IP Library Granted Patent US 11,216,762
Granted Patent B1
US 11,216,762 · App. 15/684,507 · Granted Jan 4, 2022

Automated risk visualization using customer-centric data analysis

Inventors: Alexander Maass (New York, NY); Ben Regev (Holon, IL); Duncan Hoffman (Paris, FR); Eugene Mak (Hurlstone Park, AU); Elise Norman (London, GB); Elizabeth Patitucci (London, GB); Yevhen Shevchuk (Kiev, UA); Harkirat Singh (London, GB); Joshua Aschheim (New York, NY); Juan Jimenez Puig (Amsterdam, NL); Jorien Van Den Bergh (London, GB); Kai Kamberger (London, GB); Maciej Biskupiak (New York, NY); Marissa Miracolo (Lancashire, GB); Matthew Julius Wilson (London, GB); Nicolas Prettejohn (Bath, GB); Patrick Walter (Berlin, DE); Rootul Patel (Oyster Bay, NY); Stephen Heitkamp (London, GB); Richard Deitch (Dallas, TX)
Assignee: Palantir Technologies Inc.
G06Q10/0635G06Q20/10
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,216,762
App. No.
15/684,507
Granted
Jan 4, 2022
Kind
B1
Abstract

A customer risk trigger associated with a customer may be identified. A response to the customer risk trigger may be detected. First risk analysis data related to the customer risk trigger may be gathered, based on the response, from a first datastore. Second risk analysis data related to the customer risk trigger may be gathered, based on the response, from a second datastore. A customer risk profile to model risk attribute(s) of the customer may be gathered. The risk attributes may represent a risk correlation between the customer and a prohibited act. Customer risk visualization tool(s) configured to facilitate visual user interaction with the customer risk profile may be gathered. The customer risk visualization tools may be rendered in a display of the computing system. The customer risk visualization tools provide a customer-centric view of risk for various applications, including anti-money laundering applications.

Claims (52)

1. A method being implemented by a computing system including one or more physical processors and a storage media storing machine-readable instructions, the method comprising:

receiving a trigger associated with an entity, wherein the trigger is associated with one or more of a request to perform an electronic transfer by the entity, an indication that the entity is on a known suspicious list, and a request by a user of the computing system to access information relating to the entity;

gathering, in response to the trigger, first analysis data from a first datastore, the first analysis data comprising data relating to payments and the first datastore is associated with a payment screening system;

gathering, in response to the trigger, second analysis data from a second datastore, the second analysis data comprising results of criminal activity from an investigation of intermediate and final institutions, and data of biographic and location information associated with the entity;

modeling, based on the first analysis data and the second analysis data, a profile associated with the entity, the profile including one or more attributes that provide information of assets and liabilities in accounts associated with the entity, countries of transactions, institutional codes of the transactions, originators and beneficiaries of the transactions, or a corporate structure of a second entity associated with the entity, the one or more attributes representing a correlation between the entity and a prohibited act;

modifying, based on the correlation, criteria associated with the prohibited act for a specific context;

rendering, based on the profile, using one or more visualization tools, a first tab that, upon selected, displays information of the accounts associated with the entity directly above information of the entity, wherein:

the information of the accounts includes a first column identifying an annual credit and annual debit across the accounts and a second column identifying a risk associated with the accounts, the risk being dynamically updated; and

the information of the entity includes a third column identifying annual sales associated with the entity and a fourth column identifying a risk associated with a related entity to the entity, the fourth column being positioned directly below the second column and the third column being positioned directly below the first column;

rendering, based on the profile, using the one or more visualization tools, a second tab that, upon selection, populates a first region including a filter selection region and a second region including a pictorial depiction that has a connection graph comprising nodes connected by one or more edges, nodes representing the accounts associated with the entity, companies at which the accounts are held and persons accessing the accounts, and the one or more edges representing relationships between the accounts, the companies, and the persons, wherein the second region is populated based on filters selected in the first region; and

rendering, based on the profile, using the one or more visualization tools, a third tab that, upon selection, populates a third region including a second filter selection region and a fourth region including a second pictorial depiction that has a bar graph of transactions associated with the entity, wherein the bar graph provides data relating to transaction volume, transaction value, and average transaction amount over a time period, and wherein the fourth region is populated based on filters selected in the third region.

