Article Series: Scoring Concepts
This series of articles explores the foundational concepts behind building a performant and high-quality Batch Scoring solution in Quantexa. Each article breaks down a key component of the scoring process — from network generation and scoreable models to alerting and network pruning — offering practical guidance and design considerations. How will the articles help your team and deployment? Whether you're new to Batch Scoring or refining an existing implementation, this content provides a clear, structured approach to best-practice design. By understanding and applying these concepts, teams can ensure their scoring solutions are efficient, scalable, and investigator-friendly — ultimately driving better outcomes from their Quantexa deployments. Make sure you're signed in to the Commnity to access the articles. Articles in the series: Scoring Concepts: Run Date Scoring Concepts: In-Scope Customers Scoring Concepts: Scoring Levels and Scorecards Scoring Concepts: Scenarios & Risk Factors Scoring Concepts: Alerting and Re-alerting Scoring Concepts: Write-Once Steps Scoring DAG Design in Assess
Scoring Concepts: Scenarios & Risk Factors
This guide explains how to differentiate between Scenarios and Risk Factors. At Quantexa, we aim to give our clients meaningful Alerts. We focus on those that pose the highest risk to investigators. This article targets Business Analysts, Business End Users, and Subject Matter Experts (SMEs). It focuses on individuals engaged in risk assessment, decision-making, or developing Scores. When readers grasp these distinctions, they can design Scores and Scorecards better. This helps us show only the most relevant risk profiles to investigators. Read the full article for: Definition of Scenarios and Risk Factors Best Practices for Setting Scenarios vs Risk Factors How Scenarios and Risk Factors affect Alerting and Re-Alerting Using Detection Packs 4. Scoring Concepts: Scenarios & Risk Factors - Quantexa Community This article explains how to differentiate between Scenarios and Risk Factors. At Quantexa, we aim to give our clients meaningful Alerts. We focus on those that pose the highest risk to investigators. This article targets Business Analysts, Business End Users, and Subject Matter Experts (SMEs). It focuses on individuals…Scoring Concepts: Network Generation & Design
Learn Effective Network Generation & Design Explore the essential concepts and tools behind network generation in Scoring Concepts: Network Generation & Design. Networks are central to Quantexa solutions, offering context to complex datasets through nodes and edges. Nodes can represent either: Documents, a hierarchical representation of raw data, or Entities, real-world concepts like individuals, businesses, or accounts created through Entity Resolution. This article covers: Network Design and Scoring: How to create networks that meet your project needs. Network Types: The differences between Natural Networks and Ego-centric Networks. Graph Script DSL Expansion Tips: Practical advice for generating high-quality ego-centric networks. For additional guidance, check out Graph Scripting Best Practices, or log in now to read the full article: 1. Scoring Concepts: Network Generation & Design - Quantexa Community This article introduces some concepts, tools and tips on the topic of network generation. By the end, you should understand which tool you would use to generate networks for your project and how to ensure the network output will cover the scores you have in your project. Introduction Networks are at the core of any…
Scoring Concepts: Network Scoring
We can feed networks derived in Graph Scripting DSL into a Scoring pipeline to derive information and insight in the form of network-based scenarios. This article outlines: Concepts and approaches available for batch Network Scoring, including extracting information from graphs, testing, and debugging. Available tools and methods for performing network analysis with Assess. Read the article (login required): 2. Scoring Concepts: Network Scoring - Quantexa Community This article outlines the concepts and approaches available for batch Network Scoring, including extracting information from graphs, testing, and debugging. This article also highlights the available tools and methods for performing network analysis. The below steps are applicable for Assess only. Introduction We can feed…
Scorecard Tuning📋
Scoring is a key part of the Quantexa Platform, and to maximise effectiveness needs to be tuned in an ongoing iterative process. There are various elements in the scoring process that can be tuned, and this article serves as a guide as to methods that can be employed to do so. Read the full article (login required): 1. Scorecard Tuning - Quantexa Community Introduction Scoring is a key part of the Quantexa Platform, and to maximise effectiveness, needs to be tuned in an ongoing iterative process. There are various elements in the scoring process that can be tuned, and this article will serve as a guide as to methods that can be employed to do so. What can be Tuned? There are…
New guide 📖 Scoring Concepts: Write-Once Steps
Discover how to efficiently use Write-Once Steps in the Assess framework for data transformation. This detailed guide complements the Write-Once Steps documentation and helps you determine when to apply Write-Once Steps effectively in both Batch and Dynamic Scoring contexts. Key topics covered: The potential cost of using the wrong method When to use Write-Once Steps vs. Logical Sources Strategies for scoring networks in Batch (SparkScoringContext) and Dynamic (DynamicScoringContext) environments Gain a deeper understanding of how to avoid duplicating logic across contexts and streamline your data engineering workflows. Read the full article (login required) to explore practical scenarios and best practices for scoring networks with Write-Once Steps: 5. Scoring Concepts: Write-Once Steps - Quantexa Community This article serves as an extension of the Product documentation of Write-Once Steps and provides a guide on which situation should the Write-Once Steps be used. Introduction The Write-Once Step is a data transformation step in the Assess framework, which is executable in both Batch and Dynamic contexts, meaning you do not…
FinCrime Detection Pack 0.4 is now available
