Finuit

Payslip Analyzer

Caselet → Intelligent document processing for credit approvals

Caselet Payslip Analyzer

Reducing TAT for personal loans with intelligent processing of payslip data

Learn how a large bank accelerated its credit approval processes by 70%

Background Insight

Retail Credit

GHAC Bank is among the fastest-growing Indian banking companies. The bank enjoys a significant market share in the retail and small business credit segments. A high brand recall value and a suite of innovative offerings have helped the organization cement its position as a reputed, trustworthy bank.

The bank has over 6.5 N million customers served by 3000+ employees from 400 branch offices. The bank clocked 13% year-on-year growth in the retail loan segment, enhancing its market share to 18%.


(For confidentiality purposes, the names and identifying details used in this case have been altered.)

Challenges in financial automation

For banks and financial institutions in the retail lending space, the borrower’s payslip is a critical source of information. Income and deduction values in these documents are credible representations of the customer’s creditworthiness. However, manual scrutiny of payslips requires a trained workforce. Even with a dedicated team, the process remains cumbersome and time-consuming.
As GHAC Bank’s focus on the segment grew, the shortcomings of the conventional approach became more apparent. The organization’s ambitious growth plans were hampered by processing delays and manual errors. Switching to a robust, scalable, agile system that could overcome the challenges was imperative.

Human
limitations

The scrutiny of multiple payslips for a single loan application demands significant effort and time.

Errors and
inaccuracies

The rigorous, monotonous work leads to fatigue-induced errors and human mistakes.

Variations in
formats

Data extraction must be precise and consistent, regardless of the diverse layouts and styles followed by organizations.

Terminology
differences

Different terminologies used in payslips make it difficult to recognize and associate name-value pairs.

Keen to upgrade your payslip processing
workflows?

Solution

Finuit optimized solution for scalability, versatility, and seamless
integration with GHAC Bank workflows, enabling instant loan approvals.

Ready for any
input

The solution handles diverse payslips, including scanned documents, using ML algorithms to extract accurate data automatically.

Built for ease
of use

Browser UI enables rapid deployment. Provides instant credit scores and comprehensive reports with downloadable summaries for insights.

Customizable for specific needs

Versatile rule engine configurable for segment- or customer-specific needs, with user-defined parameter privileges.

Features of the solution

Indication of AI-powered confidence score for enhanced reassurance

Dashboard views and controls for hassle-free management

Optimized to handle a variety of payslip layouts, terminologies, and formats

Flexible configuration options to address evolving business needs

Calculation of credit scores and risk factors for instant decisions

In-built tools to detect fraud and discrepancies for risk-free approvals

Results

Unlocking the key to higher efficiency with quick and
failproof credit approvals

350

+

Payslips

01

Minutes

88

%

Accuracy

16

X

Faster decisions

RESULTS

Finuit’s
performance
highlights

Finuit’s performance highlights

Approvals with increased speed and efficiency

The bank’s processing efficiency gets a boost while customers were delighted with quick turnaround times.

Upselling and cross selling from actionable insights

With critical insights into the borrower’s financial health, the solution opened up exciting upselling and cross-selling opportunities.

Risk-free decisions

Pre-emptive risk detection is done by using purpose-built algorithms to spot suspicious data, flag discrepancies, and assess risk factors for better credit decisions.

Streamlined accuracy

Error- free data extraction from scanned or system-generated documents of varying quality and size for sound lending decision.

Keen to upgrade your payslip processing workflows?

Is manual processing of customers’ payslips the weak link in your loan approval workflow? Is the exercise of data extraction from diverse layouts and formats fast enough? Is the acquired data truly error-free?

Unshackle your processes from the limitations of legacy approaches. Modernize loan approvals with Finuit and give your business a competitive advantage.

Payslip
Data
Digitization

Passbook
Data
Analytics