Computer-based systems and method for computing a score for contacts of a financial services firm indicative of resources to be deployed by the financial services firm for the contacts to maximize revenue for the financial services firm

• US 8,566,146 B1
• Filed: 05/10/2012
• Issued: 10/22/2013
• Est. Priority Date: 05/10/2012
• Status: Active Grant

• Current Assignee: Morgan Stanley Services Group Inc. (Morgan Stanley)
• Original Assignee: Morgan Stanley & Company LLC (Morgan Stanley)
• Inventors: Hurewitz, Barry S., Solomon, Scott, Rachidi, Thami, Moustafa, Omar, Fleming, Lauren, Treder, Robert, Harvey, Vaughn S.
• Primary Examiner(s): Jarrett, Scott L
• Application Number:
  US13/468,348
• Time in Patent Office: 530 Days
• Field of Search: 705/7.38, 705/7.39, 705/7.41
• US Class Current: 705/7.38
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

Computer-based systems and methods for computing a score (a “target score”) for the contacts of a research department. The target score may be computed for each contact for each analyst team of the research department. The target score indicates how resources should be deployed by the research department to maximize revenue for the research department. The target score is computed based on a number of metrics. These metrics can include both analyst-team-specific contact metrics that relate to the contact-analyst team combination, as well as account metrics that pertain to the investment accounts associated with each of the contacts. Weights for the metrics may be determined using an optimization algorithm.

Claims

1. A computer-implemented method for computing a target score for one or more contacts of a financial services firm indicative of resources to be deployed by the financial services firm for the contacts to maximize revenue for the financial services firm, wherein the financial services firm comprises a plurality of employee teams that produce research pertaining to at least one of financial instruments, industries and geographic regions, wherein each of the one or more contacts is associated with an account for holding and trading financial instruments, and wherein the one or more contacts comprise consumers of the research, the method comprising:

determining, by a computer system, for the one or more contacts, a value for each of a plurality of metrics that are used to compute the target scores for the contacts, wherein the plurality of metrics comprise, for each of the one or more contacts, at least;

a contact-employee team revenue metric that, for each of the one or more employee teams, is related to revenue of the employee team from the account associated with the contact over a prior time period that is allocated to the contact, wherein;

revenue from the contact'"'"'s account is based on trade execution revenue of the financial services firm for the account;

revenue of the financial services firm from the contact'"'"'s account is allocated to the one or more employee teams based on at least service provided by the employee teams to the account associated with the contact; and

revenue of the financial services firm from the contact'"'"'s account allocated to the one or more employee teams is allocated to the contact based on at least service provided to the contact by the one or more employee teams; and

for the one or more employee teams, a contact revenue per unit time metric that is related to a ratio of (i) the revenue for the employee team from the contact'"'"'s account that is allocated to the contact, to (ii) the time duration of the interactions by the contact with employees of the financial services firm over a prior time period; and

at least one or more of the following metrics for each of the one or more contacts;

a contact priority metric for each employee team, indicative of whether the contact is priority for the employee team; and

an account tier metric indicative of a service tier for the account associated with the contact;

storing the values for the plurality of metrics in a computer data storage system of the computer system;

determining, by the computer system, by using an optimization algorithm, weights for each of the plurality of metrics that maximizes revenue of the financial services firm by maximizing a sum of the revenue for each employee team from each of the one or more contacts per a unit time subject to one or more constraints; and

computing by the computer system the target score for each of the one or more contacts for each employee team based on at least (i) the values for each of the plurality of metrics for each of the one or more contacts stored in the computer data storage system and (ii) the weights,

wherein;

contacts with greater target scores are targeted for more service from the financial services firm; and

the one or more constraints for the optimization algorithm comprise at least one constraint on availability for interactions between the employees and the contacts.

2. The method of claim 1, wherein computing the target score for one contact for one employee team comprises:

computing a product for each of the plurality of metrics by multiplying (i) the weight for each of the plurality of metrics by (ii) the value for the metric of the contact for the employee team; and

summing the plurality of products.

3. The method of claim 1, wherein determining the weights comprises determining the weights using a heuristic optimization algorithm.

4. The method of claim 1, wherein determining the weights comprises determining the weights using a probabilistic optimization algorithm.

5. The method of claim 1, wherein the one or more constraints comprises a constraint that each employee team interacts with a maximum number of contacts per the unit time.

6. The method of claim 1, wherein the one or more constraints comprises a constraint that each contact interacts with a maximum number of employee teams per the unit time.

7. The method of claim 1, wherein the one or more constraints comprises:

a first constraint that each employee team interacts with a maximum number of contacts per the unit time; and

a second constraint that each contact interacts with a maximum number of employee teams per the unit time.

