US-12626304-B1 - Methods and systems for generating a financial plan and streamlining client onboarding

US12626304B1US 12626304 B1US12626304 B1US 12626304B1US-12626304-B1

Abstract

A computer implemented method and system for using machine learning and artificial intelligence to generate a financial plan and streamline client onboarding is disclosed. The computer implemented method includes identifying first financial information from a recording of a first conversation between a first, a second and a third computing device, querying in a connected database, a preprogrammed financial plan algorithm for generating a provisional financial plan, determining missing financial information not in the financial information, sending, a message to the third computing device requesting the missing information. Further, the computer implemented method includes receiving a second message over the communications network from the third computing device and generating a financial plan based on the second financial information as the provisional financial plan, and editing the financial plan based on a third financial information and a fourth financial information to generate an updated financial plan.

Inventors

Spencer Jake Gauta

Assignees

Spencer Jake Gauta

Dates

Publication Date: 20260512
Application Date: 20240730

Claims (10)

1 . A computer implemented method using machine learning and artificial intelligence to generate a financial plan and streamline client onboarding comprising: initiating, with a first computing device, an audio-visual communication channel over a communications network between a second computing device associated with a financial advisor and a third computing device associated with a client; recording, using a microphone of the first computing device, a first conversation comprising at least audio data between the financial advisor and the client conducted via the audio-visual communication channel; transcribing, by a processor of the first computing device, a recording of the first conversation to generate text data and storing the text data in a client record of a customer relationship management system; querying a connected database comprising a customer relationship management system for storing a plurality of client records; identifying first financial information from at least one of the recording of the first conversation and the transcribed text data using at least one machine learning algorithm comprising at least one sniffer algorithm; wherein the at least one sniffer algorithm comprises at least one of (i) natural language processing algorithms, (ii) pattern recognition algorithms, and (iii) data classification algorithms to analyze data, extract, and capture predetermined relevant financial information; extracting the first financial information based on the at least one sniffer algorithm; querying in the connected database, a preprogrammed financial plan algorithm for generating a provisional financial plan based on the first financial information identified from the recording of the first conversation; determining missing financial information not in the financial information based on preprogrammed financial plan algorithm; generating a first message comprising a request for the missing financial information and sending, with a transceiver of the first computing device, the first message over the communications network to the third computing device, wherein the third computing device, responsive to the first message, displays on a graphical user interface selectable prompts in the form of icons corresponding to the missing financial information; receiving a second message over the communications network from the third computing device, the second message comprising second financial information corresponding the missing financial information; generating a financial plan based on the second financial information as the provisional financial plan; providing a conversational artificial intelligence assistant for engaging in at least one of (i) text based communications, and (ii) audio based communications with at least one of the financial advisor and the client; engaging in a second conversation between the conversational artificial intelligence assistant and at least one of the financial advisor and the client; extracting third financial information from the second conversation using the at least one sniffer algorithm; receiving a plurality of documents from at least one of the second computing device and the third computing device; analyzing the plurality of documents to extract fourth financial information using the at least one machine learning algorithm; and editing the financial plan based on the third financial information and the fourth financial information to generate an updated financial plan.
2 . The computer implemented method of claim 1 , wherein the recording of the first conversation is transcribed, with a processor of the first computing device, to generate transcribed text data.
3 . The computer implemented method of claim 1 further comprising: determining, by the first computing device, if the client intends to customize the updated financial plan; displaying one or more options selectable by the client on the client device, the options being displayed in form of icons on user interface of the third computing device; receiving a selection of one or more options by the client from the third computing device; editing the updated financial plan based on the selection of one or more options to generate a revised financial plan; and sending a third message comprising the revised financial plan in a readable medium over the communications network to the third computing device and storing the revised financial plan in the client record.
4 . The computer implemented method of claim 2 , wherein the transcribed text data is stored into a client record of the plurality of client records of the customer relationship management system.
5 . The computer implemented method of claim 1 , further comprising sending a third message comprising the updated financial plan in a readable medium over the communications network to the second computing device and storing the updated financial plan in the client record.
6 . A system, over a communications network, for using machine learning and artificial intelligence to generate a financial plan and streamline onboarding of a client, comprising: a connected database comprising a customer relationship management system for storing a plurality of client records; a memory; a network interface device communicatively coupled with the communications network; and, a processor configured for: initiating, with a first computing device, an audio-visual communication channel over the communications network between a second computing device associated with a financial advisor and a third computing device associated with the client; recording a first conversation comprising at least audio data between the financial advisor and the client conducted via the audio-visual communication channel; transcribing a recording of the first conversation to generate text data and storing the text data in a client record of a customer relationship management system; querying the connected database; identifying first financial information from at least one of the recording of the first conversation and the transcribed text data using at least one machine learning algorithm comprising at least one sniffer algorithm; wherein the at least one sniffer algorithm comprises at least one of (i) natural language processing algorithms, (ii) pattern recognition algorithms, and (iii) data classification algorithms to analyze data, extract, and capture predetermined relevant financial information; extracting the first financial information based on the at least one sniffer algorithm; querying in the connected database, a preprogrammed financial plan algorithm for generating a provisional financial plan based on the first financial information identified from the recording of the first conversation; determining missing financial information not in the financial information based on preprogrammed financial plan algorithm; generating a first message comprising a request for the missing financial information and causing a transceiver of the first computing device to send the first message over the communications network to the third computing device, wherein the third computing device, responsive to the first message, displays on a graphical user interface selectable prompts in the form of icons corresponding to the missing financial information; causing the transceiver to receive a second message over the communications network from the third computing device, the second message comprising second financial information corresponding the missing financial information; generating a financial plan based on the second financial information as the provisional financial plan; providing a conversational artificial intelligence assistant for engaging in at least one of (i) text based communications, and (ii) audio based communications with at least one of the financial advisor and the client; engaging in a second conversation between the conversational artificial intelligence assistant and at least one of the financial advisor and the client; extracting third financial information from the second conversation using the at least one sniffer algorithm; causing the transceiver to receive a plurality of documents from at least one of the second computing device and the third computing device; analyzing the plurality of documents to extract fourth financial information using the at least one machine learning algorithm; and editing the financial plan based on the third financial information and the fourth financial information to generate an updated financial plan.
7 . The system of claim 6 , wherein the processor is configured for transcribing a recording of the first conversation to generate transcribed text data.
8 . The system of claim 7 , wherein the processor is further configured for: determining, by the first computing device, the client intends to customize the updated financial plan; displaying one or more options selectable by the client on the client device, the options being displayed in form of icons on user interface of the third computing device; receiving a selection of one or more options by the client from the third computing device; editing the updated financial plan based on the selection of one or more options to generate a revised financial plan; and sending a third message comprising the revised financial plan in a readable medium over the communications network to the third computing device and storing the revised financial plan in the client record.
9 . The system of claim 7 , wherein the transcribed text data is stored into a client record of the plurality of client records of the customer relationship management system.
10 . The system of claim 7 , wherein the processor is further configured for sending a third message comprising the updated financial plan in a readable medium over the communications network to the second computing device and storing the updated financial plan in the client record.

