- Send a test request with customer consent, PAN and mobile number, then check the parsed fields against the source report.
- Map the returned variables into your scorecard or rules engine, run a pilot on live applications and move to production.
Product Information
A quick look at Digitap AI Solutions's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Credit risk analysts at NBFCs
- Product teams at lending apps
- Collections and portfolio teams
Tasks
- Reading a credit bureau report at scale
- Estimating income and obligations
- Building a credit risk scorecard
- Screening applicants during onboarding
Scenarios
- Lending to customers with a thin credit file
- Replacing a manual underwriting desk
- Pre-approved offer campaigns
Key features
Bureau Report Retrieval Through One API
Digitap connects to Indian credit bureaus so a lender sends one request instead of maintaining separate integrations. The call takes customer consent, identity details and the bureau you want, then returns the report in a machine-readable form. Digitap's own consumer score page runs on Experian data, and enterprise clients can request the bureaus their policy allows.
Bureau Report Parsing Into Structured Fields
Raw bureau files bury the useful signals in long text blocks. The API performs bureau report parsing and returns accounts, credit limits, current balances, payment history, days past due and enquiry records as named fields. That structure is what makes credit report analysis repeatable across thousands of applications instead of depending on whoever reads the file.
Custom Scorecards and Underwriting Variables
Digitap builds scorecards around a lender's own portfolio rather than selling a single black-box score. Its alternate data suite exposes roughly 700 financial variables from bank data, and the device module reports more than 1,400 variables covering loans, cards, wallets and bill payments. A credit underwriting API call can return these alongside the bureau view, so risk teams can test weights before committing to a policy.
Bank Statement Analysis Alongside Bureau Data
The credit report tells you how a customer has handled borrowed money. Bank statements show how money moves now. Digitap accepts statements through net banking, PDF upload or the Account Aggregator framework, then returns categorised transactions, balance trends, salary detection and bounce history. Lenders use the bank statement analysis API for income checks and for applicants who have little or no bureau history.
Fraud and Tamper Checks
Digitap runs document and data checks on the files it receives. The bank statement module looks for signs of edited PDFs, while the device and SMS module surfaces fraud indicators that a report alone would miss. For a lender, that means a suspicious statement can be flagged before it reaches a credit decision, not after a loan has been disbursed.
Compliance and Consent Controls
Digitap holds ISO/IEC 27001, SOC 2 and ISO 22301 certifications, and it operates as a Sahamati-certified TSP for the Account Aggregator framework. Consent artefacts and audit trails travel with the data request. Lenders still need their own consent copy and grievance process, yet the vendor side gives auditors something concrete to review.
Pros and cons
Pros
- One vendor covers bureau reports, bank statements and device data, which cuts the number of integrations a lending team has to maintain.
- Parsed fields arrive ready for a rules engine, so credit report analysis stops depending on manual PDF reading.
- Custom scorecards let a lender keep its own risk appetite instead of accepting a vendor's generic score.
- The compliance stack includes ISO 27001, SOC 2, ISO 22301 and Sahamati TSP status, which helps during security reviews.
- Digitap reports more than 200 million API hits a month across its client base, a useful signal of operating scale.
Cons
- There's no public price list and no self-serve trial, so a small team can't test the credit report analytics API without a sales conversation.
- Coverage is built for India, which rules it out for lenders operating in other markets.
- Production use depends on bureau and Account Aggregator uptime, and consent drop-off can still slow an application.
- The API returns data, not a lending policy, so you need risk staff who can turn variables into cut-offs.
Frequently asked questions
It returns a parsed credit bureau report with accounts, balances, repayment history, days past due and enquiries, plus optional scorecard variables. Your system receives fields it can score, not a PDF that someone has to read.
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