2. The method of claim 1 , wherein the first datastore comprises an internal datastore.

3. The method of claim 2 , wherein the first analysis data further comprises background data associated with the entity.

4. The method of claim 2 , wherein the first analysis data further comprises transaction data about a transaction requested by the entity.

5. The method of claim 1 , wherein the second datastore further comprises a public financial crimes datastore.

6. The method of claim 1 , wherein the second analysis data further comprises public financial data associated with the entity.

7. The method of claim 1 , wherein the one or more visualization tools are configured to facilitate one or more enhanced due diligence processes to be performed on the first analysis data and the second analysis data associated with the entity.

8. The method of claim 1 , wherein the bar graph further includes a filter to filter the transactions based on account types and transaction amounts.

9. A system comprising:

one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the system to perform:

receiving a trigger associated with an entity, wherein the trigger is associated with one or more of a request to perform an electronic transfer by the entity, an indication that the entity is on a known suspicious list, and a request by a user of the computing system to access information relating to the entity;

gathering, in response to the trigger, first analysis data from a first datastore, the first analysis data comprising data relating to payments and the first datastore is associated with a payment screening system;

gathering, in response to the trigger, second analysis data from a second datastore, the second analysis data comprising results of criminal activity from an investigation of intermediate and final institutions, and data of biographic and location information associated with the entity;

modeling, based on the first analysis data and the second analysis data, a profile associated with the entity, the profile including one or more attributes that provide information of assets and liabilities in accounts associated with the entity, countries of transactions, institutional codes of transactions, originators and beneficiaries of transactions, or a corporate structure of a second entity associated with the entity, the one or more attributes representing a correlation between the entity and a prohibited act;

modifying, based on the correlation, criteria associated with the prohibited act for a specific context;

rendering, based on the profile, using one or more visualization tools, a first tab that, upon selected, displays information of the accounts associated with the entity directly above information of the entity, wherein:

the information of the accounts includes a first column identifying an annual credit and annual debit across the accounts and a second column identifying a risk associated with the accounts, the risk being dynamically updated; and

the information of the entity includes a third column identifying annual sales associated with the entity and a fourth column identifying a risk associated with a related entity to the entity, the fourth column being positioned directly below the second column and the third column being positioned directly below the first column;

rendering, based on the profile, using the one or more visualization tools, a second tab that, upon selection, populates a first region including a filter selection region and a second region including a pictorial depiction that has a connected graph comprising nodes connected by one or more edges, the nodes representing the accounts associated with the entity, companies at which the accounts are held and persons accessing the accounts, and the one or more edges representing relationships between the accounts, the companies, and the persons, wherein the second region is populated based on filters selected in the first region; and

rendering, based on the profile, using the one or more visualization tools, a third tab that, upon selection, populates a third region including a second filter selection region and a fourth region including a second pictorial depiction that has a bar graph of transactions associated with the entity, wherein the bar graph provides data relating to transaction volume, transaction value, and average transaction amount over a time period, and wherein the fourth region is populated based on filters selected in the third region.

10. The system of claim 9 , wherein the first datastore comprises an internal datastore.

11. The system of claim 10 , wherein the first analysis data further comprises background data associated with the entity.

12. The system of claim 10 , wherein the first analysis data further comprises transaction data about a transaction requested by the entity.

13. The system of claim 9 , wherein the second datastore further comprises a public financial crimes datastore.

14. The system of claim 9 , wherein the second analysis data further comprises public financial data associated with the entity.

15. The system of claim 9 , wherein the one or more visualization tools are configured to facilitate one or more enhanced due diligence processes to be performed on the first analysis data and the second analysis data associated with the entity.

