Adaptive Decisioning Platform
Simility's Adaptive Decisioning Platform is built with a data-first approach to deliver continuous risk assurance

As the digital landscape continues to evolve, sophisticated fraudsters relentlessly attempt to find ways to slip past businesses’ defenses.
Organizations need a holistic approach to fraud and risk management that not only provides the flexibility necessary to integrate various data feeds, but also enables detailed analysis, incorporates advanced machine learning, has a rich workbench to analyze results, and is customizable to changing business needs. Simility’s Adaptive Decisioning Platform empowers fraud teams at some of the world’s leading financial services, eCommerce, and payment processing companies to minimize fraud losses, reduce false positives, alleviate friction, and improve operational efficiency. The Adaptive Decisioning Platform is underpinned by four distinct features: data intelligence, powerful analytics and machine learning, intelligent orchestration, and an intuitive workbench and visualization.
Adaptive decisioning customized
to your unique business needs
Adaptive decisioning customized to your unique business needs
The Adaptive Decisioning Platform is underpinned by four distinct features: extensive data intelligence, big-data enabled machine learning, effective decision orchestration, and robust link analysis and visualization.
Reduce Friction
Reduce Manual Reviews
Help Reduce Chargebacks
Deliver Trust
Reduce Friction
Reduce Manual Reviews
Help Improve Conversion Rates
Help Reduce Chargebacks
Deliver Trust
Adaptive decisioning customized to your unique business needs
The Adaptive Decisioning Platform is underpinned by four distinct features: extensive data intelligence, big-data enabled machine learning, effective decision orchestration, and robust link analysis and visualization.
Reduce Friction
Reduce Manual Reviews
Help Reduce Chargebacks
Deliver Trust
Simility's Adaptive Decisioning Platform is underpinned by four distinct features
Extensive Data and Intelligence
As businesses move to mobile and the internet becomes ubiquitous, digital information becomes a crucial aspect in the fight against fraud. Harnessing detailed attributes from user's...
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Big Data Enabled Machine Learning
Combining machine learning with human intelligence creates a powerful blend to continuously stay ahead of evolving fraud. Machine learning allows businesses to build experience...
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Effective Decision Orchestration
The ability to quickly authenticate legitimate users without making them jump through hoops is crucial to creating a seamless customer experience.As data, customer behavior...
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Robust Link Analysis and Visualization
With fraud continuing to rise, analysts need intuitive tools to improve efficiency and productivity. Simility helps simplify the fraud-screening process through a unified interface that...
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How it works
Collect
Collect and analyze data from a variety of sources and detect patterns to identify deep-rooted fraud.
Stitch
Stitch data feeds together to identify correlations, linkages, and overlapping events from multiple channels.
Analyze
Review numerous attributes connected to a transaction, including device fingerprinting, proxy filtering, and behavioral analytics.
Enrich
Augment data from external sources, such as social networks, and use ontology classification and dynamic data linking to analyze how transactions and users connect.
Model
Patented machine learning models and rule-based strategies, combined with a unique method of analytics and linkages that are further customized for each client, analyze the data to automatically approve, reject, or flag for further review.
Decide
Get answers not just a score. Visual link analysis, trend analysis, queries, reports, and scores help analysts make manual decisions and provide feedback to enrich the machine learning models.
How it works
Collect
Stitch
Analyze
Enrich
Model
Decide
Collect and analyze data from a variety of sources and detect patterns to identify deep-rooted fraud.
Stitch data feeds together to identify correlations, linkages, and overlapping events from multiple channels.
Review numerous attributes connected to a transaction, including device fingerprinting, proxy filtering, and behavioral analytics.
Augment data from external sources, such as social networks, and use ontology classification and dynamic data linking to analyze how transactions and users connect.
Patented machine learning models and rule-based strategies, combined with a unique method of analytics and linkages that are further customized for each client, analyze the data to automatically approve, reject, or flag for further review.
Get answers not just a score. Visual link analysis, trend analysis, queries, reports, and scores help analysts make manual decisions and provide feedback to enrich the machine learning models.
How it works