US 2019/0164224 A1 · SYSTEMS AND USER INTERFACES FOR HOLISTIC, DATA-DRIVEN INVESTIGATION OF BAD ACTOR BEHAVIOR BASED ON CLUSTERING AND SCORING OF RELATED DATA

Abstract

Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria, rules, indicators, or scenarios so as to generate scores, reports, alerts, or conclusions that the analyst may quickly and efficiently use to evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a risky trading investigation.

Claims20

Dependent claims

A computer system comprising:

one or more hardware computer processors configured to execute a plurality of computer executable instructions in order to cause the computer system to:
access one or more computer readable storage devices storing:
at least one data cluster stored in a memory of the computer system and including at least:
data items including at least a plurality of trade data items including information associated with trades of a trader and a plurality of external event data items associated with the trades;
and
a plurality of logical connections indicating relationships among the data items in the data cluster;
and
a trading risk indicator configured to utilize at least a subset of the data items in the data cluster;
apply the trading risk indicator to the data cluster by:
analyzing the plurality of trade data items;
and
analyzing the plurality of external event data items to identify a subset of external event data items;
and
generate an alert based at least in part on determining that the subset of external event data items includes more external event data items than a threshold number of external event data items.

11 more elements

A computer system comprising:

one or more hardware computer processors configured to execute a plurality of computer executable instructions in order to cause the computer system to:
access one or more computer readable storage devices storing at least one data cluster stored in a memory of the computer system and including at least:
data items including at least a plurality of trade data items including information associated with trades of a trader;
a plurality of profit and loss (PNL) data items including information associated with the trader's PNL over a time period;
a plurality of logical connections indicating relationships among the data items in the data cluster;
and
a trading risk indicator configured to utilize at least a subset of the data items in the data cluster;
apply the trading risk indicator to the data cluster by:
analyzing the plurality of trade data items;
and
analyzing the plurality of PNL data items;
and
generate an alert based at least in part on the application of the trading risk indicator to the data cluster.

10 more elements

Dependencies are inferred from the claim text.

Systems and user interfaces for holistic, data-driven investigation of bad actor behavior based on clustering and scoring of related data

Life of this patent

Systems and user interfaces for holistic, data-driven investigation of bad actor behavior based on clustering and scoring of related data

Life of this patent

Abstract

Claims20