Name: Stratyfy
Author: Stratyfy.com

Help Desk

Web and Video Conferencing

Customer Support

AI Code Generation

Accessibility Testing

Development

Classroom Management

Virtual Classroom

Education

Business Intelligence (BI)

Collaboration

Data Extraction

Emissions Management

Integrated Workplace Management (IWMS)

Intellectual Property (IP) Management

Risk Management

Enterprise

Accounting

Digital Banking

Nonprofit Accounting

Treasury Management

Finance and Accounting

Applicant Tracking

Corporate Learning Management

HR Management

Payroll

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

3D Printing

Authorization

Cloud Storage

Configuration Management

Data Collaboration

Fraud Detection

Game Engine

IP Address Management (IPAM)

Integration Platform as a Service (iPaaS)

IoT Security

LAN Switches

License Management

Network Performance Monitoring

Network Security

Open-Source Database

Operating Systems

SOA Governance

Service Desk Outsourcing

Single Sign-On

Vendor Risk Management

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Appointment Scheduling

Audience Intelligence

Content Experience

Content Management

Customer Journey Mapping

Email Marketing

Influencer Marketing

Market Research

Marketing Automation

Social Media Management

Survey & Forms Building

Text to Speech

Video

Video Marketing

Web Analytics

Marketing

Meeting Room Booking

Project Management

Professional Services

Customer Relationship Management (CRM)

Sales Performance Management

Social Commerce

Sales

Virtualization Security

Security

Agriculture

Banking

Donor Management

Equipment Rental

Rental Property Management

Vertical-Specific

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Stratyfy is a transparent machine learning solution that aims to enhance credit and risk decisions. According to the vendor, this user-friendly platform is targeted towards financial institutions, fintech companies, insurance companies, lenders, and credit risk analysts. Stratyfy claims to offer features that can assist in making accurate and efficient credit decisions, detecting fraud, and addressing biases in models, with the potential to increase revenue and reduce risk.

## Key Features

**Credit Risk Assessment**: According to the vendor, Stratyfy's advanced modeling approach enables financial institutions and fintech companies to make accurate credit decisions in consumer and small business lending. Users are said to have the ability to easily build, import, test, and analyze flexible models, which could potentially save valuable time and resources.

**Fraud Detection**: The vendor states that Stratyfy's fraud detection solutions utilize machine learning to help insurers identify suspicious activity and understand the underlying drivers. Insurers are claimed to have the capability to build, import, test, and analyze flexible and interpretable models, potentially reducing false positives and manual review time.

**UnBias™**: According to the vendor, Stratyfy's UnBias™ solution offers continuous monitoring and addressing of systemic liabilities such as biases and unreliable training data. Users are claimed to be able to build and analyze smarter models, making model bias a reportable key performance indicator (KPI). The solution is said to combine human insights and AI to optimize fairness and performance.

Studio Pricing - Free

Studio Pricing - Standard

Production Web API - Dev/Test

Production Web API - Standard S1

Production Web API - Standard S2

Production Web API - Standard S3

Azure Machine Learning

The Entire Web Application

Small - 3 project slots -1200 credits

Medium - 10 project slots - 1200 credits

Large - 50 project slots - 1200 credits

Gavagai

Stratyfy

Machine learning tools are algorithmic applications of artificial intelligence that give systems the ability to learn and improve without ample human input; similar concepts are data mining and predictive modeling. They allow software to become more accurate in predicting outcomes without being explicitly programmed. The idea is that a model or algorithm is used to get data from the world, and that data is fed back into the model so that it improves over time. It’s called machine learning because the model “learns” as it is fed more and more data.

Machine Learning

Stratyfy.com

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What is Stratyfy?