Patent Application
20140365355
The subject application relates to observing behaviors and explicitly and/or implicitly interpreting personal data to generate a financial measure or a behavioral based financial score.
A number of consumers have experience with short term loans, payday advances, cash advances, and so forth. These types of financial instruments often require proof of employment and financial viability, such as a checking account and evidence of employment. Typically, the interest rate for such instruments can be high, due to the level of risk experienced by the lender. However, when a consumer needs to obtain a quick credit decision, there may be few alternatives except borrowing from pawn shops, friends, or family.
Additionally, consumers are frequently presented with opportunities to apply for instant approval for credit cards during internet shopping, or at the point of sale during traditional in-store shopping. Often the consumer can charge a current purchase to the new account if they are approved, and may be able to take advantage of one or more promotions for applying. However, consumers having little, or no, credit history are unlikely to be approved for these credit cards, such as with college students trying to start careers for the first time or groups of elderly always wary of credit. In addition, some consumers choose not to use credit cards, or elect not to go through the application process at the time that the offer is presented.
Moreover, retailers often attempt to persuade consumers to purchase additional items, or items related to items that the consumer is purchasing. In order to tailor the suggestions to the desires of the consumer, some retailers employ loyalty cards that enable the retailer to monitor the buying patterns of the consumer. Similarly, online retailers often encourage consumers to maintain a user account with the retailer, and data tracked via the user account can be used to suggest purchase options, or tailor promotions based on the consumer's buying patterns. However, similar to instant credit card applications, some consumers choose not to go through the loyalty card application or online account setup process.
The above-described deficiencies of today's credit application and promotional tools lend for the need to better serve and target potential clients. The above deficiencies are merely intended to provide an overview of some of the problems of conventional systems, and are not intended to be exhaustive. Other problems with conventional systems and corresponding benefits of the various non-limiting embodiments described herein may become further apparent upon review of the following description.
The following presents a simplified summary in order to provide a basic understanding of some aspects disclosed herein. This summary is not an extensive overview. It is intended to neither identify key or critical elements nor delineate the scope of the aspects disclosed. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
Various embodiments for facilitating a financial interaction and determining a financial score during the financial interaction are contained herein. An exemplary system comprises a memory that stores computer-executable components, and a processor, communicatively coupled to the memory, that facilitates execution of the computer-executable components. The computer-executable components include a dialogue component configured to facilitate a financial interaction relating to a set of financial behaviors. A behavioral analysis component is configured to analyze the financial interaction to determine an indication of the set of financial behaviors. A scoring component is configured to generate a financial score based on the indication.
In another non-limiting embodiment, a method comprises facilitating, by a system including at least one processor, a financial interaction relating to a set of financial behaviors. The method includes determining, from the financial interaction, one or more indications that relate to the set of financial behaviors. The method includes generating a financial score based on the one or more indications, and facilitating display of the financial score.
In still another non-limiting embodiment, an exemplary computer readable storage medium has computer executable instructions that, in response to execution by a computing system, cause the computing system to perform operations that can comprise facilitating a financial communication related to financial behavior. A financial score can be presented that is related to the set of financial communications and/or to financial behavior. The operations can further include dynamically adjusting the financial score in response to the analysis of the financial communication and/or behavior.
In another non-limiting embodiment, a system is disclosed comprising means for facilitating a financial interaction with a set of financial behavior communications, means for presenting a financial score based on an explicit and implicit behavioral analysis, and means for adjusting the financial score in response to analysis.
Embodiments and examples are described below with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details in the form of examples are set forth in order to provide a thorough understanding of the various embodiments. It will be evident, however, that these specific details are not necessary to the practice of such embodiments. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate description of the various embodiments.
Reference throughout this specification to “one embodiment,” or “an embodiment,” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrase “in one embodiment,” or “in an embodiment,” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
As utilized herein, terms “component,” “system,” “interface,” and the like are intended to refer to a computer-related entity, hardware, software (e.g., in execution), and/or firmware. For example, a component can be a processor, a process running on a processor, an object, an executable, a program, a storage device, and/or a computer. By way of illustration, an application running on a server and the server can be a component. One or more components can reside within a process, and a component can be localized on one computer and/or distributed between two or more computers.
Further, these components can execute from various computer readable media having various data structures stored thereon such as with a module, for example. The components can communicate via local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network, e.g., the Internet, a local area network, a wide area network, etc. with other systems via the signal).
As another example, a component can be an apparatus with specific functionality provided by mechanical parts operated by electric or electronic circuitry; the electric or electronic circuitry can be operated by a software application or a firmware application executed by one or more processors; the one or more processors can be internal or external to the apparatus and can execute at least a part of the software or firmware application. As yet another example, a component can be an apparatus that provides specific functionality through electronic components without mechanical parts; the electronic components can include one or more processors therein to execute software and/or firmware that confer(s), at least in part, the functionality of the electronic components. In an aspect, a component can emulate an electronic component via a virtual machine, e.g., within a cloud computing system.
The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements. In addition, the term “set” refers to “one or more.”
In consideration of the above-described deficiencies among other things, various embodiments are provided that dynamically interpret data related to clients for credit worthiness, and, more generally, is related to facilitating and observing a set of financial interactions, such as dialogues, conversations, or exchanges. An analysis of a user's behavior from the interactions and/or tracked behaviors to determine a financial behavioral score that can measure a strength or tendency towards behaving according to a particular financial behavior. The set of financial behaviors can include a person's risk tolerance level, spending habits, goal setting, saving habits, payment history, financial attitudes towards each, and/or other behavioral indications (e.g., key indicators) that relate to financial behavior, financial habits, financial beliefs, and/or, in other words, financial attitudes of a person's financial knowledge/mindset, which can be factored in a measure for financial health (e.g., a financial score).
In one embodiment, an analysis of communication/dialogue and behaviors are supplemented with factors that are traditionally easier to analyze from a traditional credit score (e.g., late payments, credit to income ratios, etc.). Computer intelligence or logic of the system can process and analyze complex relations. For example, a user can respond to advice or a recommendation of the system in various ways and also communicate different dispositions, behaviors, and/or behavioral attitudes via dialoguing to determine whether the user is compliant, obedient, stubborn, lazy, etc. Thus, observed behaviors as well as communicated attitudes (e.g., communicated behavior) can be used to dynamically calculate and illustrate a financial measure to the user through continuous and dynamic conversation.
