Continuing the above example, the dashboard may allow the user to view the balances for each of the resource accounts held with each of the financial institutions. Furthermore, the system may provide an entire view of the flow of resources into and/or out of each of the resource accounts across all payment rails and/or channels (e.g., debit, ACH, and/or the like). In this way, the unified dashboard allows the system to generate a holistic view of a user's financials in spite of the relevant resource data being spread across a number of disparate servers which may be hosted by various different third party entities.

The dashboard may further be configured to present notifications regarding what a new user can expect in an upcoming timeframe after initializing a new resource account. For instance, a new user may wish to inquire how to set up direct deposits, when they may receive new debit cards or checks, and/or the like. In such an embodiment, the dashboard may comprise an interface element that may allow the user to pose the questions (e.g., by inputting text into a text entry field), which may then be answered through an AI-powered assistant.

User Resource Account Initialization Based on User Data

In some embodiments, the system may perform intelligent initialization of a new resource account for the user (e.g., user onboarding) based on analyzing the data associated with the user. In this regard, the system may use information such as biographical data, address information, contact information, and/or the like associated with the user to optimally match the user with certain services and/or products offered by the entity. In this regard, the system may use the data associated with the user to generate a financial portrait of the user and recommend to the user products or services that may be suitable or optimal for the user. For example, the system may detect that the user is currently enrolled in a particular product (e.g., a savings account with a fixed interest rate) with a third party financial institution. Upon detecting that the user is enrolled in such a product, the system may be configured to transmit a notification on the dashboard with an offer for an upgraded product (e.g., a savings account with a higher interest rate). The notification may comprise an interactive element that, when activated by the user (e.g., by clicking on a button or interactable area), may cause a form to be displayed on the dashboard, where the form may be an onboarding form that may have one or more fields that are automatically populated using the aggregated data associated with the user.

In some embodiments, the system may be configured to provide certain recommendations based on a change in status of a user. For instance, if the system detects that the user has moved addresses, the system may be configured to display notifications for offers relevant to the area to which the user has moved (e.g., offers to sign on with partnered utility providers). The system may further be configured to present notifications regarding entity locations to the user (e.g., financial centers associated with the entity) within a predefined distance of the user's new address. The system may further be configured to track one or more life events associated with the user (e.g., moving addresses, finishing education, and/or the like). In such embodiments, the system may be configured to provide a projected timeline and estimation of costs typically incurred by other users who experience such life events.

In some embodiments, the system may continuously prompt the user to input additional information to maintain a constantly updated portrait of the user and/or the user's resource accounts. In an exemplary embodiment, the system may determine that the user has set up automatic payments for certain services or products (e.g., utilities such as water and electricity) but not others (e.g., Internet service). Upon detecting a potential gap in the user portrait, the system may, through the dashboard, prompt the user to indicate whether the user is currently signed up for the missing service. If the user responds in the affirmative, the system may further inquire regarding what payments the user may be making for such a service and subsequently offer the user to port the payments to the entity's systems. If the user once again responds in the affirmative, the system may present a pre-filled onboarding form to the user as described elsewhere herein.

AI-Based or AI-Assisted Recommendations Engine

In some embodiments, the system may generate intelligent recommendations based on the data associated with the user by providing AI-based recommendations with respect to changing a configuration of the user's resource accounts, by pre-populating one or more initialization or onboarding forms based on the pre-existing data, and/or the like. In this regard, the system may analyze the current configuration or settings for each of the resource accounts and offer settings optimization recommendations based on analyzing the configuration or settings. For example, the system may detect that the user is currently enrolled in automatic payments with a resource account hosted by a third party entity. Subsequently, the system may transmit a recommendation (e.g., through the unified dashboard) for the user to port the automatic payments settings from the existing resource account to a new resource account managed by the entity associated with the system described herein. In some embodiments, the system may generate a checklist to be presented on the dashboard such that the user may select (e.g., by checking or unchecking) which services or products that the user wishes to be ported over.

