METHOD AND SYSTEM FOR ARTIFICIAL INTELLIGENCE-BASED ACCELERATION OF ZERO-TOUCH PROCESSING

1 . A system for driving zero-touch potential for an event-to-entry process, comprising:

a processor; and

a memory, coupled to the processor, configured to store executable instructions that, when executed by the processor, cause the processor to:

perform, by a process-mining engine, process-mining on an event-to-entry process associated with an organization to collect data information associated with the process;

determine, by an input-related zero-touch evaluation engine, an input-related zero-touch quotient for the event-to-entry process based on the data information;

determine, by a rule-related zero-touch evaluation engine, a rule-related zero-touch quotient for the event-to-entry process based on the data information;

determine, by a predictive accounting factor component, a zero-touch potential predictive accounting factor (ZTP PAF) value for the event-to-entry process, the ZTP PAF value quantifying an incremental zero-touch potential for the event-to-entry process and corresponding attributes; and

generate, by a zero-touch processing engine a zero-touch processing quotient for the event-to-entry process based on the input-related zero-touch quotient, the rule-related zero-touch quotient, and the ZTP PAF value.

2 . The system of claim 1 , wherein, to perform the process-mining on an event-to-entry process associated with an organization, the instructions when executed by the processor further cause the processor to:

map activities associated with the organization to one or more events and one or more entries associated with the event-to-entry process.

3 . The system of claim 1 , wherein, to determine the input-related zero-touch quotient for the event-to-entry process, the instructions when executed by the processor further cause the processor to:

determine a first set of data components included in the event-to-entry process;

allocate a maturity value for each of the first set of data components; and

determine the input-related zero-touch quotient for the event-to-entry process based on the maturity value for each of the first set of data components.

4 . The system of claim 3 , wherein the maturity value for each of the first set of data components is determined by using a machine learning model.

5 . The system of claim 3 , wherein the first set of data components comprise one or more of a structuredness, repetitiveness, or intervention associated with the event-to-entry process.

6 . The system of claim 5 , wherein a maturity value of the structuredness, or repetitiveness has a proportionate and positive relationship to the input-related zero-touch quotient, and a maturity value of the intervention has an inverse relationship to the input-related zero-touch quotient.

7 . The system of claim 3 , wherein the instructions when executed by the processor further cause the processor to determine a maturity level for each of the first set of data components.

8 . The system of claim 7 , wherein the maturity level is one of a trailing level, evolving level, maturing level, or leading level.

9 . The system of claim 1 , wherein, to determine the rule-related zero-touch quotient for the event-to-entry process, the instructions when executed by the processor further cause the processor to:

determine a second set of data components included in the event-to-entry process;

allocate a maturity value for each of the second set of data components; and

determine the rule-related zero-touch quotient for the event-to-entry process based on the maturity value for each of the second set of data components.

10 . The system of claim 9 , wherein the second set of data components comprise one or more of a standardization, transactional/analytical, or exception associated with the event-to-entry process.

11 . The system of claim 10 , wherein a maturity value of the standardization or transactional/analytical has a proportionate and positive relationship to the rule-related zero-touch quotient, and a maturity value of the exception has an inverse relationship to the rule-related zero-touch quotient.

12 . The system of claim 1 , wherein the ZTP PAF value is determined by using a predictive machine learning model.

13 . The system of claim 12 , wherein the predictive machine learning model has been trained and tested over data including a plurality of event-to-entry processes with varying degrees of attributes.

14 . The system of claim 1 , wherein the instructions when executed by the processor further cause the processor to:

determine a plurality of zero-touch processing quotients for a plurality of processes associated with the organization; and

generate an aggregated zero-touch processing quotient based on the plurality of zero-touch processing quotients.

15 . The system of claim 1 , wherein the instructions when executed by the processor further cause the processor to:

generate one or more recommendations for improving the zero-touch processing quotient for the event-to-entry process.

16 . A computer-implemented method for driving zero-touch potential for an event-to-entry process, the method comprising:

performing process-mining for an event-to-entry process associated with an organization to collect data information associated with the process;

determining an input-related zero-touch quotient for the event-to-entry process based on the data information;

determining a rule-related zero-touch quotient for the event-to-entry process based on the data information;

determining a zero-touch potential predictive accounting factor (ZTP PAF) value for the event-to-entry process, the ZTP PAF value quantifying an incremental zero-touch potential for the event-to-entry process and corresponding attributes; and

generating a zero-touch processing quotient for the event-to-entry process based on the input-related zero-touch quotient, the rule-related zero-touch quotient, and the ZTP PAF value.

17 . The method of claim 16 , wherein performing process-mining for an event-to-entry process associated with an organization further comprises:

mapping activities associated with the organization to one or more events and one or more entries associated with the event-to-entry process.

18 . The method of claim 16 , wherein determining the input-related zero-touch quotient for the event-to-entry process further comprises:

determining a first set of data components included in the event-to-entry process;

allocating a maturity value for each of the first set of data components; and

determining the input-related zero-touch quotient for the event-to-entry process based on the maturity value for each of the first set of data components.

19 . The method of claim 16 , wherein determining the rule-related zero-touch quotient for the event-to-entry process further comprises:

determining a second set of data components included in the event-to-entry process;

allocating a maturity value for each of the second set of data components; and

determining the rule-related zero-touch quotient for the event-to-entry process based on the maturity value for each of the second set of data components.

20 . A computer program product for driving zero-touch potential for an event-to-entry process, the computer program product comprising a non-transitory computer-readable medium having computer-readable program code stored thereon, the computer-readable program code configured to:

perform a process-mining on an event-to-entry process associated with an organization to collect data information associated with the process;

determine an input-related zero-touch quotient for the event-to-entry process based on the data information;

determine a rule-related zero-touch quotient for the event-to-entry process based on the data information;

determine a zero-touch potential predictive accounting factor (ZTP PAF) value for the event-to-entry process, the ZTP PAF value quantifying an incremental zero-touch potential for the event-to-entry process and corresponding attributes; and

generate a zero-touch processing quotient for the event-to-entry process based on the input-related zero-touch quotient, the rule-related zero-touch quotient, and the ZTP PAF value.