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Credit Scoring Software

One button solution to build a scorecard and score your customers. Make solid credit decisions, fight fraud, reduce churn, cure bad debts with ABLE Scoring. Get 100% AI-based automated decisions online or score your customers in a batch.


As simple as three steps

Step 1. Upload

Upload historical dataset to our cloud and train new model with AI

Step 2. Train

Check the reports and approve the model for future use

Step 3. Score

Upload new data for assessment and get it back scored in a second

Year Established
Team Size

Predictive Models Across Full Customer Lifecycle

Onboarding and Origination: application score, fraud score, best offer recommendation model

Customer Management: behavior score, attrition score 

Collection and Recoveries: behaviour score, next best time to call model                                                           

Year Established
Team Size

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Smart credit decisions and AI models

Recommended cut-off for the scorecard is automatically calculated for every model. You can add rules to combine two scores like Credit Bureau score and another one from your own model. Scorecards can be applied in a sequence automatically to achieve the final credit decision.

Why ABLE Scoring

Predictive Analytics Can Be Simple

Easy to use

No special training required. Just upload an XLS file and get your scorecard. Build dozens of models for every customer segment in a day.

AI Models and Classic Scorecards

You can compare AI/ML models and classic logistic regression score cards by performance, stability and explainability. Check all your models on one dashboard.

Model and population stability checks

Scorecards and predictive models tend to lose their power with time. Check your model performance as well as your population stability with powerful multidimensional reports.

Data quality assured

Built-in data checks for formats, consistency and missing values. Detailed reports showing the quality data uploaded.

Models under control

No deployment efforts, transparent model repository, history of scored datasets.

Custom predictive models

ABLE Scoring can be used to create models tailored to various business problems across the enterprise.

Need scoring? Get in touch

Send request

Recent projects

We have successfully delivered over 65 projects in lending and banking process automation. Some of them are under NDA, though some we are glad to share with you.

More case studies
Loan origination

Lending Platform improved loan origination process


Hosting scorecards without the Bank’s IT department

Early Warning

Early Warning System for the Retail Commercial Bank


Soft-collection Remastering in a Bank

Trusted by banks and private lenders

Tier 1 and Tier 2 banks and microfinance institutions use our solutions to ensure a continuous and high-quality lending process. 

Year Established
Team Size

What Our Clients Are Saying

“Very mature solution for loan origination and servicing that has rich features and a powerful decision engine.

Fast deployment within 3 months, a lot of features are available out-of-the-box. The platform automates the entire loan origination process front-to-back. Gave about 558% improvement in productivity. Availability of multichannel interaction with customers like chatbots, messengers, etc.”

Paul Maleski
Product Owner


What is the credit scoring process?

The process of credit scoring is the assessment of a borrower’s creditworthiness based on specific criteria defined by a lender as critical for loan approval.

What is credit scoring and how does it work?

Credit scoring indicates a borrower’s reliability and creditworthiness and signals to a lender the level of the applicant’s risk. Credit scoring is usually based on a variety of factors to determine the terms of a loan (interest rate, for instance) offered to borrowers based on the probability of repayment.

What are the 5 ways credit scores are calculated?

There are 5 major criteria taken into consideration by financial institutions while calculating a borrower’s credit score. They are payment history, total owed amounts, credit history length, recent credit activity, and the borrower’s credit mix.

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