We are excited to announce version 0.4 of our FinCrime Detection Pack is now available in Early Access. This release introduces new features that will increase flexibility, improve score coverage and optimise score configuration to better capture desired behaviours, characteristics and events. This builds on the functionality released in version 0.3 of the FinCrime Detection Pack. Feature Highlights: You can now apply score logic on a targeted subset of transactions to help you uncover more specific underlying patterns that might otherwise be overlooked. You can now configure transaction score parameters based on the segment a score subject belongs to. This allows you to account for differences and ensure that you are capturing the behaviours and events you’re interested in. You are now enabled to select from a range of appropriate Event Windows to ensure that a score is targeting the desired behaviour or event. Target new risks with additional Score Types You can read more about the release in Detection Pack 0.4 Release (login required) For full details of the release, including compatible Quantexa Platform versions and minor enhancements, please see the Quantexa Documentation site. Release notes Migration guideScoring Concepts: Alerting and Re-alerting 📖
Alerting is the name for the process that comes after Scorecard creation and before Task loading into a Quantexa Deployment. Alerting decides which Subjects in the Scorecard output should alert to the end-users. Re-Alerting is an Alerting process that occurs after the first Alerting cycle, when new Scorecard data becomes available. Re-alerting logic compares a Subject's Scorecard output with all previous Scorecard outputs. The aim of this process is to ensure that there is new material risk that an Investigator would like to review. It is strongly encouraged that all deployments with Batch Scoring implement Alerting. Read about the Alerting Framework, Alerting Threshold, and Score Types in Scoring Concepts: Alerting and Re-alerting. Read the full article (login required): 4. Scoring Concepts: Alerting and Re-alerting - Quantexa Community This article builds upon the concepts introduced in Scoring Concepts: Scoring Levels and Scorecards. Alerting is the name for the process that comes after Scorecard creation and before Task loading into a Quantexa Deployment. Alerting decides which Subjects in the Scorecard output should alert to the end-users. Re-Alerting…
Detection Packs 0.3
What are Detection Packs? Detection Packs are a Scoring solution that enables projects to progress more quickly from resolved Entities and generated egocentric Networks to Alerts ready for investigation. Why are Detection Packs important? Using Detection Packs avoids the time and cost associated with writing the same Scores and Pipelines multiple times on different projects. This out-of-the-box Scoring solution provides a set of baseline Scores, so individual projects can focus on developing the complex Scores that match their specific needs. What is in this Detection Packs 0.3 Release? This release adds many new Scores to the FinCrime Detection Pack, and generally improves product maturity with new quality-of-life features. You can read more about the benefits of this Detection Pack release in @Greg_Jones's article (log in required): Detection Packs 0.3 Release For full details of the release, including all of the scores available, compatible Quantexa Platform versions and minor enhancements, please see the Quantexa Documentation site (log in required).
Welcome to Quantexa 2.5 | 2.5.0 Release Announcement
We are pleased to announce Quantexa 2.5! Read below for a few exciting highlights. Stream Updates to the Entity Store The Entity Store can now be updated with a streamed ingest of new Documents, and creates a change log describing how the Entity population has changed. In combination with the ability to query the full population of resolved Entities, this update enables near real-time access to the most up-to-date view of your data. Why is this important? Users and downstream systems can now get the latest view of an Entity resolved by Quantexa, enabling business processes that need to access or act upon that update in near real-time - in a Master Data Management solution (MDM), for example - to do so. Deploy and Change Custom Scoring Pipelines through Configuration The addition of Scoring Extension Mode to the Assess Template Generation functionality helps simplify the process of setting up Scoring on a project. With the new Extension Mode, it is now possible to change and add new nodes to a custom Scoring model using configuration files. Why is this important? This significantly reduces the technical skills required for setting up the Scoring pipeline and makes the generation of a custom Scoring pipeline more flexible. Flexible Scorecards: Identify and Aggregate Insights Across Multiple Typologies Assess capabilities and helper functions have been added to support multiple Scorecards on the same level within one Scoring pipeline. Scores can contribute to one or more Scorecards and flexible alerting logic can be set up to include the outcome of multiple Scorecards. Why is this important? This enables the flagging of different types of risks or insights at the same level - for different typologies or different products, for example - and helps an investigator or analyst understand and act upon the full context of the data available. Tune Scorecards with QPython QPython utilities can now interact with Assess configuration files and Scoring pipelines, which simplifies the process of tuning a Scoring model, providing an easy way to conduct a what-if analysis. The interface, using pre-written Python Notebooks, calculates a set of the most common and useful metrics for tuning. The use of Jupyter Notebooks allows the export of the reports for inclusion in the wider model governance process. Why is this important? Scorecard tuning is one of the most important parts of model development, as the model must output the most relevant (e.g., risky or interesting) information for a specific use case. These utilities make the process of Scorecard tuning much more accessible, simple, and quick. It also makes sure that the model addresses the business need and risk appetite of the deployment. Other highlights Speed up and simplify deployment of Explorer with no-code configuration; Merge and split Entities, and override Entity Attributes through the Entity Management Panel (e.g., for Master Data Management solutions); Integrate with Kafka streaming typologies more easily. Share your thoughts on this release in our poll: Which feature of Quantexa 2.5 are you most excited for? To receive updates on every release, be sure to follow the Release Announcements topic: Want to learn more? Check out the Release Notes on the Quantexa Documentation site. If you are unable to access the Documentation site, please get in touch with your Quantexa point of contact or the Community team at community@quantexa.com.
