Patent Application Titled “System For Fast Composing, Launch And Configuration Of Customizable Second-Tier Transfer Structures With Build-In Auditing And Monitoring Structures And Method Thereof” Published Online (USPTO 20220270179): Swiss Reinsurance Company Ltd.

2022 SEP 14 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventor MANGOLD, Chung-Shik (Wangen, CH), filed on March 10, 2022, was made available online on August 25, 2022.

The assignee for this patent application is Swiss Reinsurance Company Ltd. (Zurich, Switzerland).

Reporters obtained the following quote from the background information supplied by the inventors: “Automated or semi-automated risk-transfer systems, typically interacting with a user via graphical user interface (GUI), are known in the prior art. In particular, automated, cloud-based systems enabling an end-user, broker, MGA (Managing General Agent) etc. to compose and/or parametrize automatically a first-tier (insurance) and/or second-tier (reinsurance) risk-transfer structure/products, after conducting a dialogue with a knowledge-based system, are known. Such systems reduce the dependences of first-insurers or reinsurers on both their information technology (IT) and their human experts, as e.g. actuarial experts. Such systems are able to adjust the dialogue interactively according to the specific needs of the users and ask for the relevant data needed for the desired risk-transfer product.

“Typically, the structure of risk-transfers makes them for many types of risk-transfer suitable for automation with regard to the composition/configuration of the risk-transfer products. Most risk-transfers consist of a number of common basic parts and elements to configure. These parts and elements are herein referred as “structuring blocks” of the risk-transfer, i.e. the risk-transfer structure defining the characteristics of the risk-transfer. Different combinations of these structuring blocks lead to different risk-transfer products. For a human-machine interface (HMI) as e.g. Graphical User Interface (GUI), and for the corresponding necessary dialogue between the machine and the user, it should be possible to automatically compose risk-transfer products or structures out of a set of such structuring blocks. The “human” is the user of the automated system, i.e. an insured or an insurer depending if a first-tier (insurance product) or second-tier (reinsurance product) risk-transfer has to be configurated, while the “machine” refers to the automated system, as e.g. an automated web server or cloud-based system of a provider e.g. an insurer for first-tier risk-transfer products or a reinsurer for second-tier risk-transfer products. For example, using the parameterization of structuring blocks, typically a system comprising a limited amount of structuring blocks can be obtained for non-customized risk-transfer products. For example, applying domain knowledge of the actuary filed of life risk-transfer structures (life/non-life insurance structures/products), a life risk-transfer structure (defined by the policy) comprises the steps of after a monetary amount transfer (premium) either on basis of a regular money transfer or as a lump sum, the user (beneficiary) receives an endowment if the insured is alive, which means that the insurer has to pay the beneficiary a sum of money (i.e. the benefit) in the case of death in exchange for the premium transfer. Depending on the contract, other events such as terminal illness or critical illness can also trigger payment. Unseen the latter, the life risk-transfer can therefore be reduced to three basic events. These events can be assigned to a set of structuring blocks common to all life risk-transfer: premium endowment and alive. For automation, all such systems depend on triggers. Triggers detect events in its environment by observing, measuring and/or monitoring properties or characteristics of input stimuli, as measuring parameters, it receives or measures. Finally, based on the used structuring blocks, the dialogue input flow of the user interface (HMI) may follow pairs of current state and input to what the present output and the next state must be. Thereby, the input triggers the next state.

“Today, automation of the underwriting process is not enough to cope with the challenges. The increasingly dynamic and diversified reinsurance market requires shorter time-to-market of highly customized reinsurance products. Such process are technically difficult to automatize. Thus, though the prior art system are able to automate or semi-automate the underwriting process, there is still a need for a complete electronically automated solution covering the whole facultative risk-transfer (Note that that the present inventive solution covers, for risk-transfer, all line of business (natural catastrophes, casualty, etc.), all classes of businesses (proportional/non-proportional), and all risk types (life/non-life)). In particular, there is no system providing a fast, consistent and easy access to reinsurance risk-transfer, thereby allowing to reduce administration costs for managing mid-market risk portfolios, (ii) to access fast, automatic capacity approval for medium-sized single risks or facilities or treaties etc., and (iii) to relieve administration time, to focus on more complex parts of the risk-transfer. In summary, there is a need for an easy-to-use and efficient online risk placement, claims and accounting channel for clients covering the whole process of the risk-transfer, i.e. the entire value chain providing an end-to-end process, thereby providing fast composing, launch and configuration of highly customized reinsurance products.

