Abstract: Methods and systems for developing profitable convertible term products are disclosed. The methods include the disaggregation of the pricing of existing term products and the use of big data analytics to identify opportunities to improve the acceptance of the product within a particular share of the market. Then, a pricing model and a selling model are built to test the product.

Abstract: The embodiments recite systems and methods that improve the traditional underwriting process within a financial institution. These embodiments produce an underwriting model that emulates the resolution patterns of top performing underwriters. The underwriting model once is built and tested is incorporated into decision tools that provide underwriters with insightful advices when underwriting a client. The embodiments use statistical learning techniques such as support vector machine and logistic regression. These techniques can assume a linear or nonlinear relationship between factors and risk classes. Furthermore, the underwriting model also uses artificial intelligence tools such as expert systems and fuzzy logic. A company's underwriting standards and best underwriting practices may be updated periodically so that underwriting model based on decision heuristic keep improving the quality of its output over time.

Abstract: A system and a method for identifying and ranking agents are disclosed herein. The system includes an analytics engine which retrieves information from external and internal databases. The analytics engine uses the information retrieved from these databases, in addition to one or more success factors or key attributes, to identify and rank prospective agents. The analytics engine can also match one or more prospective agents with a general agent and provide ranking and performance assessment reports for evaluating and following up on the agent’s career development.

Abstract: Systems and methods for validating outputs from a machine learning model is disclosed. The machine learning model and a statistical model are executed to generate electronic documents in response to customer requests. A random sample of electronic documents generated from the machine learning model and the statistical model are then selected. A comparison is performed between the random sample of electronic documents generated from the machine learning model and the statistical model. The performance of the machine learning model is validated based on results of the comparison.

Abstract: Systems and methods for validating outputs from a machine learning model is disclosed. The machine learning model and a statistical model are executed to generate electronic documents in response to customer requests. A random sample of electronic documents generated from the machine learning model and the statistical model are then selected. A comparison is performed between the random sample of electronic documents generated from the machine learning model and the statistical model. The performance of the machine learning model is validated based on results of the comparison.

Abstract: System and methods for an agent tool that identifies high value targets within a particular area, based on an individual's social media activity are disclosed. A computing device displays a user interface generated by an analysis module, and receives an agent's search criteria. Then, the analysis module scans a plurality of social media sites and selects the profile of individuals according to the search criteria. Next, the analysis module identifies the profile of members who are associated to the profile of each previously selected individual, and compares them with the profile of pleased customers. If both profiles match, then the analysis module has identified a high value target. The system also provides the full profile of each high value target found, when needed. The agent tool identifies high value targets in a simpler, less time-consuming and inexpensive way, while increasing the company's revenue.

Abstract: The embodiments recite systems and methods that improve the traditional underwriting process within a financial institution. These embodiments produce an underwriting model that emulates the resolution patterns of top performing underwriters. The underwriting model once is built and tested is incorporated into decision tools that provide underwriters with insightful advices when underwriting a client. The embodiments use statistical learning techniques such as support vector machine and logistic regression. These techniques can assume a linear or nonlinear relationship between factors and risk classes. Furthermore, the underwriting model also uses artificial intelligence tools such as expert systems and fuzzy logic. A company's underwriting standards and best underwriting practices may be updated periodically so that underwriting model based on decision heuristic keep improving the quality of its output over time.

Abstract: A system and a method for identifying, ranking, and matching agents are disclosed herein. The system may include an analytical engine which may collect information from external and internal databases. The analytical engine may use the information collected from these databases, in addition to a success criteria, for determining one or more success factors or key attributes of successful agents. An algorithm within the analytical engine may compute probabilities, trends and variability analysis for determining the impact of the defined key attributes in the successful career developments for prospective or active agents. The analytical engine may identify prospective agents and match them to suitable general agents. A list of agents' leads, ranking reports, and ongoing assessments may be communicated or supplied to general agents through the use of agent computing devices operatively coupled with the analytical engine.

Abstract: Methods and systems determine the protection needs and cross-selling capability to RS clients. A retirement protection system includes one or more software modules that interact with each other and are used to determine and identify the protection needs of high propensity clients, and develop strategies to cross-sell annuity/life products to those clients. The retirement protection system includes different components which may be implemented through one or more software modules running on a computing device. The retirement protection system involves the analysis of a sample of RS clients to determine cross selling capability of life, disability income, and annuity products. Additionally, the retirement protection system implements an experimental approach to pilot and refine the direct marketing model in order to create campaigns for high propensity target clients or groups.

Abstract: Systems and methods for ranking and appraising leads according to their quality are disclosed. The disclosed method operates within a systems' architecture configured to rank and auction leads. One or more client computing devices allow an agent to request for the ranking and appraisal of a set of leads. Following the request, a ranking module implements one or more software modules for assessing the quality of each lead and ranks the set of leads according to a quality criterion. Next, a price modeling module defines a floor price for the set of leads. The solutions derived from the software modules are stored in an internal database where they are available to other software modules operating within the system architecture for ranking and auction leads. In some embodiments, the ranking results are used for tracking results and developing insight about the value of leads and the effectiveness of the ranking method.

