Problem Statement Area: Risk, Fraud, and Regulatory Intelligence Copilot
An AI-native procurement fraud and velocity detection platform built 100% inside the Snowflake Data Cloud using a zero-data-movement architecture. Developed natively via Snowlit, this solution completely eliminates data exfiltration and leakage vectors by keeping all data parsing, regulatory vector matching, and LLM text generation entirely within your secure database perimeter.
CRITICAL ACCESS INFO: To bypass platform credit limitations and fully evaluate Environment 2, a secure
JUDGE_ACCESS_KEYhas been injected into Slide 1 of our presentation pitch deck.Please open the Presentation Slide PDF uploaded on the Hack2Skill portal to retrieve this key and unlock all advanced workspace features in Environment 2.
- 🎬 Walkthrough Video: https://youtu.be
- ❄️ Environment 1 (Primary Production): Native App Listing: https://snowflake.com
- Note: Built natively inside the Snowflake Data Cloud to securely leverage high-performance analytical views and Snowflake Cortex AI within the data perimeter.
- ☁️ Environment 2 (External Public Staging): GitHub Streamlit App Listing: https://streamlit.app
- *Note: Deployed to Streamlit Community Cloud for public web evaluation using encrypted key-pair backend routing.
- 📋 Presentation Slide: [Uploaded directly as a PDF to the Hack2Skill portal. Environment 2 workspace features are unlocked securely via the injected
JUDGE_ACCESS_KEYin Slide 1]
The architecture operates strictly inside the Snowflake Data Cloud Perimeter (RISK_COPILOT_DB). The frontend interface uses granular role-locking, routing session states through active user master data records before granting analytical or action capabilities.
graph TD
%% Base Styling
classDef snowflake fill:#1d94d2,stroke:#0f4c6c,stroke-width:2px,color:#fff;
classDef security fill:#e056fd,stroke:#68217a,stroke-width:2px,color:#fff;
classDef app fill:#ff7675,stroke:#b12e2e,stroke-width:2px,color:#fff;
classDef data fill:#55efc4,stroke:#00b894,stroke-width:2px,color:#333;
%% Components
User([👤 User / Compliance Auditor])
subgraph UI [Snowlit Workspace - streamlit_app.py]
AuthGate[🔒 Identity Authentication Gate]
Tab1[📊 Tab 1: Operational Dashboard]
Tab2[💬 Tab 2: Conversational CoCo Copilot]
Tab3[🔍 Tab 3: Account Directory Lookup]
Tab4[🎮 Tab 4: Remediation & Actions Console]
Tab5[🔐 Tab 5: IAM Security & Access Controls]
end
subgraph SF [Snowflake Data Cloud Perimeter - RISK_COPILOT_DB]
direction TB
subgraph Core [COMPLIANCE_CORE Schema]
T1[(1. IDENTITY_ACCESS_MASTER)]
V1{{"👁️ COMPLIANCE_AUDIT_STREAM (View)"}}
T2[(2. AML_REGULATORY_POLICIES)]
T3[(3. ACCOUNT_MASTER)]
T4[(4. TRANSACTION_LEDGER)]
T5[(5. REMEDIATION_LOG)]
T6[(6. SANCTIONS_WATCHLIST)]
T7[(7. TRADE_SHIPMENTS)]
end
subgraph SnowparkEngine [Snowpark Engine & AI - copilot_engine.py]
SignalDet[Signal Detection Pipeline]
VectorSim[Cortex Vector Similarity e5-base-v2]
CortexLLM[Cortex LLM: llama3.1-70b]
RuleEng[Automated Enforcement Engine]
end
end
%% Interactions
User -->|Access System| AuthGate
AuthGate -->|Validates Active Session| T1
%% Operational Audit Flow
Tab1 -->|Trigger Pipeline| SignalDet
SignalDet <-->|Filter Min Amount & Risk Signals| V1
SignalDet -->|Semantic Context| VectorSim
VectorSim <-->|Cosine Similarity Search| T2
VectorSim -->|Augmented Context Payload| CortexLLM
CortexLLM -->|Generates Markdown STR| Tab1
%% Conversational CoCo Flow
Tab2 -->|Natural Language Context Lookup| CortexLLM
CortexLLM <-->|Session Snapshot Data| T3
%% Directory Lookup Flow
Tab3 -->|Profile Deep Dive| T3
Tab3 -->|Historical Auditing| T4
%% Remediation Log & Automation Flow
Tab4 -->|Write Lock Updates & Justifications| T5
Tab4 -->|Deploy Hardcoded Rules| RuleEng
RuleEng <-->|Scan Signals & Compute Overrides| T4
RuleEng <-->|Cross Reference Country Codes| T6
%% IAM Security Administration Flow
Tab5 -->|Create Users & Toggle Activity Status| T1
%% Apply Styles
class SF,Core,T1,V1,T2,T3,T4,T5,T6,T7 snowflake;
class AuthGate security;
class UI,Tab1,Tab2,Tab3,Tab4,Tab5 app;
class SnowparkEngine,SignalDet,VectorSim,CortexLLM,RuleEng data;
For quick judging evaluation, the system features a passwordless, biometric-style IAM mapping lookup.
