Lapse predicting tool and scoring mechanism to triage customer retention approaches

Disclosed here is a triaging system, including a value engine, an analytical engine, a scoring engine, and databases storing internal, external, and retention value data. A value engine may be configured to receive information and determine a value associated with a policy; an analytical engine may be configured to receive information related to one or more factors associated with a policyholder, as well as actuarial relationships between the one or more factors; and a scoring engine may be configured to receive information associated with a policyholder from one or more value engines and analytical engines, and may output a scalar score associated with the retention value of the policyholder. The system may determine the value of retention associated with the policyholder and use this value to build and store a client score, where the client score may be a scalar representation of the value of retaining business with the policyholder.

FIELD OF THE INVENTION

The present disclosure relates in general to policy management systems, and more specifically to systems for customer triaging.

BACKGROUND

Individuals purchase insurance products for a variety of reasons. Examples include ensuring payment of funeral services, providing additional income to the individual's family in case of an accident, or providing financial security to a loved one. These individuals typically pay for the purchased insurance via periodic payments, often through monthly or annual premiums. As individuals face economic hardship, they may not pay one or more of said premiums and the policy may lapse. Generally, lapses in payments result in negotiations with the individuals for continuing with an insurance service, or otherwise terminating the contract. Because of this, these individuals may vary in their value as perceived by the insuring company. The perceived value may play an important role during future transactions, including the discussion of future lapses or the re-underwriting of products. However, determining the value of a policyholder remains a challenge. Often, the determination of the individual's value to the company is a labor intensive, time-consuming endeavor. Thus, there exists a need for methods of computationally predicting the retention value of a policyholder.

SUMMARY

The present disclosure describes a triaging system including one or more modules running on one or more suitable computing devices. In one or more embodiments, a triaging system may include a Value Engine, an Analytical Engine, a Scoring Engine, and one or more suitable databases storing one or more of a set of internal data, a set of external data, and/or a set of retention value data.

In one or more embodiments, a value engine may be configured to receive information and determine a value associated with one or more policies; an analytical engine may be configured to receive information related to one or more factors associated with one or more policyholders, as well as actuarial relationships between the one or more factors; and a scoring engine may be configured to receive information associated with one or more policyholders from one or more value engines and analytical engines, and configured to output one or more scalar scores associated with the retention value of one or more policyholders.

In one or more embodiments, a triaging system may determine cash flows for a policy held by one or more policyholders using any suitable actuarial analyses and may take into account the residual value of new business with the policyholder.

In one or more embodiments, a triaging system may build one or more underwriting models for one or more policyholders using a suitable analytical engine. The system may then proceed to re-underwrite policies associated with the one or more policyholders using the one or more models.

The system may then determine the value of retention by comparing the value of the cash flow associated with the policyholder and the value ascribed to the policyholder after re-underwriting. The system may then use this value to build and store a client score, where the client score may be a scalar representation of the value of retaining business with the policyholder.

Systems and methods described here may provide information beneficial during lapse discussions with policyholders.

In one embodiment, a computer-implemented method comprises determining, by a value engine of a server, a cash flow value for a policy held by a policyholder based upon a residual value of new business; generating, by an analytical engine of the server, an underwriting model for the policyholder; re-underwriting, by a triaging engine of the server, the policy based on the underwriting model; determining, by the triaging engine of the server, a value of retention by comparing the determined cash flow value associated with the policyholder and a value ascribed to the policyholder after re-underwriting the policy; generating, by the triaging engine of the server, a client score for the policyholder based upon the value of retention; and calculating, by the triaging engine of the server, a probability of lapsing by the policyholder.

In another embodiment, a computer executed method comprises determining, by a value engine of a triaging server, a financial value associated with an insurance policy based on a first cash flow for the policy, the insurance policy being issued to the customer based on a first underwriting; performing, by an analytical engine of the triaging server, a second underwriting of the customer for the policy based on an underwriting model associated with the customer and determining a second cash flow for the second underwriting; comparing, by a value engine of the triaging server, the first and second cash flows; and assigning, by the value engine of the triaging server, the retention value to the customer based on the comparison.

In yet another embodiment, a system comprises a server comprising: a value engine of the server configured to determine a cash flow value for a policy held by a policyholder based upon a residual value of new business; an analytical engine of the server configured to generate an underwriting model for the policyholder; a risk analysis module of the server configured to generate a resolution based on the underwriting model; and a triaging engine of the server configured to re-underwrite a product based on the underwriting model, determine a value of retention by comparing the determined cash flow value associated with the policyholder and a value ascribed to the policyholder after re-underwriting, and generate a client score for the policyholder based upon the value of retention.

