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Risk Modeling

29 articles · Page 1 of 1
Software Engineering 3.0 Era
Software Engineering 3.0 Era
Aug 3, 2026 · Industry Insights

Why Regression Testing No Longer Looks Like Regression: Test Engineers’ AI‑Driven Reality Check

Interviews with test engineers across internet, telecom, and tool‑software firms reveal that AI is automating routine test case creation and script generation, pushing developers toward full‑stack roles and shrinking manual testing work, while the remaining value lies in human judgment, risk modeling, and evidence‑based verification.

AIIndustry SurveyJudgment
0 likes · 9 min read
Why Regression Testing No Longer Looks Like Regression: Test Engineers’ AI‑Driven Reality Check
FunTester
FunTester
May 13, 2026 · Artificial Intelligence

How to Become an AI Quality Architect: A Practical Guide

The article explains how quality should be designed rather than merely measured, contrasts traditional QA with modern Quality Engineering, outlines the AI‑driven challenges and required metrics, and provides a concrete career roadmap for aspiring AI Quality Architects.

AICost of QualityQuality Architect
0 likes · 9 min read
How to Become an AI Quality Architect: A Practical Guide
Chen Tian Universe
Chen Tian Universe
Apr 28, 2026 · Industry Insights

A Beginner’s Guide to Payment Risk Control: All You Need in One Article

This article systematically introduces payment risk‑control fundamentals, covering core terminology, risk categories, black‑market attack methods, system architecture, data and feature pipelines, list management, rule engines, modeling techniques, decision flows, key performance metrics, compliance requirements, and operational best practices.

Risk Modelingblack market attackscompliance
0 likes · 34 min read
A Beginner’s Guide to Payment Risk Control: All You Need in One Article
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Sep 29, 2025 · Artificial Intelligence

AlphaAgents: BlackRock’s LLM‑Driven Multi‑Agent System for Stock Portfolio Management

AlphaAgents introduces a role‑based multi‑agent framework—Fundamental, Sentiment, and Valuation agents—leveraging LLMs to analyze 10‑K reports, news, and price data, with a debate mechanism via Microsoft AutoGen; experiments on 15 tech stocks show superior cumulative returns and Sharpe ratios under risk‑neutral and risk‑averse settings compared to single‑agent baselines.

AlphaAgentsFinancial AILLM
0 likes · 10 min read
AlphaAgents: BlackRock’s LLM‑Driven Multi‑Agent System for Stock Portfolio Management
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Sep 26, 2025 · Artificial Intelligence

Paper Summaries: Recent AI-Driven Finance Research (Sep 20‑26, 2025)

This article presents concise English summaries of four recent arXiv papers that explore AI-driven trading frameworks, dual‑view risk‑relation identification from 10‑K filings, multimodal language models for financial forecasting, and credit‑spread prediction enhanced by non‑financial data, highlighting their methods, datasets, and performance results.

AICredit SpreadsMultimodal
0 likes · 9 min read
Paper Summaries: Recent AI-Driven Finance Research (Sep 20‑26, 2025)
Data Party THU
Data Party THU
Sep 21, 2025 · Artificial Intelligence

How Delphi-2M Uses Generative Transformers to Predict Over 1,000 Diseases

A new AI system called Delphi-2M, built on an enhanced generative‑transformer architecture and trained with UK Biobank data, can forecast the risk of more than a thousand diseases up to twenty years in advance, achieving an average AUC of 0.67 in external validation while offering explainable, extensible predictions for personalized health.

AIDelphi-2MDisease Prediction
0 likes · 5 min read
How Delphi-2M Uses Generative Transformers to Predict Over 1,000 Diseases
Volcano Engine Developer Services
Volcano Engine Developer Services
Jul 16, 2025 · Information Security

Securing the Model Context Protocol (MCP): Volcanic Engine’s End‑to‑End Approach

This article explains how Volcanic Engine safeguards the Model Context Protocol (MCP) throughout its lifecycle, detailing MCP fundamentals, core components, a step‑by‑step interaction example, seven major security risks, official design principles, and a comprehensive security architecture covering admission control, native design, and runtime protection.

