Fraud Detection with Amazon Machine Learning on AWS
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Many customers across every market segment are interested in applying AI techniques to provide some kind of automated reasoning to many areas of real-time analytics where, traditionally, a human being or perhaps a rule-based expert system was the final arbitrer.
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Fraud Detection with Amazon Machine Learning on AWS
- 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Dr. Andrew Kane, Solutions Architect drandrewkane 21st September 2017 Fraud Detection and Machine Learning on AWS
- 2. Payments fraud is an ongoing concerns for Financial Services (FS) organizations. $8.5b of fraud losses in the US* $21.8b of fraud losses globally* * From The Nilson Report (https://www.nilsonreport.com/constant_contact_promo.php?id_promo=8) $31.7b of projected fraud losses globally in 2020* In 2015…
- 3. Addresses endpoint authentication Layer 1 Solving for Multiple Layers Simultaneously
- 4. Addresses endpoint authentication Layer 1 Analyzes session behavior Layer 2 Solving for Multiple Layers Simultaneously
- 5. Addresses endpoint authentication Layer 1 Analyzes session behavior Layer 2 Monitors account behavior for a channel Layer 3 Solving for Multiple Layers Simultaneously
- 6. Addresses endpoint authentication Layer 1 Analyzes session behavior Layer 2 Monitors account behavior for a channel Layer 3 Monitoring account behavior across multiple channels Layer 4 Solving for Multiple Layers Simultaneously
- 7. Addresses endpoint authentication Layer 1 Analyzes session behavior Layer 2 Monitors account behavior for a channel Layer 3 Monitoring account behavior across multiple channels Layer 4 Monitoring multiple account behaviors across multiple channels Layer 5 Solving for Multiple Layers Simultaneously
- 9. Rules Fall Short for Fraud Detection Static set of rules
- 10. Rules Fall Short for Fraud Detection Static set of rules Human errors & bias
- 11. Rules Fall Short for Fraud Detection Static set of rules Difficult to manageHuman errors & bias
- 12. Rules Fall Short for Fraud Detection Static set of rules Difficult to manageHuman errors & bias Cannot scale
- 13. Solution Requirements • Process billions of transactions a day
- 14. Solution Requirements • Process billions of transactions a day • Make decisions in milliseconds
- 15. Solution Requirements • Process billions of transactions a day • Make decisions in milliseconds • Train with large amounts of data
- 16. Solution Requirements • Process billions of transactions a day • Make decisions in milliseconds • Train with large amounts of data • Secure and Align to compliance requirements
- 17. Solution Requirements • Process billions of transactions a day • Make decisions in milliseconds • Train with large amounts of data • Secure and Align to compliance requirements • Low cost
- 18. Solution Requirements • Process billions of transactions a day • Make decisions in milliseconds • Train with large amounts of data • Secure and Align to compliance requirements • Low cost • Flexible and Adaptable
- 19. Solution Requirements • Process billions of transactions a day • Make decisions in milliseconds • Train with large amounts of data • Secure and Align to compliance requirements • Low cost • Flexible and Adaptable • Agile and Scalable
- 20. Overview of Machine Learning
- 24. Supervised Learning Input Outcome Input Input Input Outcome Outcome Outcome Supervised Learning Known Historical Data
- 25. Supervised Learning Input Outcome Input Input Input Outcome Outcome Outcome Supervised Learning Unseen Input Same Outcome Known Historical Data
- 26. Tools of the Trade
- 27. Amazon Simple Storage Service (S3) • Highly scalable object storage • Files are stored as objects and organized into high-level folders called buckets • Store and retrieve data from anywhere on the web • Native support for encryption at rest • Data in transit to/from S3 encrypted using SSL • Highly durable (99.999999999% design) • Limitlessly scalable and PAYG • Integration with other AWS services
- 28. Amazon Elastic Map Reduce (EMR) • Managed platform • MapReduce, Apache Spark, Presto • Launch a cluster in minutes • Open source distribution & MapR distribution • Elasticity of the cloud • Support for encryption at rest and in transit • Pay by the second and save with Spot • Flexibility to customize
- 29. An Example EMR Cluster Master Node r3.2xlarge NameNode (HDFS) ResourceManager (YARN)
- 30. An Example EMR Cluster Master Node r3.2xlarge Slave Group - Core c3.2xlarge HDFS (DataNode). YARN (NodeManager). NameNode (HDFS) ResourceManager (YARN)