Numerous other aspects, features and benefits of the present disclosure may be made apparent from the following detailed description taken together with the drawing figures.

DETAILED DESCRIPTION

The present disclosure is here described in detail with reference to embodiments illustrated in the drawings, which form a part here. Other embodiments may be used and/or other changes may be made without departing from the spirit or scope of the present disclosure. The illustrative embodiments described in the detailed description are not meant to be limiting of the subject matter presented here.

As used here, the following terms may have the following definitions:

“Policy” refers to any contract insuring a person or goods.

“Policyholder” refers to any entity who holds one or more policies.

“Value” refers to the monetary worth of a person or object.

“Lapse” refers to the inability of a policyholder to pay, at a moment previously agreed with a policy issuer, a cost associated with a policy held.

“Actuarial” refers to relating to a statistical assessment of risk.

“Value of new business” or “VNB”, refers to a potential value of new business associated with a policyholder.

“Value of retention” refers to a potential value of maintaining business associated with a policyholder.

“Re-underwriting” refers to the reevaluating of a policyholder for purposes of adjusting benefits or contractual terms.

“Analytical engine” refers to a software module that handles data integration, breaks data streams into atomic parts, executes rules, and performs data matching by using fuzzy logic, among others.

“Underwriting model” refers to an algorithm which measures the risk of a potential customer.

“Factor” refers to information which can be used as a reference for measuring the risk associated with a potential customer. A factor may be information such as age, current health, occupation, among others.

“Financial distress” refers to the condition of being unable to meet, or experiencing difficulty in meeting, financial obligations.

The present disclosure describes a triaging system including one or more modules running on one or more suitable computing devices, where the modules may ascribe a retention value to policyholders.

FIG. 1is a functional block diagram illustrating a triaging system architecture, according to an embodiment. InFIG. 1, triaging system architecture100includes internal database102, external database104, triaging engine106, and retention value database108. it should be understood that system architecture100can include fewer components, additional components, different components, or differently arranged components depending on the desired goals.

InFIG. 1, internal database102, external database104, and retention value database108are each coupled to and in bi-directional communication with triaging engine106via a network connection. Examples of such network connections include intranets, local area networks (LAN), virtual private networks (VPN), wireless area networks (WAN), Bluetooth, Bluetooth Low Energy, Wi-Fi, ZigBee, and the like, including other technologies suitable for establishing a connection between any number of computing devices. In other embodiments, retention value database108is coupled to and in communication to other components of a system architecture (not shown) where a triaging system architecture is implemented.

In some embodiments, internal database102is implemented as a relational database that receives information internal to a system, stores said information, and retrieves and provides said information to authenticated users. In these embodiments, internal database102provides internal data to modules within triaging engine106for use in one or more analyses relating to policyholder triaging. Examples of information that is internal to the system include actuarial information previously associated with the one or more policyholders, previous health evaluations of the one or more policyholders, previous object valuations of one or more objects associated with the one or more policyholders, and the like.

In other embodiments, external database104is implemented as a relational database that receives information external to a system, stores said information, and retrieves and provides said information to authenticated users. in these embodiments, external database104provides external data to modules within triaging engine106for use in one or more analyses relating to policyholder triaging. Examples of information that is external to the system include data related to one or more factors associated with one or more policyholders, including age, health history, family history, and occupation, amongst others, as well as actuarial relationships between the one or more factors. In other embodiments, external database104is implemented as a data store for unstructured data, and the information stored in external database104is processed prior to use in triaging system architecture100.

In some embodiments, triaging engine106is implemented as one or more software modules configured to ascribe a retention value to policyholders. In some embodiments, modules associated with triaging engine106are loaded on one or more computing devices, such as for example personal computers, data servers, mobile phones, and tablets, amongst others. Examples of such modules include a value engine, analytical engine, scoring engine, and the like.

In other embodiments, retention value database112is implemented as a relational database that receives information relating to the retention value of one or more clients, stores said information, and retrieves and provides said information to authenticated users. In these embodiments, retention value database112communicates scores associated with one or more policyholders to components coupled to and in communication with triaging system architecture100. Examples of information relating to the retention value of one or more clients include scores associated with a client and the like.

In operation, triaging engine106receives data relating to one or more policyholders from internal database102and external database104. Triaging engine106uses the data to develop a score associated with each of the one or more policyholders, and communicates the scores to retention value database108. In some embodiments, retention value database108stores the scores generated by triaging engine106for use by components coupled to and in communication with triaging system architecture100.

