AI Bank Statement Analyser for Banks & NBFCs

A bank statement analyser turns account transactions into a structured view of income, expenses, cash flow and financial obligations. Lenders use this information to assess repayment capacity and identify issues that need review. CART by Novel Patterns applies AI to bank statement analysis for banks, NBFCs and lending teams, helping them connect transaction-level evidence with credit underwriting.

CART extracts transaction data from supported statements, interprets transaction descriptions and categorises financial activity. It analyses income patterns, recurring obligations, account balances and cash-flow movements, then highlights unusual activity for review. Credit teams can use these findings alongside the application, bureau information and their lending policies to make an informed assessment.

Choose a bank statement analyser that fits your borrower segments, Indian bank formats and underwriting workflow. Evaluate transaction categorisation, income and EMI identification, cash-flow analysis, anomaly checks, integrations and data controls using representative cases. CART brings these analysis capabilities into a lending-focused platform. A demonstration and pilot can help your institution assess its fit against your own requirements.

Look beyond transaction extraction. Compare how each tool distinguishes income from transfers, identifies existing repayments, handles unclear narrations and explains financial findings. Test different statement formats and difficult cases, then review output usability, integration effort, support and data-handling terms. For CART, ask for a walkthrough using the types of borrower files your credit team actually receives.

Yes. CART uses transaction descriptions and financial patterns to classify account activity, including income, expenses, transfers and repayment obligations. This helps lending teams examine recurring receipts and outflows without manually tagging every transaction. Reviewing the underlying entries helps an underwriter understand whether a movement represents borrower income, an internal transfer or another type of credit.

CART supports digital PDF bank statements and OCR-based processing of scanned statements. It also supports structured inputs such as CSV and Excel within the agreed workflow. During evaluation, test your actual bank formats, scan quality and document volumes so the team can confirm input coverage, extraction quality and the review process for unclear or incomplete documents.

CART is designed to analyse statements from multiple Indian banks and work across different statement layouts and input types. Confirm the banks, account types and formats needed for your implementation during a demonstration or pilot. Including both common layouts and difficult samples helps establish coverage and a clear process for handling exceptions.

Bank statement analysis helps a lender examine whether an applicant's financial behaviour supports the proposed repayment. CART provides findings on income consistency, cash-flow trends, existing obligations, account balances and unusual transactions. Credit teams can review this evidence with bureau data, supporting documents and institutional policy. The lender retains responsibility for the final credit decision.

Yes. CART helps lending teams review business receipts, operating outflows, cash-flow variation and repayment obligations for MSME and self-employed applications, including freelancer income. Its wider financial intelligence capabilities include financial statement and ITR/GSTR analysis. Combining these inputs can help underwriters investigate differences between declared income and observed banking activity, according to the institution's assessment requirements.

CART flags financial inconsistencies and unusual transaction patterns that may need investigation, including abnormal deposits, round-tripping indicators and possible document manipulation. These signals give credit and risk teams a basis for further review. A flagged transaction is an indicator to investigate alongside the source document and other evidence; it does not by itself establish fraud.

The upload process follows the institution's configured CART workflow. Typically, an authorised user associates the supported statement files with a borrower case, submits them for processing and reviews the resulting financial findings and exceptions. For integrated journeys, statements or structured data can enter through agreed interfaces. A product demonstration can show your team the exact steps for the proposed implementation.

Review who can access the data, where it is processed, how it is protected and how retention and deletion are handled. Institutions should also agree the permitted use of borrower information and the relevant access and audit controls. For CART, Novel Patterns works with the institution to define deployment, data flows and security requirements as part of implementation and the applicable client agreement.

CART supports cloud and on-premise deployment options for enterprise lending workflows. The appropriate architecture depends on the institution's data-governance requirements, integration needs and operating model. During solution design, the teams agree the hosting environment, access arrangements, processing volumes and operational responsibilities for the implementation.

CART provides APIs for connecting financial analysis with existing lending and business systems, including Loan Origination Systems. For an accounting or other downstream workflow, integration planning should confirm the specific application, required data fields, output formats and available interfaces. This defines how findings reach the teams and systems that use them, without assuming a pre-built connector for every product.

Yes. CART supports integration with India's Account Aggregator ecosystem for consent-based access to financial data. This can provide an alternative input to uploaded bank statements within an agreed lending journey. The participating institutions, available accounts, consent process and analysis requirements are confirmed for the implementation.

Bank statement analysis shows observed account activity, while ITR and GSTR analysis provides information from income-tax and GST returns. CART includes capabilities for both, helping lending teams compare banking behaviour with reported income and business activity. This supports financial assessment and investigation of inconsistencies; tax filing itself requires the appropriate filing process and professional review.

Assess the full operating requirement, including supported formats, analysis depth, review controls, processing volumes, integrations, support and data-handling terms. An expense summary for personal budgeting serves a different purpose from evidence used in institutional credit assessment. CART is an enterprise lending solution; contact Novel Patterns to discuss a demonstration, implementation scope and commercial proposal for your use case.

Book a CART demonstration focused on your loan products, borrower segments and existing systems. Agree a pilot using representative statements, including difficult formats and exception cases. Measure extraction and categorisation quality, review effort, processing time and how clearly findings support underwriting. You can also ask the team about relevant customer experience and references when assessing the platform.