“In summary, processor-driven systems with user interfaces for automated receiving data for binding contract conclusions between a user and a digital platform or channel are known in the prior art, in particular, via the Internet. In the field of risk-transfer technology, such systems or platforms are e.g. automated underwriting (UW) platforms. To increase the quality of the data acquisition, the known systems are typically equipped with validation means in order to check the input data values on the basis of data rules which are assigned to data input fields of the user interfaces and for requesting, if necessary, corrections via the user interface. In the case of products or services which are assigned to fixed purchase prices, sales contracts can be automatically concluded on-line by the known systems. If, however, the objects of contracts relate to service structures/products which cannot be simply assigned contract conditions and, in particular, prices on an individual one-to-one basis, the known systems are only suitable for data acquisition for ordering services or applying for services which must be dealt with manually by professional assistants of the service provider at a later time. This means that contracts for services which are dependent on many conditions and factors, for example risk-transfers which depend on numerous and different risk factors and risk-transfer conditions, cannot be concluded automatically and on-line by the known systems, nor can such risk-transfers or portfolios or baskets of risk-transfers be dynamically adapted form user side without human assistance form the provider side. In the known systems, it is possible to deal differently with users from different countries and/or language regions by selecting and activating different user interfaces in accordance with the specification of the relevant country or of relevant language region for the user. For example, the user is presented with a country- or language-specific graphical user interface. The existence of a number of different user interfaces for different user groups increases the complexity and maintenance costs of the system. For example, a general change of the user interface must be carried out in all country- and language-specific graphic user interfaces.

“US 2018/0114272 A1 shows a computer-based system from the prior art providing an automated, inter-arrival-time-based system for automated prediction and signaling of associated, risk-event driven risk-transfer systems, for automated low frequency catastrophic risk-transfer. The system measures risk-events and assigns them to a historic hazard set comprising event parameters for each assigned risk-event. The automated risk-transfer systems are provided with corresponding risk-transfer parameters for initiating automated risk cover. An event loss set is based on the measured frequencies with associated losses of said risk-events of the hazard set, each of said risk-events creating a set specific loss. Time-stamps, based on an automatically and/or dynamically estimated distribution of corresponding inter-arrival times parameters, capture a waiting time between consecutive events of the period loss set. The waiting times measure the time intervals between two successive risk-events and capture peril specific temporal clustering and/or seasonal occurrence patterns. US 2017/0161859 A1 shows another prior art system disclosing an automated system for disaster risk management, the system capturing country-specific parameters of a risk-exposed country relating to stored predefined criteria, assigning disaster event types to a disaster history table, capturing and storing mapping parameters for a geographic risk map, assigning each of a plurality of selectable disaster financing types to a definable cost factor capturing the capital cost of the disaster financing type in relation to its application for disaster mitigation, determining expected catastrophe losses by a loss frequency function and the geographic risk map for various scenarios of occurring natural disaster event types, and preparing a forecast of an effect of the disaster financing type to cover the catastrophe losses based on the coverage structure, the assigned cost factors, and the determined expected catastrophe losses. Finally, the prior art document US 2008/0065427 A1 discloses a system for analyzing sensor data collected from sensors monitoring property. The systems and methods analyze the data to make property insurance underwriting decisions based on the collected sensor data using a computerized process that varies the way in which it manipulates the collected sensor data based on a characteristic of the property being insured, a characteristic of the entity seeking the insurance, or on the values of the collected data parameters.”

