Overview
Introduction
Fraud detection & prevention is a combination of tools, technologies and processes to identify and prevent dishonest activities. Fradulent behaviour results in financial losses, disruption in operations and often reputational damage.
In banking, this means spotting unusual transactions or behaviors that could point to scams like account takeovers or fake charges. For rewarded ads, fraud detection involves identifying bots pretending to be real users to steal rewards or fake ad clicks to drain advertiser budgets.
Fraud Detection Systems
The first step in combating fraud is to detect it. Fraud detection systems are usually of 2 types, depending on when the system does the detection
(Near) Real Time i.e. evaluating a transaction or an event very close to its actual occurence.
Post-Event or Historical analysis i.e. investigation of historical data to figure out anomalies.
Fraud Detection Techniques
Fraud detection systems use one or more of these techniques -
Rule-based Systems
Machine Learning Systems (AutoEncoders, GNNs etc)
The Canso Platform currently supports Rule based fraud detection systems. Users can easily perform batch & real-time feature engineering, design workflows and define rules within the workflow leveraging features. Real world workflows include detecting Account takeover, UPI Fraud, Money Mules, Bot Fraud and more.
Each workflow consists of certain rules. For the Account Takeover Workflow, these could be
login from a new device and country or from a high risk device
VPN detection
No. of failed login attempts in the last 3 hours is greater than 10 or No. of failed login attempts in the last 1 hours is greater than 5
No. of attributes changes in a user's profile/account settings over the last 12 hours exceeds 3
behavioral anomaly such as 2x increase in typing speed or click velocity.
Canso's Python Client makes it easy for users to develop fraud detection solutions with seamless access to the following key services -
Workflow Management: Create worfklows and define rules to detect fraud.
Feature Management: Develop & manage features, i.e. aggregated historical behavioral data, for use in rules and decision-making.
Risk Decisioning Engine: Deploy workflows as configurable, high performance applications that can evaluate incoming transactions in sub-100 millisecond latency at scale.
An exciting release we are working hard to ship in the next couple of months is to build AI agents so that end users do not have to worry about writing code to define rules and workflows. Using simple natural language, you can express business rules, simple and complex, and the AI will figure out the rest. The AI agent is designed to respect and value human inputs and will prioritise human feedback at different stages.
Canso Fraud Management Architecture
Dive Right In
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