- 31. An Example EMR Cluster Master Node r3.2xlarge Slave Group - Core c3.2xlarge Slave Group – Task m3.xlarge HDFS (DataNode). YARN (NodeManager). NameNode (HDFS) ResourceManager (YARN)
- 32. An Example EMR Cluster Master Node r3.2xlarge Slave Group - Core c3.2xlarge Slave Group – Task m3.xlarge Slave Group – Task m3.2xlarge (EC2 Spot) HDFS (DataNode). YARN (NodeManager). NameNode (HDFS) ResourceManager (YARN)
- 33. Hadoop Applications Available in Amazon EMR Processing Databases Analytics
- 34. Amazon Machine Learning • Easy-to-use service built for developers • Robust, powerful, and technology-based • Ability to create models using your data • Deployable to production in seconds
- 35. Amazon Machine Learning Service
- 36. Amazon Machine Learning Service
- 37. Amazon Machine Learning Service
- 38. Amazon Machine Learning Service
- 39. Explore and Understand Your Data
- 40. Explore and Understand Your Data
- 41. Explore and Understand Your Data
- 42. Explore and Understand Your Data
- 43. Explore and Understand Your Data
- 44. Explore and Understand Your Data
- 45. Evaluate and Explore Model Performance
- 46. Evaluate and Explore Model Performance
- 47. Evaluate and Explore Model Performance
- 48. Evaluate and Explore Model Performance
- 50. Credit Card Transaction Dataset Customer Profile
- 51. Credit Card Transaction Dataset Customer Profile Store Profile
- 52. Credit Card Transaction Dataset Customer Profile Store Profile Transaction Details
- 53. Model Creation and Training – Reference Architecture
- 54. Model Creation and Training – Reference Architecture
- 55. Corporate Data Center Model Creation and Training – Reference Architecture
- 56. Corporate Data Center Model Creation and Training – Reference Architecture AWS Direct Connect
- 57. Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 58. AWS IAM Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 59. Amazon CloudWatch AWS CloudTrail AWS IAM AWS Config Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 60. Amazon CloudWatch AWS CloudTrail AWS IAM AWS Config AWS KMS Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 61. Amazon CloudWatch AWS CloudTrail AWS IAM AWS Config AWS KMS Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 62. Amazon CloudWatch AWS CloudTrail AWS IAM AWS Config AWS KMS Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 63. Amazon CloudWatch AWS CloudTrail AWS IAM AWS Config AWS KMS EMR MLlib Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 64. Amazon CloudWatch AWS CloudTrail AWS IAM Amazon RDS SSL/TLS AWS Config AWS KMS EMR MLlib Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 65. Amazon CloudWatch AWS CloudTrail AWS IAM Amazon RDS SSL/TLS Amazon Machine Learning SSL/TLS AWS Config AWS KMS EMR MLlib Corporate Data Center Amazon S3 Model Creation and Training – Reference Architecture AWS Direct Connect
- 66. EMR Amazon RDS Amazon Machine Learning SSL/TLS SSL/TLS SSL/TLS MLlib AWS Direct Connect Amazon CloudWatch AWS CloudTrail AWS IAM Amazon S3 AWS Config AWS KMS Online Fraud Detection – Reference Architecture Corporate Data Center
- 67. IPSEC EMR Amazon RDS Amazon Machine Learning SSL/TLS SSL/TLS SSL/TLS MLlib AWS Direct Connect Amazon CloudWatch AWS CloudTrail AWS IAM Amazon S3 AWS Config AWS KMS Online Fraud Detection – Reference Architecture Corporate Data Center
- 68. IPSEC EMR Amazon RDS Amazon Machine Learning SSL/TLS SSL/TLS SSL/TLS MLlib AWS Elastic Beanstalk App AWS Direct Connect Amazon CloudWatch AWS CloudTrail AWS IAM Amazon S3 AWS Config AWS KMS Online Fraud Detection – Reference Architecture Corporate Data Center
- 69. IPSEC EMR Amazon RDS Amazon Machine Learning SSL/TLS SSL/TLS SSL/TLS SSL/TLS MLlib AWS Elastic Beanstalk App AWS Direct Connect Amazon CloudWatch AWS CloudTrail AWS IAM Amazon S3 AWS Config AWS KMS Online Fraud Detection – Reference Architecture Corporate Data Center
- 70. The Outcomes of the AWS Solution Cost: Solution price down from $100K to $10K
- 71. The Outcomes of the AWS Solution Cost: Solution price down from $100K to $10K Speed: Development down from months to days
- 72. The Outcomes of the AWS Solution Cost: Solution price down from $100K to $10K Speed: Development down from months to days Resources: Focus shift from management to development
- 73. Next Evolution of the Platform
- 74. IPSEC EMR Amazon RDS Amazon Machine Learning SSL/TLS SSL/TLS SSL/TLS SSL/TLS MLlib AWS Elastic Beanstalk App AWS Direct Connect Amazon CloudWatch AWS CloudTrail AWS IAM Amazon S3 AWS Config AWS KMS Online Fraud Detection – Reference Architecture Corporate Data Center
- 75. Amazon RDS Amazon Machine Learning AWS Direct Connect AWS Lambda Amazon DynamoDB Amazon CloudWatch AWS CloudTrail AWS IAM AWS Config AWS KMS Amazon S3 Corporate Data Center Online Fraud Detection – Future State IPSEC SSL/TLS Amazon API Gateway
- 76. Thank You!