In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventor’s summary information for this patent application: “It is an object of the invention to allow for systematic capturing, measuring, quantifying, and forward-looking generating of appropriate risk and risk accumulation measures of risk-transfers and risk-transfer portfolios associated with risk exposures of physical real-world assets and objects based on physical measuring parameter values and data, i.e. the impact of a possibly occurring physical event in a defined future time window. It is a further object of the present invention to propose a processor-driven system or platform providing an automated digital channel for automatically concluding and dynamically adapting risk-transfers between a risk-transfer service user and a risk-transfer service provider, which does not exhibit the disadvantages of the known systems. In particular, it is an object of the present invention to propose a processor-driven, metric system or digital platform which comprises a user interface, which can be operated by means of terminals via a data-transmission network for users, comprising data input fields for inputting data relating to the object of a risk-transfer, which is available and can be used as a one-stop, end-to-end process for conducting, monitoring and adapting risk-transfers or portfolios of risk-transfers by the user independently of the location or the desired object of a contract (service). In particular, it is a further object of the present invention to propose a processor-driven, computer-based system which comprises a universal user interface which can be adapted flexibly to variable risk-transfer conditions and risk-transfer types of an automated binding process without changes which are visible to the service user. The used inventive technical teaching should be easily integratable in other processes, productions chains or risk assessment and measuring systems. Finally, the invention should be enabled to use data and measuring parameter values from multiple heterogeneous data sources. The probability and risk forecast should allow to capture various device and environmental structures, providing a precise and reproducible measuring of risk factors, and allowing to optimize associated event occurrence impacts of the captured risk events.

“According to the present invention, these objects are achieved particularly through the features of the independent claims. In addition, further advantageous embodiments follow from the dependent claims and the description.

“According to the present invention, the above-mentioned objects are particularly achieved by the inventive, automated risk-transfer configurator and digital platform and system allowing fast composing, launching and configuration of highly customized secondary risk-transfer structures, inter alia by creating an end-to-end solution for second-tier transfer (reinsuring risk) portfolios. In particular, the digital platform provides an automated, multi-channel, end-to-end risk-transfer product configuration and management process for configuring, launching and processing of customized second-tier risk-transfer structures, wherein an automated risk-transfer product placement is provided by the system as a first online channel comprising a parameter-driven, rule-based underwriting process for creating a portfolio of customized second-tier structures, wherein an automated claim handling is provided by the system as a second online channel, and wherein an automated accounting is provided by the system as a third online channel, in that the system comprises a product configurator comprising at least four structuring blocks, a first structuring block for setting coverage area parameters of the risk-transfer product, a second structuring block for setting line of business parameters, a third structuring block for setting type of risk-transfer parameters, and a fourth structuring block for setting risk information parameters, in that for capturing the risk information parameters, the product configurator comprises a machine-based exposure data intelligence enabled to automatically identify unique risks of objects based on a precise location of the objects, in that the system comprises a metric simulation engine for automated prediction of forward- and backward-looking impact measures based on event parameter values of time-dependent series of occurrences of physical impacting risk-events, wherein the occurrences of the physical risk-events are measured based on predefined threshold-values of the event parameters and wherein the impacts of the physical risk-events to a specific asset or object are measured based on impact parameters associated with the asset or object, and in that the system comprises a graphical user interface of a portfolio analytics framework providing a dynamic representation of a portfolio structure, wherein the metric simulation engine forms an integrated part of the portfolio analytics framework, and wherein, by means of the metric simulation engine, the dynamic representation of the portfolio structure provides forward- and backward-looking insights to the user thereby enabling portfolio steering by identification of critical areas of the portfolio and impacts of possible changes to the underwriting before going to launch it in the market.

“As an embodiment variant, the product configurator comprises a client rate offering module, wherein by means of the client rate offering module, the user is enabled to input and offer a rate he is willing to pay, thereby allowing the system to capture insights into the gap between willingness to pay and the costing generated by the system.

“As another embodiment variant, the machine-based exposure data intelligence can e.g. comprise an exposure database comprising a plurality of data records holding attribute parameter of properties/objects with assigned geographic location parameters, wherein the machine-based exposure data intelligence comprises a clustering module for clustering stored properties/objects of the exposure database related to their assigned geographic location parameters, and wherein different data records of the exposure database having the same assigned geographic location parameters are matched and mutual aligned, in case of triggering inconsistencies for data records having the same assigned geographic location parameters. The machine-based exposure data intelligence can e.g. comprise a rate engine providing a lookup service access for users based on the exposure database and the clustering of the data records, wherein an automated identification of location-specific risks is assessible by a user based on the precise location of the properties and/or objects. The machine-based exposure data intelligence can e.g. further comprise a user data interface enabling access via mobile devices to input location data by a GPS-module or optical sensor and/or camera of the mobile devices. The mobile device can e.g. be realized as a smart phone. A user can e.g. be enabled to scan for insured properties by means of the mobile devices as e.g. his smart phone. The machine-based exposure data intelligence can e.g. further comprise an cross-level analysis module providing identification, analysis and visualization of large risk pools, wherein a risk pool comprises a plurality of objects of the exposure database, wherein the different levels and channels comprise at least facultative risk-transfer and/or treaty risk-transfer and/or customized corporate direct risk-transfer, and wherein risk of properties/objects are analyzed based on the attributes and location at different levels and for different channels allowing for automated tracking of risk accumulation and/or capacity thresholds. The clustering module of the machine-based exposure data intelligence can e.g. comprise an automated address matching based on the latitude and longitude coordinates of a location, wherein for the clustering a search is narrowed down to a grid cell around the property/object of interest to a scale where two locations are matchable based just on the house number or other location-dependent attributes. For the clustering, the clustering module can e.g. use an adaptive cell size and/or shape, depending on the local housing/construction density. Alternatively, for the clustering, the clustering module can also use accessible building footprints to check if latitudinal/longitudinal-tags are enclosed with the footprint of interest, for example, wherein any latitudinal/longitudinal-coordinate is mapped to a unique building and/or associated to sites.