In some embodiments, the AI engine may analyze the historical resource transfer data (e.g., past transactions, transaction labels, transferee information, transaction dates, and/or the like) and proactively provide suggested configuration changes based on analyzing the historical resource transfer data. For instance, the user's transaction history may indicate that the user makes a resource transfer at the same time each month. The system may further review the data associated with the user and determine that a recurring resource transfer is not currently set up for this transaction (e.g., the user manually executes the resource transfer each time). In such embodiments, the system may generate a recommendation to set up a recurring resource transfer based on one or more optimized parameters determined by the AI engine. In this regard, the AI engine may set parameters that may provide the largest benefit to the user (e.g., faster transaction times, ease of use, and/or the like) and/or conforms to user defined preferences (e.g., resource amount limits, timeframe-based restrictions, and/or the like).

In some embodiments, the dashboard may be configured to present an AI-powered digital advisor that may provide AI-generated recommendations in real time. In this regard, the system may monitor the actions taken by the user within the dashboard (e.g., text inputs, mouse clicks, touchscreen taps, voice commands, and/or the like) and, based on monitoring the actions, generate a prediction regarding the intent of the user within the dashboard. For instance, the system may detect that the user is attempting to execute a manual resource transfer that the system has identified may be a recurring transfer. In such an embodiment, upon detecting that the user is attempting to manually execute the resource transfer, the digital advisor may present a notification to the user (e.g., within a frame or window of the dashboard) prompting the user to indicate whether the user wishes to set up a recurring resource transfer. If the user responds in the affirmative (e.g., by interacting with a button or selectable area of the notification), the system may present a form to the user on the dashboard for setting up the recurring resource transfer. In some embodiments, one or more of the fields within the form may be pre-filled based on the AI engine analyzing the historical resource transfer data associated with the user.

The system may further be configured to intelligently recommend certain products or services based on the user portrait. For instance, the system may, based on the inputs and outputs of resources through the user's resource accounts, determine that the user receives payouts on an on-demand basis. In such embodiments, the system may recommend a payout date that maximizes the amount of resources that may be paid out to the user's resource accounts. In some embodiments, the system may further analyze the inputs and outputs of resources to offer transaction smoothing (e.g., normalizing payments over time).

Resource Account and Data Labeling

In some embodiments, the system may be configured to allow the user to designate a label for each resource account within the dashboard (e.g., by entering a text-based label into a text entry field associated with each resource account). Upon receiving a label from the user, the system may use a natural language processing (“NLP”) based algorithm to parse the text input and generate recommendations based on the label. For instance, the user may designated a particular resource account as a caregiver account. In such an embodiment, the system may modify the initialization/onboarding questions that may be posed to the user and subsequently provide specific recommendations related to the particular label (e.g., if the resource account is a caregiver account, the system may recommend that the user sets up a power of attorney).

Bidirectional Communication Channel with Third Party Systems

As described above, in some embodiments, the system may be configured to push data to and/or retrieve data from the various third-party computing systems that may store data associated with the user. In some embodiments, the system may further be configured, for the user's convenience, to push data to and/or retrieve data from other types of third party systems that may be associated with the user. In an exemplary embodiment, upon detecting that the user has moved addresses, the system may, upon receiving authorization from the user, to push the new address information to various third party entities associated with the user (e.g., government agencies, new employers, utility or other service providers, and/or the like).

In some embodiments, the system may further use the AI engine to detect anomalies and/or opportunities to optimize the user's resource accounts based on analyzing the resource account data. For instance, the system may analyze the transaction history of the user and determine that duplicate transactions have been executed for a particular subscription service or may detect that a better offer (e.g., a better rate) may be applicable to the user. In such embodiments, the system may be configured to push a notification to the third party entities associated with such services to correct the errors and/or apply for the better offer on behalf of the user.

Security, Data Privacy, and Detection of Unauthorized Activity

In some embodiments, the system may analyze the resource related activity associated with the user across all resource accounts using the AI engine to detect potential unauthorized activity. Upon detecting the potential unauthorized activity, the system may present a notification on the dashboard regarding the potential unauthorized activity that prompts the user to confirm whether the activity was authorized. For example, the system may detect that an account was opened at a particular third party financial institution with the same name as the user. In this way, the system may provide for enhanced resource account security with respect to all of the user's resource accounts across all entities.