LLMMCPModel Context Protocol
0 likes · 21 min read
Securing the Model Context Protocol (MCP): Volcanic Engine’s End‑to‑End Approach
DataFunSummit
DataFunSummit
Mar 22, 2024 · Artificial Intelligence

Risk Control Model Construction for Online Small Loans: Pre‑loan, In‑loan, Post‑loan and Monitoring

This article presents a comprehensive overview of risk control model building for online small‑loan scenarios, covering pre‑loan, in‑loan and post‑loan stages, the associated data pipelines, model deployment strategies, optimization attempts, and monitoring frameworks to ensure accuracy, stability and effectiveness.

Credit ScoringData PipelineMonitoring
0 likes · 16 min read
Risk Control Model Construction for Online Small Loans: Pre‑loan, In‑loan, Post‑loan and Monitoring
Data Thinking Notes
Data Thinking Notes
Jan 16, 2024 · Fundamentals

Building Comprehensive Risk Feature Portraits for All Loan Stages

This article explains how to construct risk control feature portraits across four key scenarios—marketing, pre‑loan, in‑loan, and post‑loan—by selecting appropriate data dimensions, describing usable customer, behavior, and ID‑linked data, and illustrating each portrait with visual examples to guide accurate risk assessment.

Risk Modelingcredit riskdata dimensions
0 likes · 9 min read
Building Comprehensive Risk Feature Portraits for All Loan Stages
Model Perspective
Model Perspective
Jan 14, 2024 · Fundamentals

How Graph Theory Can Predict Global War Risks: A Quantitative Model

This article presents a graph‑theory based mathematical model that treats nations as nodes and their relationships as weighted edges, using centrality metrics to quantitatively assess and forecast potential war risks, illustrated with a 2024 case study of key global regions and an adjacency matrix.

International RelationsRisk Modelingcentrality metrics
0 likes · 9 min read
How Graph Theory Can Predict Global War Risks: A Quantitative Model
DataFunTalk
DataFunTalk
May 28, 2023 · Artificial Intelligence

Applying External Data in Consumer Credit Risk Management: Framework, Evaluation, and Joint Modeling

This article presents a comprehensive overview of using external data in consumer credit risk management, covering the risk operating framework, data types, challenges of data integration, evaluation methods, joint modeling techniques, and practical solutions to improve model performance and business outcomes.

Risk Modelingcredit riskdata evaluation
0 likes · 18 min read
Applying External Data in Consumer Credit Risk Management: Framework, Evaluation, and Joint Modeling
DataFunTalk
DataFunTalk
Jan 2, 2023 · Artificial Intelligence

Tail Traffic Modeling and Data‑Driven Risk Strategies at 360 Shuke

This article presents 360 Shuke's practical approach to modeling low‑volume (tail) credit traffic using accumulated data, covering the characteristics of tail traffic, sample expansion under low approval rates, timeliness‑based data clustering, and ranking optimization for high‑quality head customers.

Data ClusteringModel OptimizationRisk Modeling
0 likes · 19 min read
Tail Traffic Modeling and Data‑Driven Risk Strategies at 360 Shuke
DataFunSummit
DataFunSummit
May 23, 2022 · Artificial Intelligence

Applying Graph Machine Learning for Intelligent Anti‑Fraud: Models, Algorithms, and Real‑World Applications

This article explores how graph machine learning can be leveraged for intelligent anti‑fraud, covering business background, common fraud models and graph algorithm principles, practical deployment of graph algorithms, challenges in fraud modeling, and future research directions.

