Off-the-shelf AI models based on Alternate data
Get access to our library of pre-configured AI models based on alternative credit data. Whether you are an established lender or just getting started, our models will help you approve more borrowers with confidence, while reducing risk
Turning data into a competitive advantage
Effortless data ingestion and enrichment for sharper decision-making
Preconfigured Features
Rich feature library based on intelligence from 1000s of credit models built and deployed across multiple clients.
Bureau Roll-Ups
Aggregate credit bureau data for consumer and MSMEs, including credit scores, outstanding debts, payment histories, and derogatory marks.
Multiple Credit Sources
Integrate data from various sources such as bank transactions, GST data, financial statements, device data, and trade credit information.
Dynamic Growth
The credit Common Data Model (CDM) continuously evolves as new data and insights are integrated from various client interactions.
Large-Scale Data Ingestion
Designed to handle vast volumes of data from diverse credit sources.
Seamless Integration
Ingests data in various formats, including XML and JSON, from third-party APIs.
Modular and Scalable design
This ensures you can easily add new data sources in future (e.g. Bank statement, GST) or add new derived variables from existing sources.
Unrivaled credit models and scorecards
Unlock precision with world's smartest credit models
A suite of credit underwriting models is available for selection based on product, risk spectrum, and hyperlocal market conditions
Significant intellectual property ensures accuracy while optimizing model parameters
Scienaptic out-of-box features are tested on 400 million records, leveraging 1000+ snapshot, trended, and featured attributes from both Bureau and Non-Bureau sources
Comprehensive documentation of all model development steps and parameters, providing a clear trail from data to decision-making for transparency and accountability
Models provide 7x more risk differentiation compared to standard Bureau Scores, offering significant opportunities to enhance approval rates without increasing risk
Model deployment made easy on our BRE platform
Our credit decisioning BRE platform is designed to simplify the deployment of machine learning (ML) models, making it easier to manage deployment complexity and handle big data at scale during deployment.
Significant Cost and Time Savings
Our solution dramatically reduces the cost and time associated with scoring credit decisioning models.
Accelerated Deployment Cycles
Experience the benefits of faster model deployment cycles, enabling tangible business impact within weeks rather than months or years
User-Friendly Interaction
Enjoy an intuitive, drag-drop UI that facilitates seamless collaboration between the platform, risk modelers, and credit processes.
Flexible hosting
Deployment can be as SaaS or on client’s cloud
Ongoing Monitoring
Scienaptic's Credit Underwriting Platform incorporates continuous feedback loops to enhance the performance and accuracy of credit models over time. By integrating performance data, market changes, and customer insights, our platform makes it easy to monitor model and strategy performance. Scienaptic offers the following model maintenance services:
Improved Accuracy
By continuously incorporating fresh data and insights, our models become increasingly precise and reliable.
Adaptability
The ability to swiftly respond to market changes and new information ensures that models remain relevant and effective.
Customer-Centric
By integrating customer feedback and insights, our models better reflect real-world behaviors and needs, leading to more accurate credit assessments.
Headquarter
Scienaptic AI
50 West 47th Street, Ste. 1614, New York, NY, 10036
Ph: +1 212 244 4030
Branch offices
Florida, Texas, Maryland, Singapore, UAE, Cambodia, Philippines, Indonesia