Machine Learning SAR Report Generation with Jurisdiction Mapping
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Solution Overview
Problem
Current systems for generating Suspicious Activity Reports (SARs) face challenges such as escalation inconsistency, SAR content inconsistency, varying reportable activities across jurisdictions, and time-consuming investigation processes, leading to inefficiencies in identifying and reporting suspicious activities.
Innovation Solution
The system employs machine learning to map labels to reportable activities across jurisdictions, generate template-based narratives, and apply natural language generation to prepopulate report forms, ensuring consistent and efficient SAR creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual investigation and SAR generation processes are used, then flexibility in handling different jurisdictions is maintained, but time consumption and inconsistency increase
Solution Approach 1:
The system performs preliminary actions by pre-defining jurisdiction mappings, report templates, and narrative structures before SAR generation is needed. When a case is identified, the system automatically retrieves and applies the appropriate pre-configured templates and mappings for the relevant jurisdiction, eliminating manual configuration time and ensuring consistent application of jurisdictional requirements across all SARs.
Solution Approach 2:
The system creates and maintains a library of standardized SAR templates and narrative patterns that can be copied and adapted for different jurisdictions. Instead of manually creating each SAR from scratch, the system copies appropriate templates based on jurisdictional requirements and populates them with case-specific data, ensuring uniformity while maintaining productivity.
2Ease of operation
If manual SAR filling is performed, then customization for different jurisdictions is possible, but time consumption increases
Solution Approach 1:
The system pre-configures jurisdiction-specific mappings, report templates, and narrative structures before SAR generation is needed. When a case requires SAR filing, the appropriate templates and mappings are automatically retrieved and applied, eliminating manual configuration time and ensuring consistent application of jurisdictional requirements.
Solution Approach 2:
The system enables self-service by automatically generating SARs using pre-configured templates and jurisdictional mappings. The system autonomously retrieves case data, applies the appropriate templates, and generates completed SARs without requiring manual intervention for each field, significantly reducing completion time while maintaining ease of operation through automated workflows.
3Reliability
If standardized templates are used for SAR generation, then consistency is improved, but adaptability to different jurisdictions may be reduced
Solution Approach 1:
The system segments SAR templates into modular components that can be independently configured for different jurisdictions. Each jurisdiction has its own set of template parameters, mappings, and narrative structures that can be selectively applied. This segmentation allows the system to maintain consistent template structures while adapting specific content and requirements to each jurisdiction's unique regulations.
Solution Approach 2:
The system creates universal template frameworks that can serve multiple jurisdictions through configurable parameters and mappings. The core template structure remains consistent across all jurisdictions, but the templates are designed to accommodate jurisdiction-specific requirements through parameterization, allowing a single template system to fulfill multiple jurisdictional needs.
4Adaptability or versatility
If multiple jurisdictions with different requirements are supported, then comprehensive coverage is achieved, but system complexity increases
Solution Approach 1:
The system segments jurisdictional configurations into separate, manageable modules in a centralized repository. Each jurisdiction has its own isolated set of mappings, templates, and parameters that can be independently configured, maintained, and updated without affecting other jurisdictions. This segmentation reduces complexity by organizing multiple jurisdictional requirements into discrete, manageable units.
Solution Approach 2:
The system introduces a centralized jurisdictional mapping repository as an intermediary layer between case data and SAR generation. This intermediary repository stores and manages all jurisdiction-specific configurations, templates, and mappings in a standardized format, mediating between the diverse requirements of multiple jurisdictions and the uniform SAR generation process, thereby simplifying complexity management.
Data Source
AI summary
The disclosure includes a system and method for receiving, using one or more processors, a case; mapping, using the one or more processors, a first label to one or more reportable activities in one or more jurisdictions, the first label associated with the case; prepopulating, using the one or more processors, one or more reports, the one or more reports reporting the one or more activities in the one or more jurisdictions; generating, using the one or more processors, a template-based narrative, wherein the template is based on the first label, the first label associated with a first category of activities; generating, using the one or more processors, a natural language narrative by applying natural language generation associated with the first category of activities to the template-based narrative; and prepopulating, using the one or more processors, a form field with the natural language narrative.