# US 2019/0378207 A1 · Financial health tool

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- Number: US 2019/0378207 A1
- Document ID: US20190378207A1
- Status: Published application
- Kind: A1
- Application number: 16/002,383
- Filed: 2018-06-07
- Published: 2019-12-12
- Earliest claimed: 2018-06-07
- Assignees: Intuit Inc.
- Applicants: Intuit Inc.
- Inventors: Aaron DIBNER-DUNLAP; Kevin FURBISH; Kymm KAUSE; Swathi NIMMAGADDA; Nirmala RANGANATHAN
- Web page: https://patentgrep.com/patent/US20190378207A1

## CPC

- G06Q 40/02: Banking, e.g. interest calculation or account maintenance (credit or loans G06Q40/03)
- G06Q 30/02: Marketing; Price estimation or determination; Fundraising
- H04L 67/306: User profiles
- H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)}
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

A processor may obtain data indicating a user's financial health. The data may include personality data not directly related to finances. The processor may analyze the data to identify a change applicable to a financial account of the user. The change may be configured to improve the user's financial health. The processor may automatically cause the change to be implemented by a network-accessible financial service.

## Claims

### Claim 1

A method of identifying and implementing an account change comprising:
obtaining, at a processor, data indicating a user's financial health, the data including personality data not directly related to finances;
analyzing, by the processor, the data to identify a change applicable to a financial account of the user, the change configured to improve the user's financial health; and
automatically causing, by the processor, the change to be implemented by a network-accessible financial service.

### Claim 2 (depends on 1)

The method of claim 1, wherein the user is a household user including a plurality of individuals, and the data includes data generated by at least two of the plurality of individuals.

### Claim 3 (depends on 1)

The method of claim 1, wherein the personality data includes a typical daily activity pattern for the user.

### Claim 4 (depends on 3)

The method of claim 3, wherein the obtaining includes generating, by the processor, the typical daily activity pattern.

### Claim 5 (depends on 4)

The method of claim 4, wherein the generating includes:
aggregating a set of activity data describing actions of the user over a plurality of days from at least one data source;
identifying at least one regular activity routinely performed at approximately a same time of day, a same day of week, or combination thereof, and
adding the at least one regular activity to the typical daily activity pattern.

### Claim 6 (depends on 1)

The method of claim 1, wherein the data includes a transaction prediction for the user.

### Claim 7 (depends on 6)

The method of claim 6, further comprising generating, by the processor, the transaction prediction.

### Claim 8 (depends on 7)

The method of claim 7, wherein the generating includes:
aggregating a set of transaction data describing transactions of the user over a plurality of days from at least one data source;
identifying at least one frequent transaction performed repeatedly in a substantially same manner by the user;
identifying at least one second user having second personality data at least partially matching the personality data;
identifying at least one second frequent transaction performed repeatedly in a substantially same manner by the at least one second user; and
predicting the transaction by the user based on at least one of the at least one frequent transaction and the at least one second frequent transaction.

### Claim 9 (depends on 1)

The method of claim 1, wherein the personality data includes a future goal for the user.

### Claim 10 (depends on 9)

The method of claim 9, further comprising generating, by the processor, the future goal.

### Claim 11 (depends on 10)

The method of claim 10, wherein the generating includes:
identifying at least one goal within the personality data;
identifying at least one second user having second personality data at least partially matching the personality data;
identifying at least one second goal associated with the at least one second user; and
predicting the future goal based on at least one of the at least one goal and the at least one second goal.

### Claim 12 (depends on 1)

The method of claim 1, wherein the data includes a financial volatility for the user.

### Claim 13 (depends on 12)

The method of claim 12, further comprising generating, by the processor, the financial volatility.

### Claim 14 (depends on 13)

The method of claim 13, wherein the generating includes:
aggregating a set of financial data describing the finances of the user over a plurality of days from at least one data source;
aggregating a set of financial data describing the finances of the user over a plurality of days from at least one data source;
aggregating a set of activity data describing actions of the user over the plurality of days from the at least one data source;
identifying at least one abnormality in the set of financial data, the set of activity data, or a combination thereof, the at least one abnormality indicating financial vulnerability during at least a portion of the plurality of days; and
determining that the financial volatility exists based on the identifying of the at least one abnormality.