8. The method of claim 7, wherein:

the one or more constraints comprises a third constraint that limits revenue from the accounts of the one or more contacts.

9. The method of claim 1, wherein the weights are the same for each employee team.

10. The method of claim 1, wherein a first employee team has a first set of weights and a second employee team has a second set of weights.

11. The method of claim 1, wherein the plurality of metrics further comprise

an account elasticity metric for the account associated with each contact.

12. The method of claim 1, wherein the plurality of metrics comprise both the contact-employee team revenue metric and the a contact revenue per unit time metric for the one or more employee teams.

13. The method of claim 12, wherein the plurality of metrics comprise further comprise both the contact priority metric and the account tier metric.

15. The computer system of claim 1, wherein the at least one processor is programmed to compute the target score for one contact for one employee team by:

computing a product for each of the plurality of metrics by multiplying (i) the weight for each of the plurality of metrics by (ii) the value for the metric of the contact for the employee team; and

summing the plurality of products.

14. A computer system for computing a target score for one or more contacts of a financial services firm indicative of resources to be deployed by the financial services firm for the contacts to maximize revenue for the financial services firm, wherein the financial services firm comprises a plurality of employee teams that produce research pertaining to at least one of financial instruments, industries and geographic regions, wherein each of the one or more contacts is associated with an account for holding and trading financial instruments, and wherein the one or more contacts comprise consumers of the research, the computer system comprising:

a computer data storage system; and

at least one processor in communication with the compute data storage system, wherein the at least one processor is programmed to;

determine, for the one or more contacts, a value for each of a plurality of metrics that are used to compute the target scores for the contacts, wherein the value for the plurality of metrics are stored in the computer data storage, and wherein the plurality of metrics comprise, for each of the one or more contacts, at least;

a contact-employee team revenue metric that, for each of the one or more employee teams, is related to revenue of the employee team from the account associated with the contact over a prior time period that is allocated to the contact, wherein;

revenue from the contact'"'"'s account is based on trade execution revenue of the organization for the account;

revenue of the organization from the contact'"'"'s account is allocated to the one or more employee teams based on at least service provided by the employee teams to the account associated with the contact; and

revenue of the organization from the contact'"'"'s account allocated to the one or more employee teams is allocated to the contact based on at least service provided to the contact by the one or more employee teams; and

for the one or more employee teams, a contact revenue per unit time metric that is related to a ratio of (i) the revenue for the employee team from the contact'"'"'s account that is allocated to the contact, to (ii) the time duration of the interactions by the contact with employees of the organization over a prior time period; and

at least one or more of the following metrics for each of the one or more contacts;

a contact priority metric for each employee team, indicative of whether the contact is priority for the employee team; and

an account tier metric indicative of a service tier for the account associated with the contact;

determine, by using an optimization algorithm, weights for each of the plurality of metrics that maximizes revenue of the financial services by maximizing a sum of the revenue for each employee team from the one or more contacts per a unit time subject to one or more constraints; and

compute the target score for each of the one or more contacts for each employee team based on at least (i) the values for the plurality of metrics for each of the one or more contacts stored in the computer data storage system and (ii) the weights,

wherein;

contacts with greater target scores are targeted for more service from the organization; and

the one or more constraints for the optimization algorithm comprise at least one constraint on availability for interactions between the employees and the contacts.

16. The computer system of claim 14, wherein a heuristic optimization algorithm is used to determine the weights.

17. The computer system of claim 14, wherein a probabilistic optimization algorithm is used to determine the weights.

18. The computer system of claim 14, wherein the one or more constraints comprises a constraint that each employee team interacts with a maximum number of contacts per the unit time.

19. The computer system of claim 14, wherein the one or more constraints comprises a constraint that each contact interacts with a maximum number of employee teams per the unit time.

20. The computer system of claim 14, wherein the one or more constraints comprises:

a first constraint that each employee team interacts with a maximum number of contacts per the unit time; and

a second constraint that each contact interacts with a maximum number of employee teams per the unit time.

21. The computer system of claim 20, wherein:

the one or more constraints comprises a third constraint that limits revenue from the accounts of the one or more contacts.

22. The computer system of claim 14, wherein the weights are the same for each employee team.

23. The computer system of claim 14, wherein a first employee team has a first set of weights and a second employee team has a second set of weights.

24. The computer system of claim 14, wherein the plurality of metrics further comprise

an account elasticity metric for the account associated with each contact.

25. The computer system of claim 14, wherein the plurality of metrics comprise both the contact-employee team revenue metric and the contact revenue per unit time metric for the one or more employee teams.

26. The computer system of claim 25, wherein the plurality of metrics comprise further comprise both the contact priority metric and the account tier metric.