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What is Scienaptic?

Our system provides plug-and-play APIs that seamlessly incorporate both traditional and non-traditional credit data sources, enabling faster data assimilation for improved accuracy in credit evaluations. It boasts an extensive predictor library, rooted in deep credit knowledge, and includes pre-set attributes that optimize the credit decision-making process. Our unique AI and machine learning credit modeling techniques are fully transparent and significantly enhance results. Users have the ability to conduct multiple champion-challenger analyses concurrently, facilitating the comparison of different credit strategies within one cohesive framework. The rollout of new credit models and strategies is both rapid and effective. Our AI-based credit underwriting frameworks are designed to be not only transparent and compliant with FCRA regulations but also exceptionally dependable. They feature automated and straightforward reasoning for negative actions, ensuring clear communication. Thorough documentation is available, outlining the rationale behind the models, their strengths, and any constraints they may have. Each model's attributes undergo stringent disparate impact evaluations to ensure fairness in their construction. Additionally, our AI credit models provide an extensive array of explanations for negative actions, which guarantees that users are well-informed about the decision-making rationale and its consequences. This comprehensive suite of features ultimately equips organizations to execute fair and well-informed credit decisions while also fostering trust in the process.

What is Fairplay?

FairPlay has launched an innovative Fairness-as-a-Serviceâ„¢ solution specifically designed for the financial industry. By leveraging cutting-edge AI technologies, we can assess your automated decision-making models in a matter of minutes, aiming to improve both fairness and financial performance. Our offerings include five detailed Fact Sheets that delve into the mortgage equity landscape for female, black, Hispanic, millennial, and baby boomer applicants. In crafting these insights, FairPlayâ„¢ conducted a thorough analysis of publicly available data sourced from the Home Mortgage Disclosure Act Database for the year 2020. Our study concentrated solely on individuals applying for new home purchases, intentionally leaving out those looking for refinancing or lines of credit. We computed the Adverse Impact Ratio (AIR) for every county throughout the United States and broadened our investigation to include AIR values for 20 major metropolitan regions. FairPlayâ„¢ identifies discrepancies in your decision-making frameworks and provides actionable strategies to enhance both fairness and profitability, showcasing to clients, regulators, and the broader community your dedication to equitable practices. By aligning with regulatory requirements, our method fosters greater trust and transparency within the communities you serve, ultimately contributing to a more just financial landscape for all applicants.

Media

Media

Integrations Supported

Plaid

Integrations Supported

Azure Content Protection
BuyDRM
Fastevo
StreamProbe

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Scienaptic AI

Date Founded

2014

Company Location

United States

Company Website

www.scienaptic.ai/

Company Facts

Organization Name

Fairplay

Company Location

United States

Company Website

fairplay.ai/

Categories and Features

AI Lending

Not specified

Credit Management

Not specified

Categories and Features

AI Lending

Not specified

Loan Origination

Not specified

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