Credit Score Automation

Credit Score Automation

Credit Score Automation is an Intelligent Process Automation product that analyses Bank Statements and Tax Returns to build risk scores for accelerated loan processing. Using a combination of proprietary advanced technologies such as Computer Vision, Computational Geometry & Machine Learning Credit Score Automation extracts information from both PDF as well as scanned images (JPEG,PNG, etc.)


Lending institutions process 3-6 months old Bank Statements and Annual Income Tax Returns to gauge the creditworthiness of each applicant. Such processing costs significant time and resources.

What if you could do this instantly? In under two minutes, Credit Score Automation (1) extracts and reads Bank Statements or ITRs (2) tabulates key information such as, in the case of Bank Statements, cheque defaults, monthly balances, salaries, expenses, and EMI/loan and in the case of ITRs, Gross Incomes, Expenses and Profits (3) builds insights about the loan applicant and assign a risk score to enable better decisions.


From Bank Statements, Credit Score Automation instantly extracts transaction details as well as header information such as customer name, address and statement period.


It produces in-depth insights into the customer’s financial position across parameters such as
average income, average expenses, and existing debt

Risk Scoring

Using above insights, and other external information such as credit scores from third-party agencies, Credit Score Automation assigns a ‘risk score’ for a given loan amount and tenure.

Most Salient Features are

How does Credit Score Automation work?

Setting up

Credit Score Automation integrates with the bank’s workflow using a simple plug-and-play API.


Its region-of-interest detector identifies each element — header information, transaction, debit / credit etc. Credit Score Automation accepts all formats that are in use by banks in India.


It extracts information across pages without missing a single transaction value.


Based on predetermined rules, it classifies and analyses the data available, into income, expenses, debt etc.


Credit Score Automation’s machine learning algorithms produce detailed reports about the creditworthiness of the applicant. It also assigns each applicant a risk score to facilitate decision-making.

Credit Bureau Integration

Credit Score Automation integrates with popular Credit Bureaus like CIBIL, Equifax etc to obtain their corresponding credit scores of the applicant.

How we achieve near-100% accuracy?

Multiple algorithms for region-of-interest detection

In KYC Automation, there are multiple algorithms working simultaneously on region-of-interest identification, ensuring 100% detection.


De-noising systems from simple Otsu methods to deep learning-based segmentation algorithms improve KYC Automation’s extraction quality.

Exclusive algorithms for correcting false predictions

Krish IT’s patent-pending algorithms are designed especially to correct false predictions, and guess values in noisy images, at 100% accuracy.

Dual algorithmic journeys for building quorum

It builds quorum using two algorithms for every field. Each algorithm has different deep learning bases and maths for feature extraction methods, number of layers, loss functions etc.