“Finally, as an additional embodiment variant, the digital platform and system can be realized as an integrated part of a cloud-based application. The cloud-based application can be realized as Software as a Service (SaaS) over the cloud application by an appropriate provider.”

There is additional summary information. Please visit full patent to read further.”

The claims supplied by the inventors are:

“1. A digital platform and system that provides an automated, multi-channel, end-to-end risk-transfer configuration and/or parametrization process for configuring, launching, and processing of customized second-tier transfer structures, wherein an automated risk-transfer placement for objects or property assets each having a geographic location related to occurrence of physical impacting risk-events, the objects or property assets impacting events, is provided by the digital platform and system as a first online channel comprising an electronic, parameter-driven, rule-based underwriting process for automatically creating a portfolio or composition of customized second-tier structures, wherein automated claim handling is provided by the digital platform and system as a second online channel, and wherein automated accounting is provided by the digital platform and system as a third online channel, the digital platform and system comprising: a product configurator, implemented by circuitry, that uses at least four structuring blocks, a first structuring block for setting coverage area parameters of a risk-transfer product, a second structuring block for setting line of business parameters, a third structuring block for setting type of risk-transfer parameters, and a fourth structuring block for setting risk information parameters, wherein for capturing the risk information parameters, the product configurator comprises a machine-based exposure data intelligence configured to automatically identify unique risks of objects or property assets based on precise geographic locations of the objects or property assets, wherein the machine-based exposure data intelligence comprises an exposure database as a centralized geodatabase comprising a plurality of data records holding attribute parameter of objects or property assets with assigned geographic location parameters, the attribute parameters being grouped into at least geographical and/or physical and/or flood physical and/or storm physical and/or earthquake physical properties, and the location being measured by location data of a GPS-module or optical sensor and/or camera of mobile devices and inputted via a user data interface of the machine-based exposure data intelligence accessed via the mobile devices, and the machine-based exposure data intelligence is configured to perform clustering by clustering stored objects or property assets of the exposure database related to their assigned geographic location parameters, and to perform automated address matching based on latitude and longitude coordinates of a measured location, wherein for the clustering a matching is narrowed down to a grid cell around an object or property asset to a scale where two locations are matchable based location-dependent attributes using an adaptive cell size and/or shape, depending on a local housing/construction density, and wherein different data records of the exposure database having a same assigned geographic location parameters are matched and mutually aligned, in case of triggering inconsistencies for data records having the same assigned geographic location parameters; a metric simulation engine, implemented by the circuitry, configured to automatically predict forward- and backward-looking impact measures based on event parameter values of time-dependent series of occurrences of physical impacting risk-events, wherein the occurrences of the physical impacting risk-events are measured based on predefined threshold-values of the event parameters and wherein impacts of the physical impacting risk-events to a specific object or property asset are measured based on impact parameters associated with the object or property asset; and a graphical user interface of a portfolio analytics framework providing a dynamic representation of a portfolio structure, wherein the metric simulation engine forms an integrated part of the portfolio analytics framework, and wherein, by way of the metric simulation engine, the dynamic representation of the portfolio structure provides forward- and backward-looking insights to a user thereby enabling portfolio steering by identification of critical areas of the portfolio and impacts of possible changes to the underwriting process before launching it in a market.

