# US 10,769,569 B2 · System for automated resource set multi-factor risk analysis

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- Number: US 10,769,569 B2
- Document ID: US10769569B2
- Status: Granted
- Kind: B2
- Application number: 15/651,208
- Filed: 2017-07-17
- Published: 2019-01-17
- Granted: 2020-09-08
- Earliest claimed: 2017-07-17
- Assignees: Hartford Fire Insurance Company
- Applicants: Hartford Fire Insurance Company
- Inventors: Theodore J Lucas; Dariusz Wojnar; Mark D Thomas; Scott M Fitzpatrick; Kylie J Baker
- Web page: https://patentgrep.com/patent/US10769569B2

## CPC

- G06Q 10/0635: Risk analysis of enterprise or organisation activities
- G06Q 40/04: Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
- G06Q 40/06: Asset management; Financial planning or analysis
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

A multi-factor risk analysis system may include a resource data store defining, for each of a plurality of resources: a resource identifier, a current resource value, and a resource type. A back-end application computer server may establish a set of risk parameter diversification objectives and determine a set of eligible resources by accessing the resource data store. The server may then calculate a value factor characteristic and a momentum factor characteristic for each of the eligible resources. A set of index resources may be constructed from the set of eligible resources based on the risk parameter diversification objective and a risk optimization process utilizing a weighted value factor characteristic and momentum factor characteristic of each resource. An interactive user interface may then be rendered including indications associated with the constructed set of index resources, the value factor characteristics, and the momentum factor characteristics.

## Claims

### Claim 1

A multi-factor risk analysis system, comprising:
a user device;
a resource data store containing electronic records defining, for each of a plurality of resources: a resource identifier associated with an entity, a current resource value, a resource type, and a resource location;
and
an automated back-end application computer server remote from the user device, coupled to the resource data store and the user device, including:
a communication port adapted to exchange information via a distributed communication network,
a computer processor, and
a computer memory storing instructions that, when executed by the computer processor cause the automated back-end computer server to perform a method, comprising;
receiving, from the user device via the communication port, a transmitted request for a set of index resources,
responsive to said request, establishing a set of risk parameter diversification objectives,
determining a set of eligible resources by accessing the resource data store,
calculating a value factor characteristic for each of the eligible resources,
calculating a momentum factor characteristic for each of the eligible resources,
automatically constructing the requested set of index resources from the set of eligible resources based on the risk parameter diversification objective and a risk optimization process utilizing a weighted value factor characteristic and momentum factor characteristic of each resource,
exchanging information with the remote user device via the communication port to render an interactive user interface including indications associated with the requested set of index resources, the value factor characteristics, and the momentum factor characteristics, and
automatically generating a plurality of reports including indications associated with the constructed set of index resources, the value factor characteristics, and the momentum factor characteristics,
wherein the interactive user interface further includes a circular visualization associated with risk distortions such that:
a graphical area within the circle is associated with an expected tail loss risk contribution based on resource location,
a graphical length along the circumference of the circle is associated with at least one of an overall country capital allocation and an overall currency capital allocation,
a length of a line extending outside and away from the circle is associated with an allocation to a particular equity or security, and
graphical elements of the circular visualization may be interactively adjusted by a user to automatically change resource allocations.

### Claim 2 (depends on 1)

The system of claim 1, wherein the risk parameter diversification objectives are associated with at least one of: (i) geographic locations, and (ii) resource types.

### Claim 3 (depends on 1)

The system of claim 1, wherein the risk optimization process is further associated with at least one of: (i) factor expression, and (ii) volatility targets.

### Claim 4 (depends on 1)

The system of claim 1, wherein the risk optimization process is further adapted to minimize resource turnover.

### Claim 5 (depends on 1)

The system of claim 1, wherein said constructing is performed on a periodic basis.

### Claim 6 (depends on 1)

The system of claim 1, wherein the resources are associated with at least one of equities and assets, and further wherein the set of index resources comprises a portfolio.

### Claim 7 (depends on 6)

The system of claim 6, wherein the value factor characteristic is calculated based at least in part on: (i) an earnings yield, (ii) an Earnings Before Interest, Tax, Depreciation and Amortization (“EBITDA”) divided by enterprise value, (iii) an enterprise value, (iv) an operating cash flow divided by enterprise value, (v) a revenue divided by enterprise value, (vi) a dividend yield, and (vii) a book value.

