Leverage Credit Analytics to provide your members with
competitive financial services
Manual underwriting processes bear high operational costs and impact the decisioning turnaround time. Automating your credit decisioning process can dramatically reduce operational costs and enable you to make decisions within seconds.
By leveraging multiple data sources, data pooling and community scoring, and then combining this with credit analytics and machine learning algorithms, Credit unions can provide fairer and more competitive credit offers to its members, without compromising your credit risk control.
By running PARETIX advanced credit models periodically, credit unions can provide members with their financial health status by analyzing how their credit eligibility has evolved through their financial state and credit consumption.
The PARETIX Smart Credit Analytics (SCA) Platform is a complete AI-Driven underwriting solution, that includes:
Policy/decision engine
ML-driven scoring engine
Portfolio management dashboard
The Solution leverages traditional and alternative data sources, including Open Banking, Credit Bureau, CRM, etc. to develop a bespoke credit scoring model that combined with your lending policy, will provide a personalised credit recommendation.
Members’ FINANCIAL HEALTH
PARETIX offers credit unions tools to support the financial credit wellness of their members:
By running PARETIX advanced credit models periodically with the combined traditional & communal characteristics,
credit unions can provide members with their credit wellness status by analyzing
how their credit eligibility evolved through their financial state and credit consumption
PARETIX Credit Data Pooling
Credit data pooling enables even small financial entities to make use of advanced models based on Big Data and Machine Learning
PARETIX leverages this to improve credit unions underwriting models through the use of aggregated anonymized data
from multiple credit unions and responsible lenders
PARETIX Community Scoring
PARETIX cherishes the great communal value of credit unions and combines unique community features into the traditional credit scoring.
Incorporating credit-union community’s characteristics and the extent of the borrower's engagement in the credit union’s community activities (Community & Engagement Scoring), may help assessing the borrower's credit eligibility
WHY PARETIX
Bespoke models leverage your domain expertise and uniqueness to develop your own credit scorecard
AI Driven Credit Scorecard - Machine Learning Algorithms to constantly improve your model. No data scientist required
Rapid Implementation - Up and running in weeks
Your business expert has oversight on the algorithms and can challenge them (not a black-box)
