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Average Ratings 0 Ratings

Total
ease
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design
support

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Description

GiniMachine, an AI-based solution to automated decision making, is called GiniMachine. It uses advanced machine learning algorithms and historical data from companies to create high-performing scoring models. It can be used to score credit, collect, or apply, expand marketing (churn prediction), as well as sales (cross-sell, upsell) opportunities. The system uses a customized implementation of the decision tree ensemble technique, augmented with a set Heuristics for preliminary data processing. GiniMachine provides models for building and supplying. They are fully compliant to the BASEL requirements. GiniMachine works with all types of data, raw and prepared, including: Socio-demographic data Credit bureaus info Transactional data Social network data Other data.

Description

Monsoon utilizes advanced machine learning-based underwriting models to uncover ongoing trends that allow for the prediction of future repayment behaviors based on extensive borrower data, which includes credit bureau information, bank statements, demographics, location data, and, when available, alternative data sources. These identified trends are distinct for each lender, reflecting their specific methods in borrower sourcing, underwriting processes, and collection strategies. The machine learning system continuously “learns” from the historical portfolio and application-level data of each lender, integrating this with repayment data for every borrower within that portfolio. Monsoon CreditTech’s innovative technology is currently employed by 24 lenders who operate across diverse portfolios in both Retail and MSME lending sectors. In the Retail lending space, various loan products are supported, including Consumer Durable loans, Personal loans, loans for Four or Two-Wheelers, Home loans, and Credit Cards, thus catering to a wide array of borrower needs and financial situations. This adaptability in product offerings allows lenders to better serve their clientele while minimizing risk and optimizing repayment efficiency.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

CREDITONLINE Yes 
Ultimus Digital Process Automation Suite Yes 

Integrations

CREDITONLINE No 
Ultimus Digital Process Automation Suite No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

HES FinTech

Founded

2017

Country

Lithuania

Website

ginimachine.com

Vendor Details

Company Name

Monsoon CreditTech Technologies

Website

monsoonfintech.com/products/

Product Features

Predictive Analytics

AI / Machine Learning No 
Benchmarking No 
Data Blending No 
Data Mining No 
Demand Forecasting No 
For Education No 
For Healthcare No 
Modeling & Simulation No 
Sentiment Analysis No 

Product Features

Insurance Underwriting and Rating

Broker / Agent Portal No 
Carrier Upload No 
Commercial Lines No 
Comparative Insurance Rating No 
Customer Portal No 
For Casualty Insurance No 
For Health / Medical Insurance No 
For Life Insurance No 
For Personal Insurance No 
Multi-State No 
Multiple Line Rating No 

Loan Origination

Amortization Schedule No 
Audit Trail No 
Closing Documents No 
Compliance Management No 
Customer Database No 
Digital Signature No 
Document Management No 
Fee Management No 
Loan Processing No 
Online Application No 

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