FIG. 2is an exemplary computing device200in which one or more embodiments of the present disclosure may operate, according to an embodiment. In one embodiment, computing device200includes bus202, input/output (I/O) device204, communication interface206, memory208, storage device210and central processing unit212. In another embodiment, computing device200includes additional, fewer, different, or differently arranged components than those illustrated inFIG. 2.

InFIG. 2, bus202is in physical communication with I/O device204, communication interface206, memory208, storage device210, and central processing unit212. Bus202includes a path that permits components within computing device200to communicate with each other. Examples of I/O device204include peripherals and/or other mechanism that may enable a user to input information to computing device200, including a keyboard, computer mice, buttons, touch screens, voice recognition, and biometric mechanisms, and the like. I/O device204also includes a mechanism that outputs information to the user of computing device200, such as, for example a display, a light emitting diode (LED), a printer, a speaker, and the like.

Examples of communication interface206include mechanisms that enable computing device200to communicate with other computing devices and/or systems through network connections. Examples of network connections include any suitable connections between computers, such as, for example intranets, local area networks (LANs), virtual private networks (VPNs), wide area networks (WANs), the Internet, and the like. Examples of memory208include random access memory208(RAM), read-only memory (ROM), flash memory, and the like. Examples of storage device210include magnetic and/or optical recording medium, ferro-electric RAM (F-RAM) hard disks, solid-state drives, floppy disks, optical discs, and the like. In one embodiment, memory208and storage device210store information and instructions for execution by central processing unit212. In another embodiment, central processing unit212includes a microprocessor, an application specific integrated circuit (ASIC), or a field programmable object array (FPOA), and the like. In this embodiment, central processing unit212interprets and executes instructions retrieved from memory208and storage device210.

According to some aspects of this embodiment, computing device200is implemented as part of a server, Triaging Engine106, and the like. Examples of these implementations include servers, authorized computing devices, smartphones, desktop computers, laptop computers, tablet computers, a PDAs, another type of processor-controlled device that may receive, process, transmit digital data, and the like. Additionally, computing device200may perform certain operations that are required for the proper operation of system architecture100. Suitable computing devices200may perform these operations in response to central processing unit212executing software instructions contained in a computer-readable medium, such as memory208.

In one embodiment, the software instructions of system are read into memory208from another memory location, such as storage device210, or from another computing device200(e.g., Triaging Engine106, and the like) via communication interface206. In this embodiment, the software instructions contained within memory208instructs central processing unit212to perform processes that will be described inFIGS. 3-4, below. Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to implement processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

FIG. 3is a functional block diagram illustrating a triaging engine, according to an embodiment. InFIG. 3, triaging engine300includes value engine302, internal data source304, analytical engine306, external data source308, scoring engine310, and retention value data312. It should be understood that triaging engine300can include fewer components, additional components, different components, or differently arranged components depending on the desired goals. In some embodiments, triaging engine300is implemented as triaging engine106ofFIG. 1, above.

InFIG. 3, internal database302is coupled to and in communication with value engine302and analytical engine306via a network connection. External database308is coupled to and in communication with analytical engine306. Value engine302, analytical engine306, and retention value database312are coupled to and in communication with scoring engine310.

In some embodiments and referring toFIG. 1, internal database302is implemented as a relational database functioning in a manner substantially similar to internal database102. In other embodiments, external database308is implemented as a relational database functioning in a manner substantially similar to external database104. In yet other embodiments, retention value database312is implemented as a relational database functioning in a manner substantially similar to retention value database108.

In some embodiments, value engine302is implemented as one or more portions of software modules running as part of triaging engine300. In other embodiments, value engine302is configured to receive information from internal database304, where internal database304includes any data storage device loaded with information internal to a system. In yet other embodiments, value engine302is configured to determine a value associated with one or more policies held by one or more policyholders using information received from internal database304.

In other embodiments, analytical engine306is implemented as one or more portions of software modules running as part of triaging engine300. In some embodiments, analytical engine306is configured to receive information from internal data source304and external data source308, prepare the information for use in one or more analyses performed by analytical engine306and/or scoring engine310, and perform one or more analyses associated with triaging engine300. Examples of the analyses associated with triaging engine300include actuarial analysis, financial distress analysis, and the like. In these embodiments, external data source308includes information derived from components external to a system including triaging engine300.

In some embodiments, scoring engine310is implemented as one or more portions of software modules running as part of triaging engine300. In other embodiments, scoring engine110is configured to receive information from one or more of value engine302and analytical engine306, and uses said information to score one or more policyholders. triaging engine300then stores the score determined by scoring engine310within retention value database312, where information in retention value database312is made accessible to other components of a system including triaging engine300.