### Claim 8 (depends on 6)

The system of claim 6, wherein the momentum factor characteristic is calculated based at least in part on: (i) a last 10 monthly returns, and (ii) a last 5 monthly returns.

### Claim 9 (depends on 6)

The system of claim 6, wherein the method performed by the automated back-end application computer server further includes:
calculating a quality metric factor characteristic for each of the eligible resources,
wherein the optimization process further utilizes the quality metric factor characteristic for each of the eligible resources.

### Claim 10 (depends on 9)

The system of claim 9, wherein the quality metric factor characteristic is calculated based at least in part on a gross profitability divided by a total value of assets.

### Claim 11 (depends on 6)

The system of claim 6, wherein the set of eligible resources are determined based on at least one of: (i) developed markets, (ii) United States equities, (iii) emerging markets, (iv) global small capitalization equities, and (v) Real Estate Investment Trusts (“REITs”).

### Claim 12 (depends on 6)

The system of claim 6, wherein the risk parameter diversification objectives are associated with at least one of: (i) countries, (ii) industry sectors, and (iii) property type.

### Claim 13 (depends on 12)

The system of claim 12, wherein the risk optimization process is further associated with groups of equities weighted in inverse proportion to risk as indicated by a standard deviation value, variance, estimated tail loss, or other risk measure.

### Claim 14 (depends on 13)

The system of claim 13, wherein the method performed by the automated back-end application computer server further includes:
selecting a historical time window,
sorting, for each equity, periodic returns during the selected historical time window,
averaging the worst returns below a pre-determined threshold for each equity, and
determining an estimated tail loss by calculating an absolute value of a reciprocal of the average for each equity.

### Claim 15 (depends on 6)

The system of claim 6, wherein the risk optimization process is associated with a linear optimization process with an added constraint requiring a minimum number of effective equity holdings, wherein the effective equity holdings are calculated as a Herfindahl index based on an inverse of a sum of squared weights.

### Claim 16 (depends on 6)

The system of claim 6, wherein the risk optimization process is associated with a linear optimization process with an added constraint associated with a targeted maximum estimated portfolio volatility relative to at least one of: (i) a reference benchmark index, and (ii) a market segment performance.

### Claim 17 (depends on 16)

The system of claim 16, wherein the estimated portfolio volatility is calculated via a covariance matrix based on returns of portfolio holdings and a relationship of those returns to each other, wherein the covariance matrix is reduced from a size equal to the square of assets in the portfolio to a smaller size.

### Claim 18 (depends on 6)

The system of claim 6, wherein the set of risk parameter diversification objectives are associated with at least two of: (i) portfolio risk, (ii) cost risk, (iii) structural risk, (iv) market risk, (v) liquidity risk, and (vi) tax risk.

### Claim 19 (depends on 6)

The system of claim 6, wherein calculation of a target risk for a portfolio comprises an average of: (i) value at risk, (ii) volatility, (iii) estimated tail loss, and (iv) stress testing.

### Claim 20 (depends on 6)

The system of claim 6, wherein an estimated tail loss calculation uses a bootstrap Monte Carlo estimation to draw historical samples to achieve a distribution of worst case scenarios.

### Claim 21 (depends on 6)

The system of claim 6, wherein the automated back-end application computer server is further to execute a portfolio management and tax loss harvesting process.

### Claim 22 (depends on 6)

The system of claim 6, wherein the interactive user interface includes information about at least one of: (i) portfolio offensive characteristic, (ii) portfolio defensive characteristics, (iii) risk and return characteristics, and (iv) hypothetical risk and return characteristics.

### Claim 23 (depends on 22)

The system of claim 22, wherein the interactive user interface includes, for each of a benchmark set of resources, a first portfolio set of resources, and a second portfolio set of resources, a tabular presentation of at least one of: (i) weighted average portfolio characteristics, (ii) country and sector diversification, and (iii) a full period summary.

### Claim 24 (depends on 23)

The system of claim 23, wherein the interactive user interface further includes a graphical presentation of at least one of: (i) combined factor score of holdings, (ii) a factor strength and balance, (iii) company diversification, (iv) portfolio risk metrics, (v) periodic portfolio return relative to benchmark, (vi) upside/downside capture, (vii) periodic portfolio hypothetical return relative to benchmark, and (viii) hypothetical upside/downside capture.