The system operates with a dialogue component and an advice component that assesses a user's financial behavior proactively and dynamically according to assessments of the user from communications and/or observed actual behaviors related to financial transactions (e.g., online purchases, bank account activity, cash flows, etc.). For example, the system can analyze reactive deeds of a user in relation to recommendations or advice provided. Additionally, a user can make an individual decision, independent of any recommendations, which can also be assessed by the system. For example, if a user has a high interest rate on a credit card, the system can communicate a suggestion or recommendation to refinance for a particular different bank credit card for better terms. Whether the user follows or does not follow the advice, the system can assess the user's behavior. If the user did not get a financial recommendation from the system, but initiated a better term card independently and refinanced the card, the system still analyzes the behavior and impacts the score with respect to how positive or negative the decision is weighted or considered.
In one example, a financial interaction or dialogue is facilitated that is generated in response to the actual financial behavior (recent transactions, savings, debits and credits, rent, etc.) of a user. The financial interaction is facilitated according to the transactional behavior and recommendations provided to the user, whose behavior can be tracked via communications with a transactional database or system component (e.g., a digital wallet, bank account aggregators, etc.) For example, the recommendation system can recommend reducing spending in a particular category. Communication with the client can be performed in order to explicitly and implicitly, through various dialoging and responses, determine a tendency to behave financially in various ways. A financial score can be dynamically determined based on how the user behaves in response to the recommendations and/or from continuous communication with the user about financial behavior.
In addition, various dialogues can be exchanged to determine indications of a user profile and assess a user's profile, such as a psychological profile, a personality classification, and/or behavioral prediction related to the user's personal finances. A thrifty person could be very good at keeping a budget, but not fully utilize resources available such as better loan rates, opportunities for investing, etc. Therefore, a better understanding of the person's attitude and corresponding behaviors could better enable the user to be assessed and work on ways to improve his or her financial assessment through greater knowledge, understandings, and/or financial behavior.
In another embodiment, a determination of the credit worthiness of a client for a financial instrument (e.g., a small loan, a large loan or some other financial instrument) can be made based on information pertaining to the client's behavior (e.g., background, set of beliefs, attitude, habits, etc.). The information can be learned and obtained by analysis of a financial interaction that is facilitated, such as an exchange, a dialogue, and/or a conversation. The analysis can be further conducted with or without recommendations and provide determinations as to how the user will likely act as factors for a financial measure.
A set of behaviors can include, for example, beliefs, actions related to various stimuli (e.g., better credit offers, improved credit rating options, savings tips, etc.), inputs and/or responses. The set of behaviors can be ascertained from indicators or indications that are identified throughout the financial interaction with a client. These indicators can be used to determine a set of financial scores that are displayed from, during and/or throughout the interaction. The indicators can be utilized as a factor or as a basis to determine a credit worthiness score for the client interacting in the financial interaction.
Examples of Explicit and/or Implicit Personal Data Analysis for Behavioral Based Score
Referring initially to
The system 100 includes a client device 102 that includes a computing device, a mobile device and/or a mobile phone that is operable to communicate one or more messages via an electronic digital message (e.g., a text message, a multimedia text message, and the like) and/or with an audio input via a microphone, for example. The client device 102 includes a processor 104 and at least one data store 106 that processes and stores exchanges of a financial interaction (e.g., a set of conversations, exchanges, and/or interactions), which can include a number of responses or behaviors of the client that can be generated and/or tracked from among one or more devices. For example, a set of recommendations or a suggestions can be provided to a client that can include a set of questions, a set of answers, a set of statements, a set of declarations, a set of data, etc., that are exchanged during the interaction, and based on the response by the user, the system 100 can determine and/or update a financial score.
The client device 102 is operable to communicate multimedia content via the network 108, which can include a cellular network, a wide area network, local area network, and/or other type network. The client device 102 is further operable to communicate to other devices or systems, such as to a network system 110. The network 108 can also include a cloud network that enables the delivery of computing and/or storage capacity as a service to a community of end-recipients that entrusts services with a user's data, software and computation over a network. Additionally, the client device 102 can include multiple client devices, in which end users access cloud-based applications through a web browser, a light-weight desktop or mobile app and to resources of the networked system 110.
The system 100 includes the networked system 110 that is communicatively connected to one or more servers and/or client devices via the network 108 for receiving user input and communicating during the financial interaction. The network 108 is communicatively connected to the networked system 110, which is operable as a networked host to provide, generate and/or enable message generation on the network 108 and/or the client device 102 either directly or via the network 108. The networked system 110 includes an application programming interface (API) server, in which the client device 102 and/or other client device, for example, can requests various system functions by calling one or more APIs residing on the API server 112 for invoking a particular set of rules (code) and specifications that various computer programs interpret to communicate with each other. The API server 112 operates with a web server 114 to serve as an interface between different software programs, the client machines, third party servers and other devices. For example, the API server 112 and/or the web server 114 facilitate interaction with a client or customer via a dialogue component 116, a behavioral analysis component 118, and a scoring component 120, as well as with other various components, in which each have applications for hardware and/or software.
The networked system 110 further includes a database server 122 that is operatively coupled to one or more data stores 124, which includes data related to various described components and systems described herein, such as behavior options. The behavior options can comprise questions, possible financial scenarios for presentation to the user and determining how the user would act, financial recommendations, indications of financial behavior that can be indexed, stored and classified to correspond with a set of conversational/behavioral inputs, as well as other data for determining a financial score via a financial interaction and/or a transaction. Aspects of the systems, apparatuses or processes explained in this disclosure can constitute machine-executable component embodied within machine(s), e.g., embodied in one or more computer readable mediums (or media) associated with one or more machines. Such component, when executed by the one or more machines, e.g., computer(s), computing device(s), electronic devices, virtual machine(s), etc. can cause the machine(s) to perform the operations described.
The network system 110, including the dialogue component 116, the behavioral analysis component 118 and the scoring component 120, is configured to facilitate, analyze and generate feedback during and from a financial interaction/communication with a client. The dialogue component 116 is configured, for example, to facilitate dialogue or conversation, such as a financial interaction via the client device 102. The financial interaction that is facilitated is based on a set of financial behaviors, such as whether the client or user follows advice or recommendations that are provided, exhibits indications or characteristics of predictable behavior or attitudes. For example, the networked system 110 via the dialogue component 116 generates a set of recommendations or suggestions, questions, a set of answers, a set of scenarios, a set of feedback related to the questions, answers and/or scenarios, that facilitate a conversation, otherwise known as a financial interaction, which is related to financial behaviors of the user.
An example of a conversation or communication with the client device 102 could be providing a set of voice outputs from the dialogue component 116 asking the client to review a financial condition and offering as a stimulus a way to improve a financial measure that can be shared with a financial server or third party for greater reward, such as a better credit rating, better financial terms, investment advice, management options, and the like. Thus, the client can better improve a financial condition through analysis of behaviors that includes explicit and/or implicit indication of a personality, belief, discipline, knowledge, and the like, which can accompany behavior indications related to financial transactions and behavior related to recommendations provided to the user, as well as a correspondence measure of how well the client behaves toward the recommendations provided.