FIG. 4is a flowchart illustrating a method of policyholder triaging, according to an embodiment. In some embodiments, policyholder triaging400begins by performing actions to determine cash flows402for a policy held by one or more policyholders. In an example, a value engine, such as for example value engine302, carries out instructions to determine cash flows402for a policy held by one or more policyholders. In some embodiments, value engines include actuarial analyses when determining a policy's value. In other embodiments, value engines take into account the residual value of new business (RVNB) with the policyholder to determine the cash flows.

Policyholder triaging400then continues to build client model404. In an example, an analytical engine, such as for example analytical engine306, carries out instructions to build client model404. In some embodiments, the analytical engine uses a set of internal and external data to develop an underwriting model for the one or more policyholders. In this step, an analytical engine may emulate the resolution patterns of top performing underwriters by using statistical learning techniques, such as support vector machine, logistic regression, and the like. In some embodiments, the aforementioned techniques assume a linear or nonlinear relationship between factors and risk classes. In other embodiments, a nonlinear relationship between factors and risk classes is preferred. In yet other embodiments, other techniques within the space of artificial intelligence are employed, such as for example expert systems, fuzzy logic, and the like. In these embodiments, the aforementioned techniques operate based on a defined set of underwriting standards set by the company, including possible enhancements using third party data, as well as best practices derived from the top performing underwriters within the company. In some embodiments, the risk analysis module provides a resolution. Examples of such a resolution include a risk classification or a risk of loss assessment. In some embodiments, the company periodically updates its underwriting standards and best underwriting practices so that an underwriting heuristic module (not shown) keeps improving the quality of its output over time.

Policyholder triaging400continues to re-underwrite products406. In an example, a triaging engine, such as for example triaging engine300, carries out instructions to re-underwrite products406using the model developed. In some embodiments, an analytical engine module with the triaging engine re-underwrites policyholders by performing an actuarial analysis, determining a coverage value associated with the policy, and determining the costs associated with the policy, and the like.

Subsequently, policyholder triaging400continues to determine the value of retention408. In an example, a triaging engine, such as for example triaging engine300, carries out instructions to determine the value of retention408by comparing the value of the cash flow associated with the policyholder and the value ascribed to the policyholder after re-underwriting. In some embodiments, the value of retention may be proportional to the difference of the re-underwritten value and the RVNB.

Subsequently, policyholder triaging400continues to build and store a client score410. In an example, a triaging engine, such as for example triaging engine300, carries out instructions use the value of retention to build and store a client score410. In some embodiments, the client score may be a scalar representation of the value of retaining business with the policyholder. In other embodiments, the client score may be a scalar representation of probability of a client lapsing by quantifying the client's financial distress. In these embodiments, a client's degree of financial distress can be derived from external or internal data, including the client's credit score, historical lapse data, census data, customer support logs, and the like. In some embodiments, a client's degree of financial distress is derived from information regarding the client's source of income and the state of the market from which clients obtain their income.

Next, policyholder triaging400continues to policyholder categorization412. In an example, a triaging engine, such as triaging engine300, performs policyholder categorization412by assigning a category, from a set of two or more categories, to one or more policyholders represented by data within a retention value database. In an example, a category set includes a category associated with policyholders with which the company wishes to continue to pursue business, a category associated with policyholders with which the company no longer wishes to pursue business, and a category associated with policyholders with which the company wishes to reduce business. In this example, the category the policy is associated with is determined by comparing the score associated with the policyholder within a retention value database to a predetermined threshold (e.g., RVNB).

Subsequently, Policyholder Triaging400continues to Triaging414. In an example, a system displays a score, category, or other representation associated with a policyholder's value and financial stress to a user. In some embodiments, the system allows a user to triage customer retention approaches according to the value associated with the policyholder.

Example #1 is a system including a triaging system employed in an insurance firm using a call center to follow up lapses. In this example, policyholders are individually scored from 1 to 5 (from least valuable to most valuable) by a triaging system. The scores are associated with a unique identifier which is presented to the call center representatives when interacting with the policyholders. In this example, the triaging system additionally associates the unique identifier with a score ranging from 1 to 5 indicative of the perceived financial distress of the policyholders, and may be used to evaluate the probability of a policyholder lapsing. The call center representative may then have additional insight during the call, and may use the score to provide differentiated responses depending on the policyholder's scores.

In this example, a policyholder with a value score of 5 and a financial stress score of 3 lapses in a payment associated with a high value policy. The customer representative proceeds to call the user and negotiate with the user in order to convince the user to continue using the company's services. In this example, the user changes to a policy with a diminished value that is more closely aligned with their current financial situation.