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Better Credit Decisions with AI

ZScore is an Award-winning and Explainable AI-enabled Credit Scorecard System built for Financial Institutions by Financial Services Professionals

Features

Make real-time credit decisions, Minimize portfolio risk and Maximize collections & recoveries.

High

Accuracy Models

Sophisticated ML models for better predictions and adapts to data changes to improve accuracy over time

API based

Integration

Advanced architectural components for rapid implementation through plug-in modules and multi-threaded APIs for speedy model deployment

Real-time

Scoring

Equipped with multi-threaded APIs, these models predict behaviour, assess risk and generate dynamic scores on the go

Strategy

Builder

Application allows for simulation of stress scenarios at various PD thresholds, and redeployment of adjusted models

Scorecard
Recalibration

Application readjusts and rebuilds models reflecting changed data to produce best approximation scorecards and sustainable outcomes

Explainable
AI

Allowing stakeholders to comprehend the drivers of a model-driven decision, the scoring model is made transparent

A full-scale credit scorecard system spanning customer credit life cycle - Application, Behavior and Collections

Higher
Accuracy Scorecards

Rapid
Development

Low TCO &
High ROI

Advanced Machine Learning algorithms with robust test, train & validation of models 

Develop & Deploy Scorecards within days; Recalibrate on demand to keep them current

Less reliance on expensive resources. Affordable for small & mid-size lenders too

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Benefits 

Next generation Credit scorecards that can instil Confidence, invite Changes and increase Conversions

Drive

High Quality Sales

Real-Time generation of counter-offers within acceptable PD levels for rejected application profiles, thereby enhancing sales

Achieve

Quick ROI

Quick time to market, improving acceptance rates andoptimizing existing portfolio ensures quick and positive returns

Make

Efficient decisions

Real-time processing of new customer applications and generation of next best recommendations improves quality of decisions

Increases

Quality of Collections

Early detection of high-severity cases and identifying appropriate contact plan for each customer improves collection rates

Reduce

Losses & Defaults

Highly accurate and predictive models help in proactiveassessment of customers’ ability and willingness to repay

Better
Risk management

Reviewing existing loan portfolios against latest scorecards and identifying high-risk accounts strengthens credit management