Abstract: A method for using machine learning techniques to analyze past decisions made by administrators concerning account opening requests and to recommend whether an account opening request should be allowed or denied. Further, the machine learning techniques determine various other products that the customer may be interested in and prioritizes the choices of options that the machine learning algorithm determines appropriate for the customer.

Abstract: An improved method and apparatus for determining if a financial transaction is fraudulent is described. The apparatus in one embodiment collects transactions off of a rail using promiscuous listening techniques. The method uses linear programming algorithms to tune the rules used for making the determination. The tuning first simulates using historical data and then creates a matrix of the rules that are processed through the linear programming algorithm to solve for the variables in the rules. With the updated rules, a second simulation is performed to view the improvement in the performance. The updated rules are then used to evaluate the transactions for fraud.

Abstract: A method and apparatus for improving the management of cash and liquidity of an organization utilizing a plurality of currency accounts is described. The improvements optimize the interest earnings for the cash balances in each currency account, and minimizes the expenses related to funding the currency accounts. Machine learning techniques are incorporated to forecast payments, receipts, interest rates and currency exchange rates, and then cash is transferred or borrowed or loaned to fund the payments and utilize available cash.

Abstract: A method and apparatus for improving the management of cash and liquidity of an organization utilizing a plurality of currency accounts is described. The improvements optimize the interest earnings for the cash balances in each currency account, and minimizes the expenses related to funding the currency accounts. Machine learning techniques are incorporated to forecast payments, receipts, interest rates and currency exchange rates, and then cash is transferred or borrowed or loaned to fund the payments and utilize available cash.

Abstract: A unique implementation of a machine learning application for suggesting actions for a user to undertake is described herein. The application transforms a history of user behavior into a set of models that represent user actions given a set of parameters. These models are then used to suggest that users in a payments or banking environment take certain actions based on their history. The models are created using the DensiCube, random forest or k-means algorithms.

Abstract: A method and apparatus for improving the management of cash and liquidity of an organization utilizing a plurality of ledger accounts and a plurality of currency accounts is described. One improvement in the accuracy of the forecasts comes from the uses of individual ledger accounts. The improvements optimize the interest earnings for the cash balances in each currency account and minimizes the expenses related to funding the currency accounts. Machine learning techniques are incorporated to forecast payments, receipts, interest rates, and currency exchange rates, and then the cash is transferred or borrowed or loaned to fund the payments and utilize available cash.

Abstract: A system and method for deconstructing a document is described herein, where the method is an improvement over existing document deconstruction techniques. These improvements increase speed and accuracy by rapidly identifying the vendor in an invoice by splitting the invoice into three regions and performing a perceptual image hashing on each section. Then a hamming distance is used to compare the hash for each section with the hashes of known invoices to identify the vendor who sent the invoice.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.

Abstract: A method and device for providing notification of improper access to secure data on a mobile device. The mobile device detects a request to record content displayed on a display of the mobile device. A determination is then made regarding whether the content that was displayed on the screen when the request to record was received is protected content. If the displayed content was protected, then a third party is notified that a security breach has been detected. A remedial action is also performed regarding the security breach.

Abstract: An apparatus and method for providing an immutable audit trail for machine learning applications is described herein. The audit trail is preserved by recording the machine learning models and data in a data structure in immutable storage such as a WORM device, or in a blockchain. The immutable audit trail is important for providing bank auditors with the reasons for lending or account opening reasons, for example. A graphical user interface is described to allow the archive of machine learning models to be viewed.

Abstract: Disclosed is a method and a system for processing electronic transactions is provided. The system includes an interactive display for displaying a graphical user interface, one or more processing units, and a memory unit for storing one or more programs configured to be executed by the one or more processing units. The graphical user interface includes a top portion and a bottom portion. The one or more programs includes instructions for highlighting an up-arrow on the bottom portion of the graphic user interface demanding to be swipe-up; generating a colored-wave on receiving an interaction through the interactive display; returning the colored-wave back to create the highlighted up-arrow; generating the colored-wave simultaneous to processing of the electronic transaction on receiving a swipe-up; and filling up the graphical user interface completely with the color to indicate the completion of the electronic transaction.

Abstract: A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then perform a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.

Abstract: An improved method and apparatus for determining if a financial transaction is fraudulent is described. The apparatus in one embodiment collects transactions off of a rail using promiscuous listening techniques. The method uses linear programming algorithms to tune the rules used for making the determination. The tuning first simulates using historical data and then creates a matrix of the rules that are processed through the linear programming algorithm to solve for the variables in the rules. With the updated rules, a second simulation is performed to view the improvement in the performance. The updated rules are then used to evaluate the transactions for fraud.

Abstract: Disclosed is a system for facilitating the financial planning of an objective. The system includes a storage unit for storing computer program instructions and a plurality of pre-defined graphs representing financial data sets of previous years, a display unit for displaying processed computer program instructions, a processing unit coupled to the storage unit, and the display unit for processing the computer program instructions. The computer program instructions include a data input computer program instruction, a data category display computer program instruction, a threshold computer program instruction, a data distribution computer program instruction coupled to the data input computer program instructions to allow the user to distribute the financial data sets of a previous year through the stored graphs, a slide computer program instruction and a heat map computer program instruction.

Abstract: A unique implementation of a machine learning application for suggesting actions for a user to undertake is described herein. The application transforms a history of user behavior into a set of models that represent user actions given a set of parameters. These models are then used to suggest that users in a payments or banking environment take certain actions based on their history. The models are created using the DensiCube, random forest or k-means algorithms.

Abstract: Disclosed is a system for scoring customers of a financial institution based on financial data. The system includes a central database that stores a plurality of modules, a central server that processes the plurality of modules and a display unit that displays the processed plurality of modules. The plurality of modules includes a criteria configuration module, a data module, and a computation module. The criteria configuration module includes a metric module to receive the input parameters required to evaluate the score, and a measurement module for defining transformation criteria to be applied on the data corresponding to the input parameters. The computation module includes a metric evaluation module to compute and applies the transformation criteria to the values of the input parameters, and a scoring module coupled to the metric evaluation module to automatically compute and display the score of the customers based on the values retrieved from the metric evaluation module.

Abstract: A unique user interface for improving machine learning algorithms is described herein. The user interface comprises an icon with multiple visual indicators displaying the machine learning confidence score. When a mouse hovers over the icon, a set of icons are displayed to accept the teaching user's input. In addition, the words that drove the machine learning confidence score are highlighted with formatting so that the teaching user can understand what drove the machine learning confidence score.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.