The system may further be configured to allow the user to fine-tune permissions with respect to what portions of data associated with the user is shared with the system. In this regard, the user may allow the user to select and/or unselect the data that is shared with the system (e.g., the user may wish to share information regarding one resource account, but not another). Furthermore, the system may use the AI engine to predict the preferences of the user with respect to the level of engagement with fine-tuning the data privacy permissions. For instance, based on detecting that the user often provides customized user preferences and/or settings, the system may present a granular list of data privacy settings to the user. On the other hand, if the system detects that the user often proceeds with standardized settings, the system may provide a simplified list of data privacy settings to the user.

Integrated Permissions Platform/Centralized Authentication

In some embodiments, the system may provide an integrated platform with shared permissions with each of the entities with which the user has a relationship. In particular, the system may generate a shared authentication credential that may be used across multiple institutions that may be used to authorize resource account linking and/or data sharing on an ongoing basis. In this regard, the shared authentication credential may be a secure token, certificate, private key, and/or the like that may be used to authenticate the user across multiple different platforms. By using the shared authentication credential, the system may prevent the need for the user to log in individually to each resource account that the user wishes to link to the system.

FIGS. 1A-1C illustrate technical components of an exemplary distributed computing environment 100 for the system for initialization of user resource accounts through electronic data monitoring of networked servers. As shown in FIG. 1A, the distributed computing environment 100 contemplated herein may include a system 130, an end-point device(s) 140, and a network 110 over which the system 130 and end-point device(s) 140 communicate therebetween. FIG. 1A illustrates only one example of an embodiment of the distributed computing environment 100, and it will be appreciated that in other embodiments one or more of the systems, devices, and/or servers may be combined into a single system, device, or server, or be made up of multiple systems, devices, or servers. For instance, the functions of the system 130 and the endpoint devices 140 may be performed on the same device (e.g., the endpoint device 140). Also, the distributed computing environment 100 may include multiple systems, same or similar to system 130, with each system providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system).

In some embodiments, the system 130 and the end-point device(s) 140 may have a client-server relationship in which the end-point device(s) 140 are remote devices that request and receive service from a centralized server, i.e., the system 130. In some other embodiments, the system 130 and the end-point device(s) 140 may have a peer-to-peer relationship in which the system 130 and the end-point device(s) 140 are considered equal and all have the same abilities to use the resources available on the network 110. Instead of having a central server (e.g., system 130) which would act as the shared drive, each device that is connect to the network 110 would act as the server for the files stored on it. In some embodiments, the system 130 may provide an application programming interface (“API”) layer for communicating with the end-point device(s) 140.

The system 130 may represent various forms of servers, such as web servers, database servers, file server, or the like, various forms of digital computing devices, such as laptops, desktops, video recorders, audio/video players, radios, workstations, or the like, or any other auxiliary network devices, such as wearable devices, Internet-of-things devices, electronic kiosk devices, mainframes, or the like, or any combination of the aforementioned.

The end-point device(s) 140 may represent various forms of electronic devices, including user input devices such as servers, networked storage drives, personal digital assistants, cellular telephones, smartphones, laptops, desktops, and/or the like, merchant input devices such as point-of-sale (POS) devices, electronic payment kiosks, and/or the like, electronic telecommunications device (e.g., automated teller machine (ATM)), and/or edge devices such as routers, routing switches, integrated access devices (IAD), and/or the like.

The network 110 may be a distributed network that is spread over different networks. This provides a single data communication network, which can be managed jointly or separately by each network. Besides shared communication within the network, the distributed network often also supports distributed processing. The network 110 may be a form of digital communication network such as a telecommunication network, a local area network (“LAN”), a wide area network (“WAN”), a global area network (“GAN”), the Internet, or any combination of the foregoing. The network 110 may be secure and/or unsecure and may also include wireless and/or wired and/or optical interconnection technology.

