Automated Risk Assessment System Using Biometric Data Conversion
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Solution Overview
Problem
Current risk assessment processes face challenges in automating unstructured data conversion, handling non-standard data vocabulary, and adapting to complex policies, leading to suboptimal accuracy and increased fraud and criminal activity risks.
Innovation Solution
A computer-based system that includes a tracking module, information module, risk assessment module, and memory to record and analyze biographic and biometric information, detect changes, and evaluate risks using standardized vocabulary and algorithms to provide automated and accurate entity identification and risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual risk assessment processes are used, then accuracy rates improve, but productivity decreases and loss of time increases
Solution Approach 1:
The system enables automated self-assessment of risk by converting unstructured data into structured formats and using algorithms to automatically evaluate risks, eliminating the need for manual processing while maintaining accuracy through consistent application of assessment criteria
Solution Approach 2:
Manual mechanical assessment processes are replaced with automated computer-based systems that use data conversion algorithms and risk assessment algorithms to perform evaluations, significantly increasing productivity while maintaining measurement precision through standardized processing
2Productivity
If automated risk assessment processes are implemented, then productivity improves, but measurement precision deteriorates due to difficulty in converting unstructured data
Solution Approach 1:
A data conversion module acts as an intermediary between unstructured data sources and the risk assessment algorithm, automatically converting unstructured data into structured formats that can be processed automatically, thereby maintaining measurement precision while enabling high productivity
Solution Approach 2:
The system changes the state of data from unstructured to structured format through automated conversion processes, transforming parameters such as data organization, format, and structure to enable automated processing without losing information integrity or accuracy
3Ease of operation
If standardized data vocabulary is used, then ease of operation improves, but adaptability deteriorates due to inability to handle non-standard data semantics
Solution Approach 1:
The data conversion module is designed with universal functionality to handle multiple types of unstructured data sources and convert them into standardized formats, enabling the system to operate easily across different data types while maintaining adaptability through flexible conversion capabilities
4Adaptability or versatility
If manual data processing is used, then adaptability to complex policies improves, but loss of time increases and productivity decreases
Solution Approach 1:
The system performs preliminary actions by pre-configuring assessment parameters and algorithms to reflect complex policies, enabling automated processing that adapts to policy requirements without requiring manual intervention during actual risk assessment, thereby reducing processing time while maintaining adaptability
Data Source
AI summary
The invention describes systems and methods of determining an entity's identity and assessing risk related to the entity's identity using a computer. A computer-based system including a tracking module, an information module, a risk assessment module, and a memory is provided. The tracking module records encounters of the entity with the computer-based system. The information module gathers and detects changes in biographic information and biometric information relating to the entity's identity. The risk assessment module evaluates risks associated with the entity. The memory stores the information.