Abstract: A prediction system, with at least one processor configured to: acquire a plurality of candidates of information influencing an ease of obtaining a desired result in a predetermined service; predict, for each of the plurality of candidates, based on a predetermined prediction method, whether the desired result is obtained; and identify the candidates predicted to obtain the desired result.

Abstract: At least one processor of a fraud detection system detects a login of a user in a predetermined service. The least one processor displays a user information screen for changing or registering user information on a display for the user who has logged in to the service. The least one processor acquires action information relating to an action of the user in at least a part of a period from detection of the login to display of the user information screen. The least one processor detects fraud by the user based on the action information.

Abstract: A service providing system provides a service allowed to be logged in to from each of a plurality of user terminals. At least one processor is configured to execute predetermined authentication for each of the user terminals under a state in which the service has been logged in to from the user terminal. The at least one processor performs a setting relating to the service for each of the user terminals based on whether the authentication has been executed from the user terminal. The service is provided to each of the user terminals based on the setting of the user terminal.

Abstract: A fraud detection system, comprising at least one processor configured to: acquire, based on a first fraud detection engine for detecting a fraud in a first service, a second fraud detection engine for detecting a fraud in a second service; acquire fraud information relating to a fraud that has actually occurred in the second service; determine, based on the fraud information, whether a fraud in the second service is detectable by the second fraud detection engine; and apply, when it is determined that a fraud in the second service is detectable by the second fraud detection engine, the second fraud detection engine to the second service.

Abstract: A learning system, comprising at least one processor configured to: determine whether each of a plurality of pieces of first data satisfies a first condition relating to labeling; create a first learning model capable of the labeling based on a first group being a group of pieces of the first data which satisfy the first condition and which are labeled; convert a second group being a group of pieces of the first data which do not satisfy the first condition and which are not labeled so that a distribution of the second group is close to a distribution of the first group; and execute the labeling for the second group based on the first learning model and the second group.

Abstract: A fraud detection system, comprising at least one processor configured to: acquire, based on a first fraud detection engine for detecting a fraud in a first service, a second fraud detection engine for detecting a fraud in a second service; acquire fraud information relating to a fraud that has actually occurred in the second service; determine, based on the fraud information, whether a fraud in the second service is detectable by the second fraud detection engine; and apply, when it is determined that a fraud in the second service is detectable by the second fraud detection engine, the second fraud detection engine to the second service.

Abstract: A fraud detection system, comprising at least one processor configured to: acquire user feature information relating to a feature of a user in a first service; acquire user identification information with which the user is identifiable; acquire, based on the user identification information, result information relating to a result of fraud detection of the user in a second service which uses a different fraud detection engine for detecting a fraud from a fraud detection engine of the first service, and detect a fraud in the first service based on the user feature information in the first service and the result information in the second service.

Abstract: At least one processor of a learning model creating system acquires authenticated information relating to an action of an authenticated user who has executed a predetermined authentication from a user terminal from which a predetermined service is usable. At least one processor creates, based on the authenticated information, a learning model for detecting fraud in the service such that the action of the authenticated user is estimated to be valid.

Abstract: At least one processor of a fraud detection system detects a login of a user in a predetermined service. The least one processor displays a user information screen for changing or registering user information on a display for the user who has logged in to the service. The least one processor acquires action information relating to an action of the user in at least a part of a period from detection of the login to display of the user information screen. The least one processor detects fraud by the user based on the action information.

Abstract: A storage of an estimation system stores a learning model which has learned a relationship between first position information which is based on a position of a first location visited by a first user in past and second position information which is based on a position of a second location visited by the first user after the first location. At least one processor of the estimation system acquires third position information which is based on a position of a third location being a location visited by a second user in the past. The at least one processor acquires output of the learning model corresponding to the third position information as an estimation result of fourth position information which is based on a position of a fourth location being a location that is likely to be visited by the second user in future.

