Automated method and system for a gaming opportunity

• US 20080261701A1
• Filed: 08/13/2007
• Published: 10/23/2008
• Est. Priority Date: 04/18/2007
• Status: Abandoned Application

• Current Assignee: Technology Assurance Laboratory Incorporated
• Original Assignee: Technology Assurance Laboratory Incorporated
• Inventors: Ito, Taro, Chu, Leo, Lewin, Bart A.
• Application Number:
  US11/889,363
• Publication Number:
  US 20080261701A1
• Time in Patent Office: Days
• US Class Current: 463/43
• CPC Class Codes: G07F 17/32 for games, toys, sports, or amusements
• CPC Class Codes: G07F 17/3237 about the players, e.g. profiling, responsible gaming, strategy/behavior of players, location of players
• CPC Class Codes: G07F 17/3241 Security aspects of a gaming system, e.g. detecting cheating, device integrity, surveillance computer security G06F21/00

Abstract

A method and system of screening a player for a gaming opportunity, including obtaining disparate data of a player from a plurality of data sources, weighting the player data based on at least one business rule, and applying the weighted player data to at least one decision model to generate at least one composite score indicative of a scale of eligibility of the player for the gaming opportunity.

Claims

1. A method of screening a player for a gaming opportunity, comprising the steps of:

obtaining disparate data of a player from a plurality of data sources;

weighting the player data based on at least one business rule; and

applying the weighted player data to at least one decision model to generate at least one composite score indicative of a scale of eligibility of the player for the gaming opportunity.

2. The method of claim 1, wherein the player data obtained from the data sources may be changed manually.

3. The method of claim 1, further including the step of randomly selecting the player for a manual screening process.

4. The method of claim 1, further comprising the step of validating the player data.

5. The method of claim 4, wherein the step of validating the player data includes the step of verifying the player data using at least one independent data source.

6. The method of claim 1, wherein the business rule includes jurisdictional requirements.

7. The method of claim 1, wherein the business rule includes age requirements of the player.

8. The method of claim 1, wherein the business rule includes an exclusion list.

9. The method of claim 1, wherein the business rule includes a player skill level requirement.

10. The method of claim 1, wherein the business rule includes a cost of annoyance.

11. The method of claim 1, wherein the business rule includes a history of use by the player of impermissible playing methods.

12. The method of claim 1, wherein the player data include location information of the player.

13. The method of claim 12, wherein the player location information is obtained from at least one of

an IP address,

a Media Access Control (MAC) address,

a serial number of a device from which the player requested access,

reverse email directories, and

gaming facility databases.

14. The method of claim 1, wherein weights for the weighting is adjustable.

15. The method of claim 1, wherein the player data are weighted based on age of the player data.

16. The method of claim 1, wherein the player data are weighted based on accuracy.

17. The method of claim 1, wherein regulatory criteria are given the greatest weight.

18. The method of claim 1, wherein the player data are weighted based on comparison to a range of values observed in other players.

19. The method of claim 1, wherein the step of weighting includes nested business rules to weight the player data.

20. The method of claim 1, wherein the at least one decision model includes a feedback loop.

21. The method of claim 1, wherein the at least one decision model includes predictive statistical modeling.

22. The method of claim 1, wherein the at least one decision model includes an adaptive algorithm.

23. The method of claim 22, wherein the adaptive algorithm is at least one of a logical multiple regression, a neural network, a Bayesian classification, a variance analysis, and a classification tree.

24. The method of claim 1, wherein the composite score includes at least one base score.

25. The method of claim 24, wherein the base score is adjustable based on any one of

(a) weight of the player data used to calculate the base score,

(b) accuracy of the player data used to calculate the base score,

(c) age of the player data used to calculate the base score, and

(d) completeness of the player data used to calculate the base score.

26. The method of claim 1, wherein the composite score includes an averaged base score.

27. The method of claim 26, wherein at least one composite score is calculated as an average of at least two base scores.

28. The method of claim 1, further comprising the step of indicating eligibility of the player for the gaming opportunity if the composite score is within a first range.

29. The method of claim 1, further comprising the step of indicating ineligibility of the player for the gaming opportunity if the composite score is within a second range.

30. The method of claim 1, further comprising the step of indicating conditional eligibility of the player for the gaming opportunity if the composite score is above a first threshold but below a second threshold.

31. The method of claim 30, wherein the first and second thresholds are adjustable.

32. The method of claim 1, further comprising the step of determining a cost of annoyance when the composite score is within a second range.

33. The method of claim 32, wherein the step of determining the cost of annoyance includes analyzing any one of a cost of allowing the player to play, a cost of not allowing the player to play, and probability of losing future revenue from the player.

34. The method of claim 32, wherein the step of determining the cost of annoyance is based on estimated player revenue, probability that the player will not leave, cost of allowing the player to play, and probability that the player is ineligible.

35. The method of claim 34, wherein the estimated player revenue is calculated based on a theoretical win per game and number of times an average player plays a game.

36. The method of claim 32, further comprising the step of indicating eligibility of the player for the gaming opportunity if the cost of annoyance is within a third range.

37. The method of claim 32, further comprising the step of indicating ineligibility of the player for the gaming opportunity if the cost of annoyance is within a fourth range.

38. The method of claim 32, further comprising the step of manually screening the player for eligibility of the gaming opportunity if the cost of annoyance is between a third and fourth threshold.

39. The method of claim 32, wherein the step of determining the cost of annoyance includes subtracting the cost of a false positive from the revenue lost from not allowing the player to play.

40. The method of claim 32, wherein the step of determining the cost of annoyance includes subtracting cost of a false negative from the cost of allowing the player to play.

41. The method of claim 30, wherein the conditional eligibility includes an obligation to receive coaching during play.

42. The method of claim 41, wherein coaching is provided according to at least one gaming strategy.

43. The method of claim 41, wherein coaching is provided if the player has less than a predetermined credit rating.

44. The method of claim 41, wherein coaching is provided if the player is below a predetermined level of playing experience.

45. The method of claim 41, wherein coaching is provided from a compilation of tips from at least one gaming celebrity.

46. The method of claim 30, wherein the conditional eligibility includes an obligation for the player to play according to at least one predetermined gaming strategy.

47. The method of claim 46, wherein the at least one predetermined gaming strategy is required if the player is below a predetermined level of playing experience.

48. The method of claim 46, further comprising the step of monitoring the player for compliance with the at least one predetermined gaming strategy.

49. The method of claim 28, wherein the player with the composite score within the first range is allowed to play in an automated playing mode.

50. The method of claim 46, wherein the player playing according to the at least one predetermined gaming strategy is allowed to play in an automated playing mode.

51. A system for screening a player for a gaming opportunity, comprising:

a server configured to communicate with a player device, the server including

a data collection module to obtain disparate data of the player from a plurality of data sources,

a rules module to weight the player data based on at least one business rule, and

a decision module to apply the weighted player data to at least one decision model to generate at least one composite score indicative of a scale of eligibility of the player for the gaming opportunity.

52. A computer program product comprising computer readable medium having stored thereon computer executable instructions that, when executed on a computer, causes the computer to perform a method of screening a player for a gaming opportunity comprising the steps of:

obtaining disparate data of a player from a plurality of data sources;

weighting the player data based on at least one business rule; and

applying the weighted player data to at least one decision model to generate at least one composite score indicative of a scale of eligibility of the player for the gaming opportunity.