System and method for prioritizing customer data

1 . A method of prioritizing data, the method comprising, using a computer processor:

using one or more datasets of tabular data to generate one or more analysis prompts, wherein one or more of the datasets are received from one or more computer devices separate from the processor, and wherein one or more of the datasets are transformed into natural language;

applying the one or more analysis prompts to a large language model (LLM) to generate a vector for each customer dataset

generating, by a classifier model, a prioritization value based on the generated vector; and

generating a prioritization of the one or more datasets by comparing the prioritization value of the vector to threshold values, and producing an alert when the prioritization value of the vector lies above the threshold values.

2 . A method according to claim 1 , wherein when the prioritization value of the vector lies above the threshold values, suspending a customer account linked to the vector.

3 . A method according to claim 1 , wherein when the prioritization value of the vector is higher than the threshold values, classifying the dataset as high priority dataset; and

when the prioritization value of the vector is lower than the threshold values, classifying the dataset as low priority dataset.

4 . A method according to claim 1 , wherein the one or more datasets comprise data items selected from a group consisting of categorical data items and numerical data items.

5 . A method according to claim 1 , wherein the vector undergoes principal component analysis.

6 . A method according to claim 1 , wherein the one or more datasets of tabular data are converted into an open standard file format prior to the analysis prompt generation.

7 . A method according to claim 1 , comprising creating the threshold value based on previously recorded datasets comprising customer datasets using machine learning.

8 . A method according to claim 1 , comprising generating the prioritization by comparing the prioritization value of the vector with predicted vector values.

9 . A method according to claim 1 , wherein one or more datasets of tabular data comprise data items for which a previously predicted threshold value has been recorded.

10 . A system for prioritizing data, the system comprising:

a computing device;

a memory; and

a processor, the processor configured to:

use of one or more datasets of tabular data to generate one or more analysis prompts, wherein one or more of the datasets are received from one or more computer devices separate from the processor, and wherein one or more of the datasets are transformed into natural language;

apply the one or more analysis prompts to a large language model (LLM) to generate a vector for each dataset;

generate, by a classifier model, a prioritization value based on the generated vector; and

generate a prioritization of the one or more datasets by comparing the prioritization value of the vector to threshold values, and producing an alert when the prioritization value of the vector lies above the threshold values.

11 . A system according to claim 10 , wherein when the prioritization value of the vector lies above the threshold values, the processor is configured to suspend a customer account linked to the vector.

12 . A system according to claim 10 , wherein when the prioritization value of the vector is higher than the threshold values, classifying the dataset as high priority dataset; and

when the prioritization value of the vector is lower than the threshold values, classifying the dataset as low priority dataset.

13 . A system according to claim 10 , wherein the one or more datasets comprise data items selected from a group consisting of categorical data items and numerical data items.

14 . A system according to claim 10 , wherein the vector undergoes principal component analysis.

15 . A system according to claim 10 , wherein the one or more datasets of tabular data are converted into an open standard file format prior to the analysis prompt generation.

16 . A system according to claim 10 , wherein the processor is configured to create the threshold values based on previously recorded datasets comprising customer datasets using machine learning.

17 . A method of managing data, the method comprising, using a computer processor:

using a plurality of datasets of tabular data to create a plurality of analysis prompts, wherein one or more of the datasets are received from one or more computer devices separate from the processor, and wherein one or more of the datasets are transformed into natural language;

submitting the plurality of analysis prompts to a large language model (LLM) to convert the plurality of analysis prompts into a vector for each dataset;

generating, by a classifier model, a prioritization value based on the generated vector; and

comparing the prioritization value of the vector to threshold values to create a prioritization of the plurality of data sets, and producing an alert when the prioritization value of the vector lies above the threshold values.