For example, from tracking a financial transaction (e.g., a purchase), the dialogue component 110 can suggest to the user to assess a financial condition through questions and/or options for recommendations. Choosing to not engage in the conversation or dialogue exchange would not necessarily hurt a financial measure of the client, but deciding to engage in communication and analysis of behavior and attitudes toward finances could alone aid third parties (e.g., bank or lending institution) to take greater risk or liability with the client. The client could communicate various spending plans, behavior or personality assessments, etc. through conversation with the dialogue component 116. As such, explicit and implicit knowledge about the client's behavior can be determined together with tracking actually exhibited behaviors over time that are related to finances. As with a client device (e.g., a mobile phone, etc.), the client can receive assistance with financial knowledge, and analysis of finances continuously to better aid the client in increasing knowledge through educational modules with the dialogue component 116, attitudes towards finances, and also receive a dynamic financial planning, in which together or separately can contribute to aiding the client in financial goal setting and spending planning.
The dialogue generated can be between the network system 110 and the client device 102, in which live interaction can occur between at least one user and with the dialogue component 116. The dialogue component 116 can facilitate dialogue through various means, such as via live interaction among two parties, a voice generated interaction, key pad interaction, chat interaction and/or interaction with various forms, questionnaires, responses, recommendations, etc., in which advice or suggestions provided to the client are then tracked, such as via a digital wallet, bank account aggregators, and other such information sources of financial data related to the client's behavior. A set of dialogues or communications can be dynamically adapted by the networked system 110 in order to learn and encourage the user's behaviors.
In one example, a user interacts with the networked system 110 via the client device 102 through a discussion, which can be operated by the dialogue component 116 by a dynamic set of processes or logic that learns and adapts conversational outputs with the user from an initial learning process or set of dialogues. The dialogue component 116 can dynamically respond to various responses, answers, statements, etc., provided, as well as through actual financial behaviors of the user, such as recent transactions, savings, debits and credits, rent payments and any other such financial related behavior associated with the client via the client device 102. The responses from the dialogue component 116 can be recommendations or advice that includes options for improving the client's financial condition, such expenditure planning, investment opportunities (e.g., a better savings account, money market account, Certificate of Deposit, checking account being offered, better credit card deals that can have various types of rewards being offered for using the card, and the like). For example, a question could be provided that is a closed ended question (e.g., eliciting yes or no answers), such as “Would you like to determine a financial score for credit based on your behavior, receive a lower interest rate on a credit card, or register for auto-pay for one or more bills?” Other types of questions or options could also be provided to provide a set of financial recommendations and to indicate a user's behavior in response to the recommendations. Based on how the user follows a recommendation, suggestion and/or, otherwise, and advice, the system 100 is configured to determine a financial score.
For example, the dialogue component 116 can operate to conduct a personality test, which is a questionnaire or other standardized instrument designed to reveal aspects of an individual's character or psychological makeup in relation to financial health. Since early efforts of these test for selection into militaries were used, a wide variety of personality tests have been developed, such as the Myers Briggs Type Indicator (MBTI), the Minnesota Multiphasic Personality Inventory (MMPI), and a number of tests based on the Five Factor Model of personality. Personality tests are used in a range of contexts, including individual and relationship counseling, career planning, and employee selection and development. Psychological tests, like many measurements of human characteristics, can be interpreted in a norm-referenced or criterion-referenced manner. Norms are statistical representations of a population. A norm-referenced score interpretation compares an individual's results on the test with the statistical representation of the population. In practice, rather than testing a population, a representative sample or group can be tested in order to generate the testing. This provides a group norm or set of norms. One representation of norms is the Bell curve (also called “normal curve”). Norms are already available for standardized psychological tests, allowing for an understanding of how an individual's scores compare with the group norms. Norm referenced scores are typically reported on the standard score(z) scale or a rescaling of it, and can be determined from the communications indications or response inputs from the client via the dialogue component 116.
In addition, the dialogue component 116 can provide options or recommendations in response to questions (such as open or closed ended questions, scenario options, data fields, questions related to various psychological analysis or assessments (e.g., Myers Briggs testing, MMPI, etc., to further facilitate an interaction about a client's finances for determining key indicators to the client's behavior. For example, a question, such as “Would the client like to provide savings in a savings account?”, “From what account would the client like to transfer money to a savings account?”, “What frequency would the client like to transfer money to a savings account?” and other such financially related questions or options could be generated by the dialogue component 116. Because behaviors, such as a client's financial behavior, can be a product of various beliefs, habits, and experiences, as well as abilities and means, the interaction is facilitated to gauge these sets of behaviors from indications of the client's behavior. Once an overall profile or assessment is determined with indications about a client's financial behavior, recommendations or advice can be further given for modifying the behavior, and a financial score can be determined in response to actions related to the recommendations and/or the communications exchanged. Additionally, references, tutorials, or other educational options can be suggested to the client device 102 for further reading or as information to modify beliefs, habits or experiential knowledge that can drive behavior.
In one embodiment, a financial score is presented to the client device from the conversation and in accordance with the various indications or key indicators that are determined from the dialogue. The dialogue component 116 is configured to receive a set of inputs based on the financial interactions, in which the set inputs can include key indications of whether or how the client has behaved according to various behavioral criteria, such as following the advice, and/or in what ways the client has followed the advice or not. The communications exchanged between the client device and the dialogue component 116 can be evaluated from a voice input, a text input, and/or a selection input. The inputs or interactions can be further analyzed to ascertain a measure, such as a financial score for the user to view dynamically.
The behavioral analysis component 118 is configured to analyze the data obtained from the client device 102 and/or some other device, component or system (e.g., a digital wallet, bank account aggregators, and the like) during or from the financial interaction facilitated by the dialogue component 116. The behavioral analysis component 118 is configured to identify and/or determine indications such as indications of personality, characteristics, overall attitudes and beliefs related to financial conditions and that are related to the client's financial behavior. The indications can be a set of behavioral indicators related to the client's financial behavior. The behavioral indications are used to make an assessment or objective measure of the client's behavior. The indications or key indicators can be determined and analyzed explicitly through behaviors of the client related to financial transactions and/or implicitly from conversational exchanges with the client, which can thus provide evidence that the client has, has not or in what manner the client has acted with the set of behaviors for sound or healthy financing. For example, the set of behaviors can include skills, abilities, beliefs, knowledge, and the like for the client to have sound or healthy financial behavior. The indications determined or assessed can therefore be negative, positive, or neutral, and can be used to factor a financial score or to measure the client's credit worthiness based on the financial score.