Graph AlgorithmsGraph Machine LearningRisk Modeling
0 likes · 20 min read
Applying Graph Machine Learning for Intelligent Anti‑Fraud: Models, Algorithms, and Real‑World Applications
DataFunTalk
DataFunTalk
Mar 18, 2022 · Artificial Intelligence

Alternative Data Mining: From 19th‑Century Cholera Mapping to Modern AI‑Driven Risk Modeling

This talk reviews the concept of alternative data, illustrates its early use in John Snow's cholera map, explores contemporary AI‑powered systems such as IBM's Debater and satellite‑based poverty estimation, and presents the speaker's own research on using unconventional data for financial‑market risk detection and prediction.

Artificial IntelligenceRisk ModelingSatellite Imagery
0 likes · 14 min read
Alternative Data Mining: From 19th‑Century Cholera Mapping to Modern AI‑Driven Risk Modeling
G7 EasyFlow Tech Circle
G7 EasyFlow Tech Circle
Nov 24, 2021 · Artificial Intelligence

How G7 Tackles Truck Underwriting Risk: Modeling Challenges & Solutions

This article outlines G7's early-stage exploration of truck underwriting risk modeling, detailing data foundations, modeling objectives, key challenges such as target diversity and claim randomness, and proposes practical solutions across data sampling, feature engineering, model structure, and regionalization to improve risk assessment.

Risk Modelingmachine learningtruck insurance
0 likes · 17 min read
How G7 Tackles Truck Underwriting Risk: Modeling Challenges & Solutions
DataFunSummit
DataFunSummit
Sep 20, 2021 · Artificial Intelligence

Graph Algorithm Applications in Douyu Live Stream Anti‑Cheat: Architecture, Evolution, Modeling, and Case Studies

This article explains how Douyu leverages graph algorithms for live‑stream traffic anti‑cheat, detailing the platform’s risk scenarios, the overall graph architecture, its evolution, modeling workflow, practical case studies, and the resulting improvements in fraud detection and interpretability.

AIGraph AlgorithmsRisk Modeling
0 likes · 16 min read
Graph Algorithm Applications in Douyu Live Stream Anti‑Cheat: Architecture, Evolution, Modeling, and Case Studies
DataFunSummit
DataFunSummit
Jul 31, 2021 · Artificial Intelligence

Credit Risk Strategies: From Rule‑Based Scoring to Machine Learning Models

This article presents a comprehensive overview of credit risk control strategies, covering industry background, traditional scoring‑card development, data integration, feature engineering, model evaluation, rate and limit optimization, and advanced machine‑learning approaches for loan underwriting.

Financial AnalyticsRisk ModelingScoring
0 likes · 11 min read
Credit Risk Strategies: From Rule‑Based Scoring to Machine Learning Models
DataFunTalk
DataFunTalk
Dec 8, 2020 · Artificial Intelligence

Financial Big Data Risk Control Models: Techniques, Applications, and COVID‑19 Challenges

This article presents a comprehensive overview of financial big‑data risk control models at Du Xiaoman, covering traditional scoring cards, AI‑driven time‑series and text processing, graph‑based networks, model interpretability, probability calibration, stability analysis, and the specific challenges introduced by the COVID‑19 pandemic.

Artificial IntelligenceBig DataCredit Scoring
0 likes · 14 min read
Financial Big Data Risk Control Models: Techniques, Applications, and COVID‑19 Challenges
DataFunTalk
DataFunTalk
Jun 22, 2020 · Artificial Intelligence

Ctrip's Automated Iterative Anti‑Fraud Modeling Framework for Payment Risk

The article describes Ctrip's payment fraud risk characteristics, a comprehensive automated iterative anti‑fraud model framework—including variable system, GAN‑augmented sample generation, RNN behavior encoding, and tree‑based classifiers—and demonstrates how this approach restores recall performance compared with traditional static models.

GaNRNNRisk Modeling
0 likes · 12 min read
Ctrip's Automated Iterative Anti‑Fraud Modeling Framework for Payment Risk
DataFunTalk
DataFunTalk
Sep 2, 2019 · Artificial Intelligence

Credit Risk Strategies: Data, Rules, and Model Development for Consumer Lending

This article presents a comprehensive overview of consumer credit risk management, covering industry background, traditional scoring‑card and machine‑learning model development processes, risk‑rate and limit strategies, rule effectiveness diagnostics, and advanced model‑optimization techniques to improve underwriting performance and cost efficiency.