Abstract: A method of identifying potential clients from aggregate sources for an insurance company is disclosed. The disclosed method includes an external database, a profile analyzer, and a profile database. A Profile Analyzer is configured to retrieve a set of search results from an external database and may use predictive analytics to extract information from the data retrieved. Further analysis of this data is filtered and may be used to predict trends and consumer behavior patterns. Profile analyzer generates potential client profiles. The client profiles are stored in a profile database operatively coupled with the profile analyzer. Clients profile includes metadata associated with weighted coefficient used for estimating a suitable list of potential clients.

Abstract: A method of identifying potential clients from aggregate sources for an insurance company is disclosed. The disclosed method includes an external database, a profile analyzer, and a profile database. A Profile Analyzer is configured to retrieve a set of search results from an external database and may use predictive analytics to extract information from the data retrieved. Further analysis of this data is filtered and may be used to predict trends and consumer behavior patterns. Profile analyzer generates potential client profiles. The client profiles are stored in a profile database operatively coupled with the profile analyzer. Clients profile includes metadata associated with weighted coefficient used for estimating a suitable list of potential clients.

Abstract: A method for matching insurance products to orphan policyholders may enable an insurance company to automatically identify sales value and propensity to sales of a list of orphan policyholders, among other characteristics, by using collaborative filtering techniques and learning algorithms. The method may further enable for automated marketing and sales and may reduce internal costs which may be further transferred to customers as a discount and provide a competitive edge within the insurance industry.

Abstract: Systems and methods can present a financial plan that is based upon a customized selection of goals on a user interface, whereby a set of shapes representing goals can be configured along a timeline and data representing those goals can be edited, which dynamically adjusts a financial plan algorithm to provide a solution in a more dynamic and on demand approach than conventional solutions.

Abstract: A method and system for obtaining leads based on data derived from a variety of sources is disclosed. The method is executed by a system that includes a data processing module within a leads management system, among others system components. The data processing module scans one or more external data sources; collects lead data from those sources; analyzes the data collected; identifies attributes of interest about one or more potential quality leads; identifies one or more high quality leads; creates a profile for those high quality leads; stores those profiles in an internal database; and generates a list of one or more high quality leads.

Abstract: Methods and systems for developing profitable convertible term products are disclosed. The methods include the disaggregation of the pricing of existing term products and the use of big data analytics to identify opportunities to improve the acceptance of the product within a particular share of the market. Then, a pricing model and a selling model are built to test the product.

Abstract: The embodiments recite systems and methods that improve the traditional underwriting process within a financial institution. These embodiments produce an underwriting model that emulates the resolution patterns of top performing underwriters. The underwriting model once is built and tested is incorporated into decision tools that provide underwriters with insightful advices when underwriting a client. The embodiments use statistical learning techniques such as support vector machine and logistic regression. These techniques can assume a linear or nonlinear relationship between factors and risk classes. Furthermore, the underwriting model also uses artificial intelligence tools such as expert systems and fuzzy logic. A company's underwriting standards and best underwriting practices may be updated periodically so that underwriting model based on decision heuristic keep improving the quality of its output over time.

Abstract: System and methods for an agent tool that identifies high value targets within a particular area, based on an individual's social media activity are disclosed. A computing device displays a user interface generated by an analysis module, and receives an agent's search criteria. Then, the analysis module scans a plurality of social media sites and selects the profile of individuals according to the search criteria. Next, the analysis module identifies the profile of members who are associated to the profile of each previously selected individual, and compares them with the profile of pleased customers. If both profiles match, then the analysis module has identified a high value target. The system also provides the full profile of each high value target found, when needed. The agent tool identifies high value targets in a simpler, less time-consuming and inexpensive way, while increasing the company's revenue.

Abstract: Systems and methods for ranking and appraising leads according to their quality are disclosed. The disclosed method operates within a systems' architecture configured to rank and auction leads. One or more client computing devices allow an agent to request for the ranking and appraisal of a set of leads. Following the request, a ranking module implements one or more software modules for assessing the quality of each lead and ranks the set of leads according to a quality criterion. Next, a price modeling module defines a floor price for the set of leads. The solutions derived from the software modules are stored in an internal database where they are available to other software modules operating within the system architecture for ranking and auction leads. In some embodiments, the ranking results are used for tracking results and developing insight about the value of leads and the effectiveness of the ranking method.

Abstract: Methods and systems determine the protection needs and cross-selling capability to RS clients. A retirement protection system includes one or more software modules that interact with each other and are used to determine and identify the protection needs of high propensity clients, and develop strategies to cross-sell annuity/life products to those clients. The retirement protection system includes different components which may be implemented through one or more software modules running on a computing device. The retirement protection system involves the analysis of a sample of RS clients to determine cross selling capability of life, disability income, and annuity products. Additionally, the retirement protection system implements an experimental approach to pilot and refine the direct marketing model in order to create campaigns for high propensity target clients or groups.