Bid Aggregation System for Securities Auctions
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Solution Overview
Problem
In securities auctions, existing systems face challenges in efficiently compiling and analyzing large volumes of bids from potential investors in a timely and reliable manner, particularly in well-publicized offerings where millions of bids are submitted, necessitating a robust and reliable bid intake system.
Innovation Solution
An auction management system that includes a data stripper to segment bids by investor ID and a bid aggregation system for hierarchical aggregation, combined with an analytics system for real-time analysis, using indexed memory structures to facilitate quick data retrieval and processing, and detect manipulative bids.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional bid compilation systems are used to handle millions of bids, then the system can process the bids, but the processing time becomes excessively long and the system reliability decreases
Solution Approach 1:
The patent divides the bid data into multiple segments or partitions, each handled by separate processing units. This segmentation allows parallel processing of bid data, significantly improving processing speed while maintaining system reliability through distributed processing. Each segment can be processed independently, reducing the burden on any single system component.
Solution Approach 2:
The patent implements a hierarchical aggregation structure where bid data is aggregated at multiple levels - from individual bid segments to larger aggregated groups. This nested structure enables efficient summarization and analysis of bid data at different granularities, improving both processing speed and reliability by organizing data in a manageable hierarchy.
2Productivity
If all bid data is processed in a single aggregation pass, then the processing logic is simple, but the processing time becomes unacceptably long for millions of bids
Solution Approach 1:
The aggregation process is divided into multiple passes or stages, each handling specific aspects of bid data. This segmented approach allows the system to process different portions of bid data in parallel, improving processing speed while keeping each individual aggregation pass relatively simple and manageable.
Solution Approach 2:
The patent introduces additional dimensions to the aggregation process by implementing hierarchical levels of aggregation. Instead of a single linear pass, the system aggregates data across multiple dimensions and levels, enabling faster processing through parallel operations while managing complexity through structured organization.
3Measurement precision
If bid data is stored in a conventional format, then data storage is simple, but real-time analysis and retrieval become inefficient
Solution Approach 1:
The patent pre-processes and organizes bid data into optimized storage formats and structures before actual analysis is needed. This preliminary organization includes creating aggregated summaries and structuring data for efficient retrieval, allowing real-time analysis to proceed quickly without sacrificing accuracy, as the data is already prepared in an optimal state.
Data Source
AI summary
Systems and methods for compiling and analyzing bids from bidders in an auction offering of securities by an issuing company are disclosed. A data striper stripes bid data compiled from the bids of potential investors into a plurality of stripes according to an algorithm and a bid aggregation system aggregates the bid data in the stripes. The bid aggregation system may perform a first-level aggregation on the bid data in the data stripes for combinations of a plurality of attributes related to the bid data and/or a second-level aggregation based on the first-level aggregation. The auction management system may further comprise an analytics system for analyzing the aggregated bid data. The analytics system may receive user requests for analysis of the bid data, perform the analysis in real time based on the user inputs, and serve the results of the analysis to the user.