Risk Modelingconsumer lendingcredit risk
0 likes · 10 min read
Credit Risk Strategies: Data, Rules, and Model Development for Consumer Lending
DataFunTalk
DataFunTalk
Aug 22, 2019 · Artificial Intelligence

End‑to‑End Group Risk Perception Modeling: From Requirement Mining to Deployment

This article presents a comprehensive workflow for group risk perception, covering business requirement mining, data acquisition and understanding, feature engineering, model training and evaluation, deployment, and practical user applications, with detailed objectives, methods, and deliverables for each stage.

Model deploymentRisk Modelingdata mining
0 likes · 11 min read
End‑to‑End Group Risk Perception Modeling: From Requirement Mining to Deployment
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 15, 2019 · Artificial Intelligence

How Auto Risk Transforms Behavior Sequence Data with Unsupervised Pre‑Training

This article introduces Auto Risk, a deep‑learning risk model for behavior‑sequence data that leverages unsupervised pre‑training with proxy tasks, details its convolution‑attention encoder, demonstrates significant gains across multiple business scenarios, and highlights its strong small‑sample and analogy capabilities.

Risk ModelingUnsupervised Learningbehavior sequence
0 likes · 20 min read
How Auto Risk Transforms Behavior Sequence Data with Unsupervised Pre‑Training
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 30, 2019 · Artificial Intelligence

Auto Risk: Pretraining Deep Models on Unlabeled Behavior Sequences

This article introduces Auto Risk, a behavior‑sequence deep‑learning framework that uses unsupervised pre‑training with proxy tasks to learn universal feature representations from massive unlabeled data, achieving significant gains in risk‑control scenarios, improving AUC, supporting multi‑scene generalization and small‑sample learning.

Risk ModelingUnsupervised Learningbehavior sequence
0 likes · 20 min read
Auto Risk: Pretraining Deep Models on Unlabeled Behavior Sequences
DataFunTalk
DataFunTalk
Jun 12, 2019 · Artificial Intelligence

Credit Scoring Cards vs Machine Learning in Financial Risk Control: Comparative Analysis and Practical Applications

The article compares traditional credit‑scoring‑card models with modern machine‑learning approaches for financial risk control, detailing feature selection criteria, non‑linear handling, data characteristics, practical ML techniques, large‑scale modeling challenges, and summarizing insights for future development.

Risk Modelingfinancial riskmachine learning
0 likes · 14 min read
Credit Scoring Cards vs Machine Learning in Financial Risk Control: Comparative Analysis and Practical Applications
DataFunTalk
DataFunTalk
Apr 17, 2019 · Artificial Intelligence

Evolution of Ctrip Financial Risk Control Models: From Data Platform to AI‑Driven Scoring and Anti‑Fraud Systems

This report details Ctrip Financial's end‑to‑end risk control development, covering business overview, a three‑layer data platform, the progression of credit scoring and anti‑fraud models from rule‑based to advanced AI techniques, and the evaluation, monitoring, and social‑network‑based fraud detection strategies employed.

Big DataFinancial AIRisk Modeling
0 likes · 16 min read
Evolution of Ctrip Financial Risk Control Models: From Data Platform to AI‑Driven Scoring and Anti‑Fraud Systems
AntTech
AntTech
Sep 7, 2018 · Artificial Intelligence

How Alipay Leverages LSTM to Strengthen Mobile Payment Fraud Detection

This article explains how Alipay combats the surge of mobile payment fraud by upgrading its risk‑identification system with deep‑learning techniques, modeling victim and fraudster behavior sequences using LSTM, and integrating the resulting scores into existing models to achieve a measurable increase in detection coverage.

LSTMRisk Modelingbehavior sequence
0 likes · 11 min read
How Alipay Leverages LSTM to Strengthen Mobile Payment Fraud Detection