16. The system of claim 9 , wherein the one or more visualization tools are configured to display one or more of an originator of a non-currency transfer, a beneficiary of the non-currency transfer, or one or more discrepancies between the non-currency transfer and past transfers performed by the entity.

17. A non-transitory computer readable storage media of a computing system storing instructions that, when executed by one or more processor of the computing system, cause the computing system to:

receiving a trigger associated with an entity, wherein the trigger is associated with one or more of a request to perform an electronic transfer by the entity, an indication that the entity is on a known suspicious list, and a request by a user of the computing system to access information relating to the entity;

gathering, in response to the trigger, first analysis from a first datastore, the first analysis data comprising data relating to payments and the first datastore is associated with a payment screening system;

gathering, in response to the trigger, second analysis data from a second datastore, the second analysis data comprising results of criminal activity from an investigation of intermediate and final institutions, and data of biographic and location information associated with the entity;

modeling, based on the first analysis data and the second analysis data, a profile associated with the entity, the profile including one or more attributes that provide information of assets and liabilities in accounts associated with the entity, countries of transactions, institutional codes of transactions, originators and beneficiaries of transactions, or a corporate structure of a second entity associated with the entity, the one or more attributes representing a correlation between the entity and a prohibited act;

modifying, based on the correlation, criteria associated with the prohibited act for a specific context;

rendering, based on the profile, using one or more visualization tools, a first tab that, upon selected, displays information of the accounts associated with the entity directly above information of the entity, wherein:

the information of the accounts includes a first column identifying an annual credit and annual debit across the accounts and a second column identifying a risk associated with the accounts, the risk being dynamically updated; and

the information of the entity includes a third column identifying annual sales associated with the entity and a fourth column identifying a risk associated with a related entity to the entity, the fourth column being positioned directly below the second column and the third column being positioned directly below the first column;

rendering, based on the profile, using the one or more visualization tools, a second tab that, upon selection, populates a first region including a filter selection region and a second region including a pictorial depiction that has a connection graph comprising nodes connected by one or more edges, the nodes representing the accounts associated with the entity, companies at which the accounts are held and persons accessing the accounts, and the one or more edges representing relationships between the accounts, the companies, and the persons, wherein the second region is populated based on filters selected in the first region; and

rendering, based on the profile, using the one or more visualization tools, a third tab that, upon selection, populates a third region including a second filter selection region and a fourth region including a second pictorial depiction that has a bar graph of transactions associated with the entity, wherein the bar graph provides data relating to transaction volume, transaction value, and average transaction amount over a time period, and wherein the fourth region is populated based on filters selected in the third region.

18. The non-transitory storage media of claim 17 , wherein the second datastore further comprises a public financial crimes datastore.

19. The non-transitory storage media of claim 17 , wherein the second analysis data further comprises public financial data associated with the entity.

20. The non-transitory storage media of claim 17 , wherein the one or more visualization tools are configured to facilitate one or more enhanced due diligence processes to be performed on the first analysis data and the second analysis data associated with the entity.

Assignments (2)
SECURITY INTEREST Recorded Jul 3, 2022
From: PALANTIR TECHNOLOGIES INC.
To: WELLS FARGO BANK, N.A.
Reel/Frame 060572/0506 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 10, 2018
From: MAASS, ALEXANDER; REGEV, BEN; HOFFMAN, DUNCAN; MAK, EUGENE; NORMAN, ELISE; PATITUCCI, ELIZABETH; KAMBERGER, KAI; SHEVCHUK, YEVHEN; SINGH, HARKIRAT; ASCHHEIM, JOSHUA; PUIG, JUAN JIMENEZ; VAN DEN BERGH, JORIEN; BISKUPIAK, MACIEJ; MIRACOLO, MARISSA; WILSON, MATTHEW JULIUS; PRETTEJOHN, NICOLAS; WALTER, PATRICK; PATEL, ROOTUL; HEITKAMP, STEPHEN; DEITCH, RICHARD
To: PALANTIR TECHNOLOGIES INC.
Reel/Frame 046124/0528 →
Continuity (1)
Provisional Application 62532193 · Jul 13, 2017