For example, if the networked system 110 can assess the responses provided by the client device 102 for competence to “make payments well,” “savings planning” etc., the behavioral analysis component 118 compares responses received from the client device 102 to an index of possible positive or negative key indicators for competency in making payments well, saving, etc. An example of positive behavioral key indicators can be that the client makes payment obligations each month, pays obligations on time, does not get behind on payments, pays bills immediately, pays entire balance to avoid interest each month, has a predetermined number of bills that are paid (e.g., at least four, and under ten bills), as well as other such financial indications or indicators of various financial conditions that are related to the behavioral criteria of the recommendations, suggestions and/or advice given to the client.
Negative indicators that can be related to a competency for “making payment well” that are analyzed by the behavioral analysis component 118 could be the opposite of the positive indicators, and also include other indicators such as having too many or too few bills to pay. Making a minimum payment only could be a neutral indicator that could elicit a recommendation to double payments with a calculated amount of interest that would be saved to the client device 102. No one indicator or set of indicators are fixed, and any number of indicators related to financial conditions or states of behavior are envisioned to be utilized by the networked system 110.
In another example, the behavioral analysis component 118 can measure competencies for saving, with indicators such as having a savings account, a percentage of savings established, and/or a desire to save as indicated by answers to questions involving open ended, closed ended and/or scenario questions, and/or as indicated by tracking of a digital wallet, a bank aggregator or some other financial transaction system that tracks the user's financial behavior. Various indicators or indications can be useful to indicate a client's behavior since a person could say one thing, but behave differently, especially when a delayed gratification response is low. Scenario questions could be dynamically generated to include certain things a person likes, such as video games, cars, food, etc., which could be presented to the client as part of a financial scenario with choices to purchase one of these likes that are new and available as opposed to more frugal options, such as increasing savings or saving for education.
Various competencies can be analyzed during the financial interaction with the client device 102 and can further include a financial score that is updated dynamically or in real time during the financial interaction as different indicators of the client's behavior toward finances are analyzed. The indications or indicators discussed can be inputs from conversation and/or behavior that provides an indication that a behavior characteristic and/or actual behavior related to a financial transaction is more likely or more than probable inherent to the clients beliefs, attitudes or personal behavior as related to finances. The analysis of the key indicators or, in other words, determined indications can be based on a set of behavioral criteria, such as aspects of various competencies as discussed above. The behavioral criteria can include a matching of the indicators to a score in an index stored in a data store (e.g., data store 124) that corresponds to predefined financial conditions, such as having a savings account, desire to open a savings account, desire and ability to save, choosing to save over choosing to spend on a desired item when confronted with different financial scenarios (not paying bills, paying for education, etc.), generating an expenditure plan, investment plan, retirement plan, and implementation for each. Indicators for each of these criteria and other financial criteria indications can be first elicited through the facilitated financial interaction in the form of recommendations, suggestions or advices that can include questions, open ended or closed ended questions, scenarios, and/or statements that can be rated on a predefined scale according to how the client follows the advice or what options the client follows or behaves according to. For example, the behavioral analysis component 116 can detect that the user exchanges currency while traveling and detects that the conversion rate was not good. The dialogue component 116 can then recommend to the user to exchange his currency at a different place. If indications are detected that the user ignored the advice, the system 100 can then downgrade the user's score. In another example, the behavioral analysis component 118 can detect that the user did not pay his credit card balance in full and thus will need to pay a higher interest rate. The system 100 via the dialogue component 116 can inform the client (e.g., the client device 102) and ask the client if he wants to be reminded next time, as well as provide further options such as setting up auto-pay and/or other financial recommendations. According, to the client's behavior a financial score is upgraded or downgrades. For example, if the client follows the advice, his score can be upgraded based on how the client responds and/or to what advice the client follows or does not follow.
Each indicator provided by the client and ascertained by the behavioral analysis component 118 can be looked up in an index and matched for a score. The scoring component 120 is configured to generate a financial score based on the set of key indicators of financial behavior, such as did the client follow a recommendation or not, or follow some other course of action that demonstrates sound or healthy financial responsibility. The financial score for example can be a combination of scores that correspond to one or more indicators. For example, the scores can be summed together and weighted based on other indicators and/or based on the number of other categories of indicators that have been determined. Throughout the financial interaction, as more indicators for various types of financial related behaviors/competencies are determined, the score can be altered and dynamically generated by the scoring component. Thus, the client device 102 is able to view or receive a financial score throughout the financial interaction to show how behavior and/or behavior changes influence financial health.
In one embodiment, the financial scores can be determined from a combination of predefined scores matching different financial conditions, which can be pre-weighted. For example, rating a behavior that indicates a low belief in saving money can be set to indicate a low financial score. The financial score can be based on a scale that can be similar to the scale for a credit score or can be based on a different range of numbers, which can have various ranges therein corresponding to excellent, good, mediocre, bad and/or terrible financial behavior. The scoring component 120 is operable to determine and provide to the client device 102 a score based on one indicator and an updated score based on other indicators that are determined throughout the financial interaction.
In one embodiment, the networked system 110 is operable to interpolate the financial score where an indicator is provided of financial condition and there is no matching score within an index for a particular indicator. For example, where a client provides input indicating a desire to save, but the client provides a mixed answer where either conflicting indicators are provided or there is no score indexed to the indicator, then the financial score can be interpolated. For example, the scoring component 120 can use a different formula where a response in the financial interaction has too many indictors, conflicting indicators, and/or indicators not matching an indexed score. Rather than adding scores, or sampling matching indexed scores, the scoring component 120 can define a financial score based on the nearest indexed score in the index within a predetermined distance. For example, if a strong desire to save is indicated, but a lack of an ability to save is determined from the responses or behaviors detected, a score could interpolate the strength of the ability as being between the scores for a strong desire and a mediocre desire. Other methods of interpolation can also be used to determine indications of behavior that are not indexed with a matching score such as piecewise constant interpolation, linear interpolation, polynomial interpolation, and other forms of interpolation. This further enables a more dynamic analysis and keeps financial scores related to as many responses as possible during the financial interaction.