“2. The digital platform and system according to claim 1, wherein the product configurator comprises a client rate offering module configured to enable the user to input and offer a rate the user is willing to pay, thereby allowing the digital platform and system to capture insights into a gap between willingness to pay and costing generated by the digital platform and system.

“3. The digital platform and system according to claim 1, wherein the machine-based exposure data intelligence comprises a rate engine providing a lookup service access for users based on the exposure database and the clustering of the data records, wherein an automated identification of location-specific risks is assessible by the user based on the precise geographic location of the objects or property assets.

“4. The digital platform and system according to claim 1, wherein the machine-based exposure data intelligence further comprises a user data interface configured to enable access via a mobile device, of the mobile devices, to input location data by a GPS-module or optical sensor and/or camera of the mobile device.

“5. The digital platform and system according to claim 4, wherein the mobile device is a smart phone.

“6. The digital platform and system according to claim 4, wherein a user is enabled to scan for insured properties using the mobile device.

“7. The digital platform and system according to claim 1, wherein the machine-based exposure data intelligence comprises an cross-level analysis module providing identification, analysis, and visualization of large risk pools, wherein a risk pool comprises a plurality of objects of the exposure database, wherein different levels and channels comprise at least facultative risk-transfer and/or treaty risk-transfer and/or customized corporate direct risk-transfer, and wherein risk of properties/objects are analyzed based on the attributes and location at different levels and for different channels allowing for automated tracking of risk accumulation and/or capacity thresholds.

“8. The digital platform and system according to claim 1, the clustering by the machine-based exposure data intelligence comprises an automated address matching based on the latitude and longitude coordinates of a location, wherein for the clustering a search is narrowed down to a grid cell around a property/object of interest to a scale where two locations are matchable based just on a house number or other location-dependent attributes.

“9. The digital platform and system according to claim 8, wherein the clustering uses an adaptive cell size and/or shape depending on the local housing/construction density.

“10. The digital platform and system according to claim 8, wherein, for the clustering, the machine-based exposure data intelligence uses accessible building footprints to check whether latitudinal/longitudinal-tags are enclosed with a footprint of interest, wherein any latitudinal/longitudinal-coordinate is mapped to a unique building and/or associated to sites.

“11. The digital platform and system according to claim 1, wherein structured asset/object characteristics parameters of the objects or property assets are captured at least partially by a parameter-driven, rule-based bifurcation process dynamically capturing characteristics parameter values and mapping the values to the structured characteristics parameters, wherein a plurality of risk-transfers associated with occurrence of one or more predefined risk-events impacting the objects or property assets are captured by metric risk-exposure units and transferred to a portfolio holding the risk-transfers by the captured risk-exposure units, and wherein the structural mix characteristic of the portfolio is given by the measured and captured types of risks and assigned number of risk-transfers with associated metric risk-exposure units, the metric simulation engine applies basic rate measures to the metric risk exposure units associated with a specific type of risk-transfer based on the event parameters of the risk-transfer and asset/object characteristics parameters of the objects or property assets determined by the metric simulation engine, wherein a basic rate measure provides for a cost measure of resources needed to cover the risk associated with a specific transfer, and wherein a premium for the risk-transfer is generated multiplying the basic rate measure by a number of risk-exposure units of the specific risk-transfer, and the metric simulation engine provides dynamically forward- and backward-looking impact measures based on a variation of the basic rate measure and/or the structural mix characteristic of the portfolio comprising the captured risk-exposure units, wherein the forward- and backward-looking impact measures at least comprise a measure for an total amount of premiums associated with the portfolio of risk-transfers and/or a net amount of premiums given by the total amount of premiums minus premiums associated with secondary risk-transfers assigned to transferred parts of the risk exposure units of the portfolio, and/or a total expected loss measure and/or a CM1 measure.

“12. The digital platform and system according to claim 11, wherein a basic rate measure and/or a structural mix characteristic of a basket comprising captured risk-exposure units is varied until a desired degree regarding the varied values of the basic rate measure and/or the structural mix characteristic is reached.”

There are additional claims. Please visit full patent to read further.

For more information, see this patent application: MANGOLD, Chung-Shik. System For Fast Composing, Launch And Configuration Of Customizable Second-Tier Transfer Structures With Build-In Auditing And Monitoring Structures And Method Thereof. Filed March 10, 2022 and posted August 25, 2022. Patent URL: https://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220220270179%22.PGNR.&OS=DN/20220270179&RS=DN/20220270179

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