It is to be understood that the structure of the distributed computing environment and its components, connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed in this document. In one example, the distributed computing environment 100 may include more, fewer, or different components. In another example, some or all of the portions of the distributed computing environment 100 may be combined into a single portion or all of the portions of the system 130 may be separated into two or more distinct portions.

FIG. 1B illustrates an exemplary component-level structure of the system 130, in accordance with an embodiment of the invention. As shown in FIG. 1B, the system 130 may include a processor 102, memory 104, input/output (I/O) device 116, and a storage device 106. The system 130 may also include a high-speed interface 108 connecting to the memory 104, and a low-speed interface 112 connecting to low speed bus 114 and storage device 106. Each of the components 102, 104, 106, 108, and 112 may be operatively coupled to one another using various buses and may be mounted on a common motherboard or in other manners as appropriate. As described herein, the processor 102 may include a number of subsystems to execute the portions of processes described herein. Each subsystem may be a self-contained component of a larger system (e.g., system 130) and capable of being configured to execute specialized processes as part of the larger system.

The processor 102 can process instructions, such as instructions of an application that may perform the functions disclosed herein. These instructions may be stored in the memory 104 (e.g., non-transitory storage device) or on the storage device 110, for execution within the system 130 using any subsystems described herein. It is to be understood that the system 130 may use, as appropriate, multiple processors, along with multiple memories, and/or I/O devices, to execute the processes described herein.

The memory 104 stores information within the system 130. In one implementation, the memory 104 is a volatile memory unit or units, such as volatile random access memory (RAM) having a cache area for the temporary storage of information, such as a command, a current operating state of the distributed computing environment 100, an intended operating state of the distributed computing environment 100, instructions related to various methods and/or functionalities described herein, and/or the like. In another implementation, the memory 104 is a non-volatile memory unit or units. The memory 104 may also be another form of computer-readable medium, such as a magnetic or optical disk, which may be embedded and/or may be removable. The non-volatile memory may additionally or alternatively include an EEPROM, flash memory, and/or the like for storage of information such as instructions and/or data that may be read during execution of computer instructions. The memory 104 may store, recall, receive, transmit, and/or access various files and/or information used by the system 130 during operation.

The storage device 106 is capable of providing mass storage for the system 130. In one aspect, the storage device 106 may be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. A computer program product can be tangibly embodied in an information carrier. The computer program product may also contain instructions that, when executed, perform one or more methods, such as those described above. The information carrier may be a non-transitory computer- or machine-readable storage medium, such as the memory 104, the storage device 104, or memory on processor 102.

The high-speed interface 108 manages bandwidth-intensive operations for the system 130, while the low speed controller 112 manages lower bandwidth-intensive operations. Such allocation of functions is exemplary only. In some embodiments, the high-speed interface 108 is coupled to memory 104, input/output (I/O) device 116 (e.g., through a graphics processor or accelerator), and to high-speed expansion ports 111, which may accept various expansion cards (not shown). In such an implementation, low-speed controller 112 is coupled to storage device 106 and low-speed expansion port 114. The low-speed expansion port 114, which may include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet), may be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.

The system 130 may be implemented in a number of different forms. For example, it may be implemented as a standard server, or multiple times in a group of such servers. Additionally, the system 130 may also be implemented as part of a rack server system or a personal computer such as a laptop computer. Alternatively, components from system 130 may be combined with one or more other same or similar systems and an entire system 130 may be made up of multiple computing devices communicating with each other.

FIG. 1C illustrates an exemplary component-level structure of the end-point device(s) 140, in accordance with an embodiment of the invention. As shown in FIG. 1C, the end-point device(s) 140 includes a processor 152, memory 154, an input/output device such as a display 156, a communication interface 158, and a transceiver 160, among other components. The end-point device(s) 140 may also be provided with a storage device, such as a microdrive or other device, to provide additional storage. Each of the components 152, 154, 158, and 160, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.

The processor 152 is configured to execute instructions within the end-point device(s) 140, including instructions stored in the memory 154, which in one embodiment includes the instructions of an application that may perform the functions disclosed herein, including certain logic, data processing, and data storing functions. The processor may be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor may be configured to provide, for example, for coordination of the other components of the end-point device(s) 140, such as control of user interfaces, applications run by end-point device(s) 140, and wireless communication by end-point device(s) 140.