In another embodiment, the networked system 110 is operable to generate multiple financial interactions with a client device 102. In some cases, for example, the client device 102 can undergo various financial interactions in order to increase their score or obtain a target score for credit worthiness. In this manner, the financial interactions generated by the dialogue component 116, can operate as tutorials by which a client is able to learn better behaviors that can generate better scores. A user can undergo this process different ways such as by trial and error, a reverse mapping scheme, a chronology of financial scores mapped to a time line of the financial interaction, and/or through other like methods. A reverse mapping, for example, can provide an illustration of sample responses or behaviors within the financial interaction that could generate a target score that the user desires to obtain. For example, where the user answered or behaved in one way, other ways of answering various questions or behaving could be sampled to illustrate how to obtain a better score. While multiple different behaviors, questions, responses and/or answers could be used to calculate a financial score during the course of a financial interaction by the scoring component 120, the reverse mapping could provide various samples of behaviors or answers that could generate a better score or a target score inputted via the client device 102.
In another embodiment, the networked system 110 is operable to generate a chronology of the financial scores that are updated or altered throughout the financial interaction with the user. For example, answers, responses, and/or exchanges generated throughout the financial interaction can be mapped along a time line with corresponding financial scores that are generated in responses to key indicators identified. In this manner, the user can see how certain behaviors affect financial health. Where certain areas of the dialogue are based on certain competencies or certain behaviors, the user can see where weaknesses and/or strengths could be.
Referring now to
The input component 202, for example, is configured to receive a set of inputs based on the financial interaction, the set of inputs including at least one of a voice input, a text input, or a selection input received during the financial interaction that is analyzed for media content to correspond with certain key indicators, such as actions, words or phrases related to a set of behaviors. The input component 202 can include one or more mechanisms in addition to a touch panel that permit a user to input information thereto, such as microphone, keypad, control buttons, a keyboard, a gesture-based device, an optical character recognition (OCR) based mechanism, a joystick, a virtual keyboard, a speech-to-text engine, a mouse, a pen, and/or voice recognition and the like. The client (or user) can input selections or options to follow according to the recommendations provided, such as to set up a savings account, auto pay, and/or other financial options that are presented to the client device 102.
A chat component 204 is configured to transmit and receive at least one of textual dialogue, voice dialogue, video content or image content related to the financial interaction. For example, a user can view various selections, questions, statements, options, scenarios of financial situations, conditions and the like, chat with a live representative, view recommendations or financial advice tips during the interactive financial dialogue generated. The chat component 204 can generate a chat screen in order to facilitate various stimuli in the form of questions and answers sessions that facilitate interaction and enable the networked system 110 to ascertain key indicators regarding the user's behavior, which includes the beliefs, knowledge, experiences that form the behavior in the user. The chat component 204 can generate a chat session that responds dynamically to a user with artificial intelligence logic, such as rule based logic, fuzzy logic and/or other artificial intelligence design. For example, a user can respond with concerns about saving money, and the system could focus questions, scenarios, and the like to generate key indicators in order to measure or rate the behavior and how a credit score would correspond. The credit score, for example, can be determined by the scoring component 120 and be predefined based on the indicators matching conditions in an index with a score. The index scores can be predefined based on real life data from people having similar scores with similar behaviors (i.e., behavioral characteristics) related to financial behavior, or analyzed based on another rating which weights various indicators based on desired behavior and the level in which the behavior is encouraged or discouraged, for example.
The index component 206, for example, is configured to index indicators/indications and a set of index scores related to the indicators analyzed during the financial interaction. The indicators, for example, can be indexed as a set of financial conditions such as saving for an emergency, paying bills on auto pay, paying bills on time, budgeting and/or other financial behaviors, whether positive, negative and/or neutral. These financial conditions and behaviors are related to financial health and can be categorized and/or indexed with a score or weight factor to be used in calculating a financial score. As positive indicators of behavior are determined in the client responses to the recommendations during the interactive dialogue, the score is increased according to the amount of positive impact to a client's credit that the behavior can have, and similarly, decreased with predefined negative indicators. Examples of negative indicators are financing a car without a job, financing a car without any savings, opening a line of credit at a retail store without savings or with multiple other lines of credit, having carried over balances without paying the balance in full, borrowing money on any line of credit without making other payment obligations (e.g., monthly minimum payment, late fees, etc.), and/or other conditions negatively impacting a short term and/or long term financial condition. The behavioral analysis component 118 determines the key identifiers related to various financial conditions from the information provided by the client device 102, a digital wallet, bank account aggregator, and or other such devices, and with the dialogue component 116 can analyze words, phrases, and/or selections provided by the client via the client device that indicate a financial behavior or a financial condition indexed. The index component 206 indexes key identifiers (indications) that match various financial conditions, and via a presentation component 208 the client device 102 can dynamically view financial scores during the course of the financial interaction as various key identifiers are determined and scored by the scoring component 120.
The presentation component 208 is configured to facilitate display of the financial score and alter the displayed financial score during the financial interaction based on a change in the set of key indicators and updated scoring of the scoring component 120. For example, the presentation component 208 is configured to display the financial score including a plurality of financial indicators that include at least one of a financial credit score number or a financial credit grade. A number of scoring indications are envisioned, such as a letter grade, a number (e.g., a credit risk number with the highest number being about 850 and the lowest being about 300, and/or any other number range), as well as quality indications that can be illustrated according to colors (e.g., red different shades to black).
The presentation component 208 is further configured to display a chronology of the plurality of financial/key indicators that are calculated during the financial interaction. For example, a series of behaviors over time, which can be in connection with recommendations, suggestions or advice form questions, scenarios and/or statements can be generated to dialogue with the client device 102. In addition, each interaction in the series can be generated with time lines along with the financial scores at each of the time lines. As scores are altered, and/or updated, the presentation component 208 displays or communicates to the client device 102 the updated or altered score. Therefore, the presentation component 208 is operable to generate a dynamic presentation of financial scores to a user during the financial interaction.
Referring now to
The computing device 302 is operable to receive inputs during and from a conversation, exchange and/or, in other words, a financial interaction 304 related to a set of financial behaviors. The financial interaction 304, as discussed herein, can be a conversation that is carried out live via text, instant messaging, voice over telephone, and the like, in which the voice input from a client on a client device (e.g., mobile device, phone, computing device, etc.) is converted to words and/or phrases in text by the dialogue component 116 and/or analyzed for indicators of behavior by the behavioral analysis component 118. Additionally or alternatively, the interaction 304 between client device and the computing device 302 can be via a text exchange, instant messaging exchange, or any conversational dialogue that includes data being exchanged, in which a second data is in response to a first data and so on. The financial interaction 304 is a dynamic interaction that is continuous during a user session comprising a plurality responses and exchanges with the computing device 302, which is operationally similar to the networked device 110 discussed above, but can include a mobile phone, a computing device, a mobile device, a handheld device and the like device operable to interact directly with the client rather than via a different client device. The financial interaction 304 facilitated by the dialogue component 110 to drive and continue conversation, exchange, or, in other words, dialogue regarding a set of financial behaviors based on user responses, such as behavior in accordance with recommendations or not. The dialogue component 116 can alter conversational exchange towards a user interest in order to drive conversation towards areas of concern, or where improvement in a financial condition could be. For example, advice about home ownership could get a response about savings, in which the dialogue component 116 can begin exchanges about savings by questioning the user if he or she would like to interact about savings first or another topic for evaluating a financial score.
