Method and system for dynamic risk assessment, risk monitoring, and caseload management

• US 20030037063A1
• Filed: 08/10/2001
• Published: 02/20/2003
• Est. Priority Date: 08/10/2001
• Status: Abandoned Application

• Current Assignee: Qlinx
• Original Assignee: Qlinx
• Inventors: Schwartz, David R.
• Application Number:
  US09/925,558
• Publication Number:
  US 20030037063A1
• Time in Patent Office: Days
• US Class Current: 707/104.1
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

A system and method for assessing risk, monitoring risk, and managing caseloads of individuals under risk assessment is provided. The system includes a network server computer that stores into memory information regarding each individual'"'"'s environment, behavior, physical condition, personal relationships, and/or mental state of being. Similar information regarding other individuals associated with the individual being assessed for risk also may be stored in the server memory. Individuals under risk assessment, individuals associated with individuals under risk assessment, and workers responsible for overseeing individuals under risk assessment may input this information into the server memory. The server processes this information for input into a risk assessment application that may include a fuzzy logic, neural network, neuro-fuzzy, or other artificial intelligence software or hardware to compute a composite risk score. The system provides workers an alarm signal when an individual'"'"'s assessed score exceeds a predetermined level. The system provides workers an alarm signal when an assessed score of an individual exceeds a predetermined level or falls into a predetermined classification category. Worker caseloads are automatically updated and/or prioritized by the system in accordance with alarm signals present in the server database. The system and method also provide individuals accessing the system with helpful resources based on information they provide the system server, and a means for communication between system users.

Claims

1. A risk assessment system for evaluating and determining levels of risk, comprising:

a computer;

a memory accessible by the computer;

a first file stored in the memory and including data defining weighted profile characteristics of a first individual;

an interface component that allows the first individual and a set of second individuals associated with the first individual to access the first file and set at least one of the profile characteristics; and

a risk assessment application in the computer for computing and storing in the computer memory a risk score for the first individual using input based on the profile characteristics.

2. The system according to claim 1, wherein at least one of the profile characteristics has a weight based on a response to a query stored in the computer memory and accessed by one of the first individual and one of the set of second individuals.

3. The system according to claim 1, wherein the system is network based, and the computer is a network server computer.

4. The system according to claim 1, wherein the risk assessment application has an ability to learn from patterns within a set of measured input variables and thereby adjust the risk assessment application based on the patterns of the set of measured input variables.

5. The system according to claim 1, wherein the risk assessment application has an ability to adapt to changes by training the risk assessment application with data based on a set of known risk scores and respective sets of known input variables corresponding to the known risk scores.

6. The system according to claim 1, wherein the interface component comprises a telephonic connection between the first individual or the set of second individuals and the system computer.

7. The system according to claim 6, wherein the telephonic connection comprises a hot line operator.

8. The system according to claim 6, wherein the telephonic connection comprises a second computer and a modem.

9. The system according to claim 6, wherein the telephonic connection comprises a wireless device for accessing the Internet.

10. The system according to claim 3, wherein the first individual has a first privileged level of server access and the each of the set of second individuals has a respective privileged level of access to the first file, each respective level of access being based on a relationship between respective ones of the second set of individuals and the first individual.

11. The system according to claim 3, wherein the system memory includes one or more query files, and wherein a software application in the server generates query sets from the one or more query files for at least one of the first individual and the set of second individuals, and responses to the query sets are stored in the computer memory.

12. The system according to claim 11, wherein the profile characteristics correspond to query responses provided by the at least one of the first individual and the set of second individuals.

13. The system according to claim 10, wherein a subset of the set of second individuals level of access includes access to the composite risk score in the memory.

14. The system according to claim 1, wherein the computer includes software that compares the computed risk score with a predetermined value and generates a marker in the first file when the composite risk score meets or exceeds the predetermined value.

15. The system according to claim 14, wherein the marker is accessible by at least one of the set of second individuals.

16. A method of determining and monitoring a type of risk, comprising:

creating and storing in a memory accessible by a computer a first file including data defining profile characteristics of a first individual;

storing in the memory a risk assessment application for computing a composite risk score indicative of a level of the risk type;

computing the composite risk score by providing input based on the profile characteristics of the first file to the risk assessment application;

storing the composite risk score in the computer memory;

generating at least one first query set in the computer memory, wherein the query set corresponds to the risk type;

allowing the first individual or a second set of individuals associated with the first individual to access at least one question of the at least one first query set in the computer memory; and

allowing transmission of information corresponding to the profile characteristics, and based on responses to the at least one question of the at least one first query set from the first individual or second set of individuals associated with the first individual, to the computer and storing the information in the first file.

17. The method of claim 16, further comprising:

generating an alarm signal when the composite risk score exceeds a predetermined value or falls within a predetermined range of values.

18. The method of claim 17, further comprising:

storing data corresponding to the alarm signal in the computer memory and allowing at least one individual of the second set of individuals to access the data corresponding to the marker.

19. The method of claim 17, further comprising:

generating and storing in the computer memory at least one second query set, wherein the selection of at least one question for the second query set is based on changes in the first individual'"'"'s profile characteristics causing said alarm signal.

20. The method of claim 16, wherein the information is transmitted within a computer network, and the computer is a server in the network.

21. The method of claim 19, further comprising:

storing on the server memory a software application allowing communication between the first individual and at least one individual of the second set of individuals, or between individuals of the second set of individuals.

22. The method of claim 19, further comprising:

providing the first individual or at least one individual of the second set of individuals with network resources based on a response to at least one question of the query set.

23. The method of claim 16, wherein the risk assessment application comprises a neural network and the method further comprises training the risk assessment application.

24. The method of claim 23, wherein the training of the risk assessment application is performed using a backpropagation technique.

25. The method of claim 16, wherein the risk assessment application comprises a neural network and the method further comprises training the risk assessment application using an input set of profile characteristics from a plurality of first individuals.

26. The method of claim 16, wherein the risk assessment application comprises a neural network and the method further comprises training the risk assessment application using at least one neural network and at least one live expert.