The processor 152 may be configured to communicate with the user through control interface 164 and display interface 166 coupled to a display 156. The display 156 may be, for example, a TFT LCD (Thin-Film-Transistor Liquid Crystal Display) or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology. The display interface 156 may comprise appropriate circuitry and configured for driving the display 156 to present graphical and other information to a user. The control interface 164 may receive commands from a user and convert them for submission to the processor 152. In addition, an external interface 168 may be provided in communication with processor 152, so as to enable near area communication of end-point device(s) 140 with other devices. External interface 168 may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.

The memory 154 stores information within the end-point device(s) 140. The memory 154 can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units. Expansion memory may also be provided and connected to end-point device(s) 140 through an expansion interface (not shown), which may include, for example, a SIMM (Single In Line Memory Module) card interface. Such expansion memory may provide extra storage space for end-point device(s) 140 or may also store applications or other information therein. In some embodiments, expansion memory may include instructions to carry out or supplement the processes described above and may include secure information also. For example, expansion memory may be provided as a security module for end-point device(s) 140 and may be programmed with instructions that permit secure use of end-point device(s) 140. In addition, secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner.

The memory 154 may include, for example, flash memory and/or NVRAM memory. In one aspect, a computer program product is tangibly embodied in an information carrier. The computer program product contains instructions that, when executed, perform one or more methods, such as those described herein. The information carrier is a computer- or machine-readable medium, such as the memory 154, expansion memory, memory on processor 152, or a propagated signal that may be received, for example, over transceiver 160 or external interface 168.

In some embodiments, the user may use the end-point device(s) 140 to transmit and/or receive information or commands to and from the system 130 via the network 110. Any communication between the system 130 and the end-point device(s) 140 may be subject to an authentication protocol allowing the system 130 to maintain security by permitting only authenticated users (or processes) to access the protected resources of the system 130, which may include servers, databases, applications, and/or any of the components described herein. To this end, the system 130 may trigger an authentication subsystem that may require the user (or process) to provide authentication credentials to determine whether the user (or process) is eligible to access the protected resources. Once the authentication credentials are validated and the user (or process) is authenticated, the authentication subsystem may provide the user (or process) with permissioned access to the protected resources. Similarly, the end-point device(s) 140 may provide the system 130 (or other client devices) permissioned access to the protected resources of the end-point device(s) 140, which may include a GPS device, an image capturing component (e.g., camera), a microphone, and/or a speaker.

The end-point device(s) 140 may communicate with the system 130 through communication interface 158, which may include digital signal processing circuitry where necessary. Communication interface 158 may provide for communications under various modes or protocols, such as the Internet Protocol (IP) suite (commonly known as TCP/IP). Protocols in the IP suite define end-to-end data handling methods for everything from packetizing, addressing and routing, to receiving. Broken down into layers, the IP suite includes the link layer, containing communication methods for data that remains within a single network segment (link); the Internet layer, providing internetworking between independent networks; the transport layer, handling host-to-host communication; and the application layer, providing process-to-process data exchange for applications. Each layer contains a stack of protocols used for communications. In addition, the communication interface 158 may provide for communications under various telecommunications standards (2G, 3G, 4G, 5G, and/or the like) using their respective layered protocol stacks. These communications may occur through a transceiver 160, such as radio-frequency transceiver. In addition, short-range communication may occur, such as using a Bluetooth, Wi-Fi, or other such transceiver (not shown). In addition, GPS (Global Positioning System) receiver module 170 may provide additional navigation- and location-related wireless data to end-point device(s) 140, which may be used as appropriate by applications running thereon, and in some embodiments, one or more applications operating on the system 130.

The end-point device(s) 140 may also communicate audibly using audio codec 162, which may receive spoken information from a user and convert it to usable digital information. Audio codec 162 may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of end-point device(s) 140. Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by one or more applications operating on the end-point device(s) 140, and in some embodiments, one or more applications operating on the system 130.

Various implementations of the distributed computing environment 100, including the system 130