The set of financial behaviors can include any number of financial conditions, in which a client can provide response to and/or about via an answer, a closed ended statement (yes, no), a declarative statement of fact and the like. The index component 206 indexes various financial conditions based on key indicators, which can be behaviors including words, phrases in audio and/or text that include a statement or indication of a belief or tendency to adhere to at least one financial condition indexed as well as tracked or detected behaviors as to whether recommendations were followed. The words and/or phrases are evaluated by the behavioral analysis component 118 for indicators of financial conditions, which can be indexed by the index component 206. The words and/or phrases, for example, can be in response to the recommendations or selection options provided to the user. In situations where statements, words and/or phrases, are not pre-indexed, but are deemed related to a financial behavior, by a statement, words or phrases, a closest approximate evaluation is performed by the behavioral analysis component 118 and the index component 206 such as by an interpolation. In addition, the index component 206 can learn conditions or indicators to index via a learning component. Scores can be interpolated, then later adjusted and stored based on an external assessment of the financial interaction or session.
The computing device 302 via the scoring component 120 generates a display 306 of the various topics discussed during the financial interactions, as well as an ongoing financial score that gets updated, altered or modified during the financial interaction based on the set of behaviors determined during the course of the interaction. For example, the behavioral analysis component 118 determines indicators (indications) such as detected behaviors, words or phrases that indicate a behavior to a recommendation as provided via the dialogue component 116. The key indicators determined provide indications of the set of beliefs related to the financial interactions 304. The indictors can be used to determine a score, such as a financial score during the financial interaction 304, which is dynamically displayed throughout the interaction in the display 306 for a user to observe. The display 306 can be a touch screen display for selections to be received via a touch, and/or any type of display communicatively coupled to the computing device 302 or to an external device that is in communication with the computing device 302.
The computing device 302 includes the credit risk component 308 that is configured to determine a correlation between the set of key indicators and a plurality of financial behaviors external to the facilitated financial interaction, and to determine a set of credit worthiness indicators based on the correlation. For example, the set of credit worthiness indicators include at least one of an interest rate or a credit worthiness score, such as a credit rating or credit risk indication. In other words, the amount of correlation (e.g., a correlation degree) between the financial scores determined from the financial interactions and actual behaviors determined from actual credit data, payments history, credit history, etc., for example, is factored into determining a credit worthiness score for giving a loan recommendation or other financial instrument. Various data sources, including the data store 124 and other internal and external data stores, can be employed for determining the credit worthiness, such as credit reports, or agencies/bureaus with private data pertaining to the client's credit score rating (e.g., TransUnion, Equifax, and Experion). Information about the client is searched with key search words (e.g., name, data of birth, email addresses, and the like). The data is collected and stored in a profile, such as a profile memory (not shown). The profiles of each client contain client characteristic data that includes information collected over the any number of data bases. The credit risk component 308 is operable to determine a credit worthiness score based on external data in combination with the financial score determined from the set of financial interactions analyzed by the computer device, or, in other words, the networked system discussed herein.
The feedback component 310 of the computer device 302 is configured to generate advice content related to behavioral responses received or detected during the financial interaction based on the set of key indicators. For example, advice on spending with different consequences that affect the financial score from the scoring component 120 can be provided by the feedback component 310 in response to input received during the financial interaction 304. For example, a conversation or a portion of the financial interaction 304 could include the subject of savings, and based on the responses received, the feedback component 310 generates a list of ways to save that can be elaborated on according to further inputs received. A question could be provided, for example, whether the client believes saving is a top priority or goal, and a “yes” answer to setting up a savings account or other type savings account could incrementally raise the financial score of the client as dynamically displayed in the display 306. In response to the yes, the computing device 302 could inquire further into what the client would like to save for. If the answer is beer this weekend, or some other short term benefit, a decrement to the user's score could be attributed to the score as a result of the behavior of uncontrolled delayed gratification associated with finances. A more long term savings plan would hint towards a more long term thinking client, which would be better prepared to invest money with, such as for a loan or the like. A series or set of behaviors determined provide a more accurate financial score.
Additionally, the feedback component 310 is configured to generate warnings that a certain type of move could detrimentally affect the financial score, in response to the score being lowered by a response that is a predefined difference. For example, in response to the client indicating that he or she would like to mortgage their home under an 80/20 loan/principal ratio, the system could generate that this would drop their financial score from 600 to 500, or some other difference in a range of scores.
An advantage of assessing financial risk or recommendation for credit on publicly available data is providing wider latitude to consumers needing such instruments. In particular, small business loans can be based on factors that do not require strict criteria, but can be assessed more heavily based on a person's behavior and behavioral modifications, which is ascertained from financial interactions with the customer.
Referring now to
The indexing component 206 is operable to learn various financial conditions based on different financial interactions with other clients and/or with the same client. In situations where behaviors are not pre-indexed, but are deemed related to a financial behavior a closest approximate evaluation is performed by the behavioral analysis component 118.
The index component 206 can categorize and index new financial conditions, and during the session determine a score based on an interpolation made by the interpolation component 402. For example, where saving for education may be a good condition that provides an increment of ten to fifteen points to the financial score, saving for a movie could be something that is not indexed, but given a score of close to ten since saving is a positive behavioral financial condition, although it is not a long term item. Therefore, an interpolated score could be determined by the interpolation component 402 based on something in between saving and not saving at all, or saving and saving for education, which is a more long term thought process requiring greater discipline than simply saving for anything.
Referring now to
The advice component 502 communicates further advice related to the behavior determined during the financial interactions. For example, various warnings, tips, hints, suggestions and/or recommendations can be generated to a user based on behavioral responses received. The financial profile component 504 is operable to generate a profile related to a certain client from the financial interaction and store the data profile in a data store 124, for example. The financial profile component 504 is configured to retrieve a set of search results from data sources in response to a search query, which can be a credit score, a credit history, such as a credit report from a public or private data base. The financial profile component 504 is configured to generate the client profile with metadata (e.g., attributes or characteristics) associated with the client and to rank the metadata according to a level of validity and/or relevance to the client. Characteristics or attributes are assimilated as metadata associated with the client profile in storage, for example, and can be from data sources that can include virtually any open source or publicly available sources of information, as well as private sources, including, but not limited to websites, search engine results, social networking websites, online resume databases, job boards, government records, online groups, payment processing services, online subscriptions, and so forth. In addition, the data sources can include private databases, such as credit reports, loan applications, and so forth.