Description

REFERENCE TO RELATED APPLICATIONS This application is a non-provisional application that claims the benefit of the filing date of U.S. Provisional Application Ser. No. 63/532,631 titled “Methods and Systems for Generating a Financial Plan and Streamlining Client Onboarding” and filed 14 Aug. 2023, and the subject matter of which is incorporated herein by reference. TECHNICAL FIELD The present invention relates to the field of financial plans, and more specifically to methods and systems for generating financial plans and onboarding clients. BACKGROUND A financial plan is a comprehensive evaluation of an individual's current financial situation, asset values, short-term and long-term economic goals, and a strategy to achieve the goals. The comprehensive evaluation includes analysis of the goals and a large set of data associated with an individual, such as, not limiting to, current income, tax liabilities, net worth, future retirement plan, asset allocation, and estate plans, expenses, liabilities, and other data. The short-term economic goals mainly include factors relating to current debt, a budget, and emergency funds, whereas the long-term economic goals consider objectives such as retirement, education for dependents or themselves, and major expenses, such as new car, wedding, etc. To achieve the long-term and short-term economic goals, individuals generally work with a financial advisor. The financial advisor establishes a direct relationships with many clients for financial planning, and regularly consult with each of the clients to help clients achieve their financial goals. The financial advisor considers multiple factors including variable factors, such as degrading economy, rise in interest rates, fall in equity prices, or sudden inflation that impacts assets and liabilities of the individual. Collecting and analyzing such a large set of data and considering the multiple factors to generate the financial plan is generally cumbersome and complex. The process of generating the financial plan is also time-consuming and prone to errors that may affect accuracy or reliability of the financial plan. As a result, there exists a need for improvements over the prior art and more particularly for a more efficient way of generating a financial plan and onboarding a client. SUMMARY A system and a method for using machine learning and artificial intelligence to generate a financial plan and streamline client onboarding is disclosed. This Summary is provided to introduce a selection of disclosed concepts in a simplified form that are further described below in the Detailed Description including the drawings provided. This Summary is not intended to identify key features or essential features of the claimed subject matter. Nor is this Summary intended to be used to limit the claimed subject matter's scope. In one embodiment, a computer implemented method using machine learning and artificial intelligence to generate a financial plan and streamline client onboarding is disclosed. The computer implemented method is initiating an audio-visual communication channel over a communications network between a second computing device associated with a financial advisor and a third computing device associated with a client. The audio-visual communication is initiated with a first computing device; recording, using a microphone of the first computing device, a first conversation comprising at least audio data between the financial advisor and the client conducted via the audio-visual communication channel; querying a connected database having a customer relationship management system that has a plurality of client records; identifying first financial information from a recording of the first conversation using a machine learning algorithm having a sniffer algorithm, the sniffer algorithm has one of (i) natural language processing algorithms, (ii) pattern recognition algorithms, and (iii) data classification algorithms to analyze data, extract, and capture predetermined relevant financial information; extracting the first financial information based on the sniffer algorithm; querying in the connected database, a preprogrammed financial plan algorithm for generating a provisional financial plan based on the first financial information identified from the recording of the first conversation; determining missing financial information not in the financial information based on preprogrammed financial plan algorithm; generating a first message having a request for the missing financial information and sending, with a transceiver of the first computing device, the first message over the communications network to the third computing device; receiving a second message over the communications network from the third computing device, the second message having second financial information corresponding the missing financial information; generating a financial plan based on the second financial information as the provisional financial pl