Instructions for Judges:
- Simply select any Username from the select box dropdown menu.
- The system will automatically fetch that user's identity matrix. Leave the masked password as-is.
- Click the primary **🔓 Authenticate & Enter System ** button to enter the workspace!
The application maps specific interfaces dynamically based on the verified CLEARANCE_LEVEL row entry assigned to the user inside IDENTITY_ACCESS_MASTER:
| Role | Clearance Level | Permitted Views & Actions | System Restrictions |
|---|---|---|---|
| JUNIOR_CLERK | L1_BASIC |
View basic operational dashboard metrics & active anomalies. | Cannot query CoCo, view detailed profiles, lock accounts, or manage users. |
| COMPLIANCE_OFFICER | L2_ELEVATED |
Operational Dashboard + Conversational CoCo room chat + Customer 360 lookup. | Blocked from executing manual remediations, auto-rules, or IAM adjustments. |
| PRINCIPAL_PCO | L3_RESTRICTED |
All functional views + Execute manual containment protocols + Deploy automated rules. | Restricted from adding/managing system users or altering system clearancies. |
| SYSTEM_ADMIN | L4_FULL_ACCESS |
Complete system access. Manage IAM table, append records, toggle user activity statuses. | None — Unrestricted Account Administrator Access. |
Runs a multi-tier risk calculation pipeline powered by Snowpark analytics:
- Signal Detection: Filters out anomalies from
COMPLIANCE_AUDIT_STREAM(View) based on an interactive cross-border amount slider, matching high-impact criteria (IS_PEP, suspended flags, velocity warnings). - Dynamic Risk Scoring: Programmatically builds a real-time risk profile using geographic target parameters (e.g., scoring adjustments for tax havens like
CHorKY). - Semantic Policy Extraction: Executes a native Snowflake
VECTOR_COSINE_SIMILARITYsearch queryingAML_REGULATORY_POLICIESusing thee5-base-v2embedding engine to surface matching legal context. - Automated STR Assembly: Pipelines structured data and unstructured legal fragments directly into Cortex
llama3.1-70bto build a production-grade markdown Suspicious Transaction Report (STR) complete with metric summary cards and charts.
An interactive natural language compliance assistant. CoCo matches account mentions (e.g., searching for numeric patterns or strings like ACC_101) to parse details out of the ACCOUNT_MASTER layout instantly. If specific key phrases regarding "status" or "locks" are queried, CoCo references active states from the remediation log; general compliance prompts route out to a context-augmented Cortex LLM engine.
Exposes a comprehensive Customer 360 profile registry using data from ACCOUNT_MASTER. System users can browse demographic parameters, PAN numbers, Import Export Code (IEC) fields, GSTIN registrations, and historical transactional logs from the TRANSACTION_LEDGER. Security Guard: If an account is currently marked with an ACTIVE_LOCK inside REMEDIATION_LOG, transaction histories are automatically masked to preserve audit integrity.
Allows direct database containment enforcement. Modifying an active account protocol to an unlocked state requires a mandatory compliance rationale and file upload attachment (PDF/images), appending audit traces directly to REMEDIATION_LOG. Includes the Automated Data Engine Rules runner which programmatically audits the workspace and processes system locks for high-risk targets:
- Rule 1 (Sanctioned Country Auto-Freeze): Immediate account lockdown if capital routes to countries flagged inside the
SANCTIONS_WATCHLIST(KP,IR,SY, orMM). - Rule 2 (PEP Tax Haven Lock): Immediate lockdown and
ENHANCED_EDDescalation if a Politically Exposed Person transfers funds to designated tax havens.
A secure simulator panel displaying active clearance configurations. When accessed by an L4_FULL_ACCESS administrator, it unlocks database insertion wrappers to register new users with SHA2 password hashes or toggle live operational access statuses inside IDENTITY_ACCESS_MASTER.