In one embodiment, the credit risk component 308 communicates with the financial profile component 504 to obtain information that is external to the financial interaction and to evaluate a correlation degree between the information on behavior obtained during the interaction and the profile information from the financial profile component 504. Based on the correlation, the credit risk component can calculate a credit worthiness score.
The advice component 502 and the financial profile component 504 are communicatively coupled to a marketing component 506. Based on predetermined criteria such as information obtained from official data sources and information obtained from publicly available data sources, the marketing component 506 can output recommendations for providing credit, a loan or other financial instrument to a client, such as via a marketing plan or strategy. For example, where a life experience can make one marketing strategy for a loan discouraging to a client, another strategy could be used to portray financial instruments in a better light. Rather than only basing recommendations on financial data, the marketing component 506 determines recommendation on publicly available data such as the interest, abilities, skills, temperament, associations and character aspects of the client, for example.
Referring now to
The reverse mapping component 604 can generate a reverse order or a reverse mapping of the financial interaction in order to demonstrate to a client how the client could obtain a target score, which could be different from the actual financial score determined from the interaction. In this manner, the financial interactions generated by the dialogue component 116, can operate as tutorials by which a client is able to learn better behaviors that can generate better scores. A user can undergo this process different ways such as by trial and error, a reverse mapping scheme, a chronology of financial scores mapped to a time line of the financial interaction, and/or through other like methods. The reverse mapping component 604 is configured to generate the reverse mapping, for example, that provide an illustration of sample responses within the financial interaction could generate a target score that the user desires to obtain. The reverse mapping component 604 receives a target score and based on the financial interaction, or an upcoming future financial interaction with the user is configured to generate set of responses that would enable a better score. For example, where the user answered one way, other ways of answering various questions could be sampled to illustrate how to obtain a better score, which can be mapped in a reverse hierarchy of the financial interaction. While multiple different questions, responses and/or answers could be used to calculate a financial score during the course of a financial interaction by the scoring component 120, the reverse mapping could provide various samples or answers that could generate a better score or a target score inputted via the client.
While the methods described within this disclosure are illustrated in and described herein as a series of acts or events, it will be appreciated that the illustrated ordering of such acts or events are not to be interpreted in a limiting sense. For example, some acts may occur in different orders and/or concurrently with other acts or events apart from those illustrated and/or described herein. In addition, not all illustrated acts may be required to implement one or more aspects or embodiments of the description herein. Further, one or more of the acts depicted herein may be carried out in one or more separate acts and/or phases.
An example methodology 700 for implementing a method for a system is illustrated in
At 704, a set of key indicators are determined related to the set of financial behaviors. The key indicators, for example, can be key words or phrases that are identified or determined throughout the financial interaction. The determining can be based on a set of behavioral criteria that, for example, includes a matching of financial conditions having scores that are weighted or predefined with the key indicator. For example, the key indicators can correspond with a set of conditions that are indexed, such as statements or words pertaining to financial categories, situations, topics, and/or other conditions related to financial behavior.
At 706, a financial score is generated that is based on the set of key indicators. For example, certain indicators can be indexed or tied to a positive score that increments a client's score, while other indicators could be more negative and cause a decrement to the financial score.
At 708, a display of the financial score is facilitated. The displaying can be dynamically during the financial interaction and updated dynamically throughout the course of the interaction.
An example methodology 800 for implementing a method for a system in accordance with various embodiments herein is illustrated in
The method 800, for example, provides for a system to facilitate a dialogue with a client and generate financial score(s) during the dialogue. At 802, a financial interaction of financial communications related to a set of financial behaviors is facilitated. At 804, a financial score is presented based on at least one financially related indication or key indicator received to the set of financial communications or exchanges that occur during the financial interaction. At 806, the financial score is adjusted based on at least one different indication/key indicator received in response to the set of financial communications.
One of ordinary skill in the art can appreciate that the various non-limiting embodiments of the shared systems and methods described herein can be implemented in connection with any computer or other client or server device, which can be deployed as part of a computer network or in a distributed computing environment, and can be connected to any kind of data store. In this regard, the various non-limiting embodiments described herein can be implemented in any computer system or environment having any number of memory or storage units, and any number of applications and processes occurring across any number of storage units. This includes, but is not limited to, an environment with server computers and client computers deployed in a network environment or a distributed computing environment, having remote or local storage.
Distributed computing provides sharing of computer resources and services by communicative exchange among computing devices and systems. These resources and services include the exchange of information, cache storage and disk storage for objects, such as files. These resources and services also include the sharing of processing power across multiple processing units for load balancing, expansion of resources, specialization of processing, and the like. Distributed computing takes advantage of network connectivity, allowing clients to leverage their collective power to benefit the entire enterprise. In this regard, a variety of devices may have applications, objects or resources that may participate in the shared shopping mechanisms as described for various non-limiting embodiments of the subject disclosure.
Each computing object 910, 912, etc. and computing objects or devices 920, 922, 924, 926, 928, etc. can communicate with one or more other computing objects 910, 912, etc. and computing objects or devices 920, 922, 924, 926, 928, etc. by way of the communications network 940, either directly or indirectly. Even though illustrated as a single element in
There are a variety of systems, components, and network configurations that support distributed computing environments. For example, computing systems can be connected together by wired or wireless systems, by local networks or widely distributed networks. Currently, many networks are coupled to the Internet, which provides an infrastructure for widely distributed computing and encompasses many different networks, though any network infrastructure can be used for exemplary communications made incident to the shared shopping systems as described in various non-limiting embodiments.
Thus, a host of network topologies and network infrastructures, such as client/server, peer-to-peer, or hybrid architectures, can be utilized. The “client” is a member of a class or group that uses the services of another class or group to which it is not related. A client can be a process, i.e., roughly a set of instructions or tasks, that requests a service provided by another program or process. The client process utilizes the requested service without having to “know” any working details about the other program or the service itself.
In client/server architecture, particularly a networked system, a client is usually a computer that accesses shared network resources provided by another computer, e.g., a server. In the illustration of
A server is typically a remote computer system accessible over a remote or local network, such as the Internet or wireless network infrastructures. The client process may be active in a first computer system, and the server process may be active in a second computer system, communicating with one another over a communications medium, thus providing distributed functionality and allowing multiple clients to take advantage of the information-gathering capabilities of the server. Any software objects utilized pursuant to the techniques described herein can be provided standalone, or distributed across multiple computing devices or objects.