### Claim 15 (depends on 1)

The method of claim 1, further comprising automatically causing, by the processor, a user interface to suggest a user action configured to improve the user's financial health in response to the analyzing.

### Claim 16

A system for identifying and implementing an account change comprising:
a non-volatile memory; and
a processor coupled to the memory, the processor configured to:
obtain data indicating a user's financial health, the data including personality data not directly related to finances;
store the data in the memory;
analyze the stored data to identify a change applicable to a financial account of the user, the change configured to improve the user's financial health; and
automatically cause the change to be implemented by a network-accessible financial service in communication with the processor through a network.

### Claim 17 (depends on 16)

The system of claim 16, wherein the user is a household user including a plurality of individuals, and the data includes data generated by at least two of the plurality of individuals.

### Claim 18 (depends on 16)

The system of claim 16, wherein the personality data includes a typical daily activity pattern for the user.

### Claim 19 (depends on 18)

The system of claim 18, wherein the processor is further configured to:
generate the typical daily activity pattern; and
store the typical daily activity pattern in the memory.

### Claim 20 (depends on 19)

The system of claim 19, wherein the generating includes:
aggregating a set of activity data describing actions of the user over a plurality of days from at least one data source in communication with the processor through the network;
identifying at least one regular activity routinely performed at approximately a same time of day, a same day of week, or combination thereof; and
adding the at least one regular activity to the typical daily activity pattern.

### Claim 21 (depends on 16)

The system of claim 16, wherein the data includes a transaction prediction for the user.

### Claim 22 (depends on 21)

The system of claim 21, wherein the processor is further configured to:
generate the transaction prediction; and
store the transaction prediction in the memory.

### Claim 23 (depends on 22)

The system of claim 22, wherein the generating includes:
aggregating a set of transaction data describing transactions of the user over a plurality of days from at least one data source in communication with the processor through the network;
identifying at least one frequent transaction performed repeatedly in a substantially same manner by the user;
identifying at least one second user having second personality data at least partially matching the personality data;
identifying at least one second frequent transaction performed repeatedly in a substantially same manner by the at least one second user; and
predicting the transaction by the user based on at least one of the at least one frequent transaction and the at least one second frequent transaction.

### Claim 24 (depends on 16)

The system of claim 16, wherein the personality data includes a future goal for the user.

### Claim 25 (depends on 24)

The system of claim 24, wherein the processor is further configured to:
generate the future goal; and
store the future goal in the memory.

### Claim 26 (depends on 25)

The system of claim 25, wherein the generating includes:
identifying at least one goal within the personality data;
identifying at least one second user having second personality data at least partially matching the personality data;
identifying at least one second goal associated with the at least one second user; and
predicting the future goal based on at least one of the at least one goal and the at least one second goal.

### Claim 27 (depends on 16)

The system of claim 16, wherein the data includes a financial volatility for the user.

### Claim 28 (depends on 27)

The system of claim 27, wherein the processor is further configured to:
generate the financial volatility; and
store the financial volatility in the memory.

### Claim 29 (depends on 28)

The system of claim 28, wherein the generating includes:
aggregating a set of financial data describing the finances of the user over a plurality of days from at least one data source in communication with the processor through the network;
aggregating a set of financial data describing the finances of the user over a plurality of days from at least one data source;
aggregating a set of activity data describing actions of the user over the plurality of days from the at least one data source;
identifying at least one abnormality in the set of financial data, the set of activity data, or a combination thereof, the at least one abnormality indicating financial vulnerability during at least a portion of the plurality of days; and
determining that the financial volatility exists based on the identifying of the at least one abnormality.

### Claim 30 (depends on 16)

The system of claim 16, wherein the processor is further configured to automatically cause a user interface of a user device in communication with the processor through the network to suggest a user action configured to improve the user's financial health in response to the analyzing.