Introducing Hakkōda’s Cortex-Powered Trade Alert Intelligence Platform

A Snowflake-Native Architecture That Keeps Data Secure 

Most traditional surveillance tools depend on moving sensitive trade data into external systems. This creates unnecessary complexity, cost, and risk. 

 Our approach is different. The entire Trade Alert Intelligence workflow runs directly inside Snowflake. This includes alert ingestion, classification, scoring, reasoning, and distribution. Cortex inference is executed within the warehouse, which means: 

• No external ETL pipelines. 

• No duplicated data silos. 

• No additional compliance exposure. 

• Unified governance, lineage, and access control. 

By keeping all data in one controlled and auditable environment, firms gain both a stronger compliance posture and significantly simplified operations. 

Key Capabilities of the Platform

1. Alert Ingestion and Pre-Filtering

The platform processes high volumes of raw trade activity and transforms them into structured alert records. Custom logic identifies relevant behavioral patterns such as rapid cancellations, large order imbalances, or repetitive trading sequences. 

This pre filtering stage reduces noise before any AI classifier is applied and creates a consistent, standardized dataset ready for risk scoring.

2. AI Driven Risk Classification

Each alert is enriched with AI based scoring using Cortex. For every record, the model generates: 

• A numerical risk score. 

• A classification of High, Medium, or Low risk. 

• A confidence score. 

• A sentiment or behavioral assessment. 

• A natural language explanation describing why the alert was categorized the way it was. 

This transforms raw metadata into real insight. High risk activity rises to the top, and repetitive low risk behavior no longer dominates the analyst queue.

3. Analyst Workspace for Exploration and Decision Making

We designed an interactive interface that allows analysts to work more efficiently and with better context. Key capabilities include: 

• Filtering by trader, ticker, alert type, and risk class 

• Comparing alert patterns by symbol or category 

• Visualizing alert distribution across time or behavior types 

• Clicking into any alert to view AI generated reasoning 

• Reviewing all relevant metadata in a consolidated view 

This workspace brings together everything an analyst needs to evaluate risk quickly and consistently.

4. Built In Feedback Loop for Continuous Learning

A major limitation of legacy surveillance tools is that they do not improve over time. Even if analysts repeatedly dismiss the same benign pattern, the system continues to flag it. 

With the Hakkoda platform, analysts can submit simple feedback that the model uses for continuous improvement. If an alert is misclassified, analysts can mark it as incorrect. These examples become part of a growing training set that refines future risk assessments. 

Over time, the platform reduces false positives even further and adapts to the firm’s trading behavior.

5. Full Transparency and Auditability

Regulators expect more detail and justification around surveillance decisions. They want to understand why alerts were escalated, why others were closed, and whether decisions were consistent across the team. 

The platform is designed for this reality. Every classification includes model scores, reasoning text, timestamps, analyst inputs, feedback history, and metadata used for evaluation. 

By extension, this fully expainable and audit-friendly design means that compliance officers gain reliable visibility into decision making, and the firm gains a stronger audit trail for both internal and regulatory reviews. 

The Business Impact: A Smarter and More Scalable Surveillance Operation 

Significantly Less Noise: By applying both pre filtering and AI driven classification, the platform reduces the number of alerts analysts must review. This allows compliance teams to focus on meaningful behavior instead of repetitive false positives. 

Faster and More Confident Decision Making: Analysts no longer need to piece together context from scattered systems. Scoring, explanations, and metadata appear together, leading to faster investigations and fewer unresolved alerts at the end of each cycle. 

A Stronger Compliance Posture: Transparency and explainability support the expectations of regulators across global markets. When decisions are clear, consistent, and auditable, the firm reduces operational risk and improves its ability to demonstrate effective supervision. 

A Future Proof Architecture: Because the solution is built entirely within Snowflake, it can scale across: 

• New asset classes.
• Additional trading desks.
• Cross regional surveillance. 
• Future rule changes or AI models.

There is no need for additional infrastructure or data movement.