In a network environment in which the communications network 940 or bus is the Internet, for example, the computing objects 910, 912, etc. can be Web servers with which other computing objects or devices 920, 922, 924, 926, 928, etc. communicate via any of a number of known protocols, such as the hypertext transfer protocol (HTTP). Computing objects 910, 912, etc. acting as servers may also serve as clients, e.g., computing objects or devices 920, 922, 924, 926, 928, etc., as may be characteristic of a distributed computing environment.
As mentioned, advantageously, the techniques described herein can be applied to a number of various devices for employing the techniques and methods described herein. It is to be understood, therefore, that handheld, portable and other computing devices and computing objects of all kinds are contemplated for use in connection with the various non-limiting embodiments, i.e., anywhere that a device may wish to engage on behalf of a user or set of users. Accordingly, the below general purpose remote computer described below in
Although not required, non-limiting embodiments can partly be implemented via an operating system, for use by a developer of services for a device or object, and/or included within application software that operates to perform one or more functional aspects of the various non-limiting embodiments described herein. Software may be described in the general context of computer-executable instructions, such as program modules, being executed by one or more computers, such as client workstations, servers or other devices. Those skilled in the art will appreciate that computer systems have a variety of configurations and protocols that can be used to communicate data, and thus, no particular configuration or protocol is to be considered limiting.
Although not required, embodiments are described in the general context of “computer readable instructions” being executed by one or more computing devices. Computer readable instructions may be distributed via computer readable media (discussed below). Computer readable instructions may be implemented as program modules, such as functions, objects, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types. Typically, the functionality of the computer readable instructions may be combined or distributed as desired in various environments.
In other embodiments, device 1012 may include additional features and/or functionality. For example, device 1012 may also include additional storage (e.g., removable and/or non-removable) including, but not limited to, magnetic storage, optical storage, and the like. Such additional storage is illustrated in
The term “computer readable media” as used herein includes computer storage media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions or other data. Memory 1018 and storage 1020 are examples of computer storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by device 1012. Any such computer storage media may be part of device 1010.
Device 1012 may also include communication connection(s) 1026 that allows device 1010 to communicate with other devices. Communication connection(s) 1026 may include, but is not limited to, a modem, a Network Interface Card (NIC), an integrated network interface, a radio frequency transmitter/receiver, an infrared port, a USB connection, or other interfaces for connecting computing device 1012 to other computing devices. Communication connection(s) 1026 may include a wired connection or a wireless connection. Communication connection(s) 1026 may transmit and/or receive communication media.
The term “computer readable media” as used herein includes computer readable storage media and communication media. Computer readable storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions or other data. Memory 1018 and storage 1020 are examples of computer readable storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by device 1010. Any such computer readable storage media may be part of device 1012.
Device 1012 may also include communication connection(s) 1026 that allows device 1012 to communicate with other devices. Communication connection(s) 1026 may include, but is not limited to, a modem, a Network Interface Card (NIC), an integrated network interface, a radio frequency transmitter/receiver, an infrared port, a USB connection, or other interfaces for connecting computing device 1012 to other computing devices. Communication connection(s) 1026 may include a wired connection or a wireless connection. Communication connection(s) 1026 may transmit and/or receive communication media.
The term “computer readable media” may also include communication media. Communication media typically embodies computer readable instructions or other data that may be communicated in a “modulated data signal” such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” may include a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal.
Device 1012 may include input device(s) 1024 such as keyboard, mouse, pen, voice input device, touch input device, infrared cameras, video input devices, and/or any other input device. Output device(s) 1022 such as one or more displays, speakers, printers, and/or any other output device may also be included in device 1012. Input device(s) 1024 and output device(s) 1022 may be connected to device 1012 via a wired connection, wireless connection, or any combination thereof. In one embodiment, an input device or an output device from another computing device may be used as input device(s) 1024 or output device(s) 1022 for computing device 1012.
Components of computing device 1012 may be connected by various interconnects, such as a bus. Such interconnects may include a Peripheral Component Interconnect (PCI), such as PCI Express, a Universal Serial Bus (USB), firewire (IEEE 1394), an optical bus structure, and the like. In another embodiment, components of computing device 1012 may be interconnected by a network. For example, memory 1018 may be comprised of multiple physical memory units located in different physical locations interconnected by a network.
Those skilled in the art will realize that storage devices utilized to store computer readable instructions may be distributed across a network. For example, a computing device 1030 accessible via network 1028 may store computer readable instructions to implement one or more embodiments provided herein. Computing device 1012 may access computing device 1030 and download a part or all of the computer readable instructions for execution. Alternatively, computing device 1012 may download pieces of the computer readable instructions, as needed, or some instructions may be executed at computing device 1012 and some at computing device 1030.
Various operations of embodiments are provided herein. In one embodiment, one or more of the operations described may constitute computer readable instructions stored on one or more computer readable media, which if executed by a computing device, will cause the computing device to perform the operations described. The order in which some or all of the operations are described should not be construed as to imply that these operations are necessarily order dependent. Alternative ordering will be appreciated by one skilled in the art having the benefit of this description. Further, it will be understood that not all operations are necessarily present in each embodiment provided herein.
Moreover, the word “exemplary” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as advantageous over other aspects or designs. Rather, use of the word exemplary is intended to present concepts in a concrete fashion. As used in this application, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X employs A or B” is intended to mean any of the natural inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, then “X employs A or B” is satisfied under any of the foregoing instances. In addition, the articles “a” and “an” as used in this application and the appended claims may generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form.
Also, although the disclosure has been shown and described with respect to one or more implementations, equivalent alterations and modifications will occur to others skilled in the art based upon a reading and understanding of this specification and the annexed drawings. The disclosure includes all such modifications and alterations and is limited only by the scope of the following claims. In particular regard to the various functions performed by the above described components (e.g., elements, resources, etc.), the terms used to describe such components are intended to correspond, unless otherwise indicated, to any component which performs the specified function of the described component (e.g., that is functionally equivalent), even though not structurally equivalent to the disclosed structure which performs the function in the herein illustrated exemplary implementations of the disclosure. In addition, while a particular feature of the disclosure may have been disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular application. Furthermore, to the extent that the terms “includes”, “having”, “has”, “with”, or variants thereof are used in either the detailed description or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.”
The subject patent application is related to co-pending U.S. patent application Ser. No. 13/615,053, filed on Sep. 13, 2012, entitled “Behavioral Based Score,” which is hereby incorporated by reference in its entirety.