Abstract: A fraud detection system including at least one processor configured to: calculate a fraud level of a user who uses a service based on a behavior of the user; obtain a determination result as to whether the behavior is actually fraudulent; and calculate accuracy of fraud detection for each user based on the fraud level and the determination result.

Abstract: Provided is a call subject determination system including at least one processor configured to: predict, for each of a plurality of call candidates, a return call probability, which is a probability of the call candidate returning a phone call instead of answering the phone call; acquire a call taker constraint, which is a constraint in terms of capacity of a call taker who takes the returned phone call; and determine, from the plurality of call candidates, a plurality of call subjects to whom phone calls are to be made so that the call taker constraint is satisfied, based on the return call probability of the each of the plurality of call candidates.

Abstract: Provided is a call subject determination system including at least one processor configured to: predict, for each of a plurality of call candidates, a talk probability, which is a probability of succeeding in holding a phone talk with the call candidate; predict, for each of the plurality of call candidates, an advantageous result to be gained from the phone talk with the call candidate; acquire a talker constraint, which is a constraint in terms of capacity of a talker; and determine, from among the plurality of call candidates, a plurality of call subjects to whom phone calls are to be made so that the talker constraint is satisfied and great advantageous results are gained from the plurality of call subjects on the whole, based on the talk probability and the advantageous result of the each of the plurality of call candidates.

Abstract: Relevance information obtaining means of a fraud estimation system is configured to obtain relevance information about relevance between one service and another service. Comparison result obtaining means is configured to obtain a comparison result of a comparison between user information of a target user in the one service and user information of a fraudulent user or an authentic user in the another service. Estimation means is configured to estimate fraudulence of the target user based on the relevance information and the comparison result.

Abstract: A fraud detection system for executing predetermined processing when a detection target is detected by using a detection device, the fraud detection system comprising at least one processor which determines, before the detection target is detected, whether a predetermined action has been performed by a user having a user terminal; executes, when it is determined that the predetermined action has been performed, fraud detection on the user based on identification information stored in the user terminal; and executes, when the detection target is detected, the predetermined processing based on an execution result of the fraud detection.

Abstract: Disclosed herein is an information processing apparatus, comprising: a memory configured to store program code; and electric circuitry including a processor, the processor being configured to read and operate according to the program code, the electronic circuitry configured to: set a plurality of candidate values of a parameter tunable in a computer system; trial each of the plurality of set candidate values of the parameter to the computer system for a predetermined period of time or a predetermined number of times and to calculate a reward in the computer system; select, when a trial satisfies a predetermined termination criterion, a candidate value of the parameter for which the maximum reward is calculated among the candidate values of the parameter and apply the selected candidate value of the parameter to the computer system; and re-set candidate values of the parameter based on the selected candidate value of the parameter to repeat.

Abstract: A fraud detection system including at least one processor configured to: calculate a fraud level of a user who uses a service based on a behavior of the user; obtain a determination result as to whether the behavior is actually fraudulent and calculate accuracy of fraud detection for each user based on the fraud level and the determination result.

Abstract: A fraud detection system includes at least one processor configured to acquire, based on an action performed by each of a plurality of users, a score relating to a fraud level of the user, determine, based on the score of each of the plurality of users, an acquisition method for a feature amount of the user such that an acquisition time of the feature amount becomes shorter as the fraud level becomes lower, acquire the feature amount of each of the plurality of users based on the acquisition method determined for the user, and detect fraud made by each of the plurality of users based on the feature amount of the user.

Abstract: A prediction system, with at least one processor configured to: acquire a plurality of candidates of information influencing an ease of obtaining a desired result in a predetermined service; predict, for each of the plurality of candidates, based on a predetermined prediction method, whether the desired result is obtained; and identify the candidates predicted to obtain the desired result.

Abstract: Provided is an estimation system including at least one processor configured to: acquire position information on a position of another location visited by a user who has visited an estimation target location which is a location for which an attribute is to be estimated; acquire a positional relationship between a position of the estimation target location and the position indicated by the position information; and estimate the attribute of the estimation target location based on the positional relationship.