Generating cohesive explanations that communicate insights and patterns on multi-dimensional financial planning data

A computer-program product comprising one or more non-transitory machine-readable storage media, including stored instructions configured to cause a computing system to perform a set of actions including:

• determining that analysis is enabled for a hierarchy of data of a multi-dimensional set of data, wherein analysis is disabled for one or more other hierarchies of data of the multi-dimensional set of data;
• based at least in part on determining that the analysis is enabled, analyzing members of the hierarchy to detect a pattern or anomaly within the hierarchy;
• in response to detecting the pattern or anomaly in a member of the hierarchy, generating a prompt comprising:
• a path to the member, wherein the path comprises one or more ancestor nodes and a delimiter between the one or more ancestor nodes and the member;
• one or more values identified as having the pattern or anomaly for the member;
• one or more metrics that define an extent of the pattern or anomaly in relation to one or more other values;
• one or more time periods during which the pattern or anomaly occurred;
• one or more examples comprising one or more example paths, one or more example values, one or more example metrics, one or more example time periods, and one or more example summaries of one or more example patterns or anomalies for one or more example members at the one or more example paths;
• prompting a large language model with the prompt to generate a resulting summary of the pattern or anomaly;
• causing display of at least part of the resulting summary of the pattern or anomaly.

A system comprising:

• one or more processors;
• one or more non-transitory computer-readable media storing instructions, which, when executed by the system, cause the system to perform a set of actions including:
• determining that analysis is enabled for a hierarchy of data of a multi-dimensional set of data, wherein analysis is disabled for one or more other hierarchies of data of the multi-dimensional set of data;
• based at least in part on determining that the analysis is enabled, analyzing members of the hierarchy to detect a pattern or anomaly within the hierarchy;
• in response to detecting the pattern or anomaly in a member of the hierarchy, generating a prompt comprising:
• a path to the member, wherein the path comprises one or more ancestor nodes and a delimiter between the one or more ancestor nodes and the member;
• one or more values identified as having the pattern or anomaly for the member;
• one or more metrics that define an extent of the pattern or anomaly in relation to one or more other values;
• one or more time periods during which the pattern or anomaly occurred;
• one or more examples comprising one or more example paths, one or more example values, one or more example metrics, one or more example time periods, and one or more example summaries of one or more example patterns or anomalies for one or more example members at the one or more example paths;
• prompting a large language model with the prompt to generate a resulting summary of the pattern or anomaly;
• causing display of at least part of the resulting summary of the pattern or anomaly.