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June 2013
Risk & Compliance Engineering, PayPal
Pradeep Ballal
Staale Nerboe
Greg Berry
This deck contains generic architecture information, and does not
reflect the exact details of current or planned systems.
Decisions as a Service
Confidential and Proprietary2
• Encompasses processes to improve, streamline and
automate operational decision making within organizations.
• Use all available organizational resources to increase
precision, consistency and agility of decisions.
• Treat decisions as reusable assets and leverage technology
at key decision points to automate the process.
• Uses tools such as
Predictive Analytics
Business Intelligence
Business Rules
Adaptive Control
Artificial Intelligence
DECISION MANAGEMENT
Confidential and Proprietary3
IMPORTANCE OF OPERATIONAL DECISION
MANAGEMENT
Low High
LowHigh
Strategic
Decisions
e.g. New
markets, M&A
Tactical Decisions
e.g. New
products, pricing, cu
stomer
segmentation
Operational Decisions
e.g. Loan
approvals, insurance
application
approvals, customer
upgrades, cross-sell/up-
sell, marketing offers
Decision Volume
DecisionValue
Confidential and Proprietary4
Decision
Simulation
Decision
Optimi-
zation
Business
Intelligence
Business
Rules
Optimiz-
ation
Predictive
models
DECISION MANAGEMENT CYCLE
Insights into
Improvement
Operational Decision
Data
Business Data
Operational Strategic
Confidential and Proprietary5
AN ARCHITECTURE FOR DECISION
MANAGEMENT
Data
warehouse
External
Data
Industry
Data
Analytic
Workbench
Models
Rules
Operational
Data stores
Rules
Management
Rules
Policy
Documents
Code
Data
Business
Experts
Adaptive Control
Business Decisions
Insights
Feedback Loop
Operational Systems
Channels – web, mobile, contact center etc.
Decision
Service
Analytic process Decision Modeling
Confidential and Proprietary6
COMPONENTS OF A DECISION ENGINE
Designer
Configuration
center
Repository
Deployment Container
rules rules rules rules
Decision
Service
Decision
Service
Decision
Service
Client applications
Design time
Run time
• Distinct components targeted to
distinct roles
• Design time
− Define frameworks within which
operational decisions are managed
− Configure models and rules that make up
the decision
− E.g. setting up data models, rule
structures, invocation models etc.
• Run time
− Managed execution of business rules to
output decisions
− Consumed by client applications via
“Decision Services” Developers Business users
End users
System
Admins
Confidential and Proprietary7
• Clients - internal cloud or external cloud?
• Self service – all components need to be provisioned on a self service basis. Provide
flexibility to cherry pick from various available components.
• Multi-tenancy – for internal cloud, each team/domain can be a tenant within the
cloud decision management infrastructure. Each tenant is isolated and gets all the
services in the cloud based decisioning infrastructure.
• Web based rules & models management – Web based interface to manage
policies that lead up to the decision as well perform verification & validation.
• Managed APIs – Provide REST APIs to interact with both design time aspects
(repository, rule definitions, data models etc.) and run time (execute rules, rule
analytics etc.).
• Simulations – Invoke decisions against a sample set of input data to determine
impact and optimize decisions.
• Data Mining – Capture decisions for adaptive controls or corrections
DECISION ENGINE IN THE CLOUD -
CONSIDERATIONS
Confidential and Proprietary8
MULTI-TENANCY
PaaS
IaaS
Tenant1
Tenant2
Tenant3
• One instance of the
software system
serves one tenant.
• Tenant data fully
isolated and not
visible to each other.
• Configuration center
should have much
of the functionality to
enable self-service.
• No technical
development effort
is required.
• Rules can be
configured
immediately.
Designer
Automation
Interface
Configuration
center
Repository
Deployment Container
rules rules rules rules
Decision
Service
Decision
Service
Decision
Service
Client applications
Design time
Run time
Developers Business users
End users
System
Admins
Tenant4
Confidential and Proprietary9
Decision Server
INDIVIDUAL TENANT ORGANIZATION
Rules
Repository
User &
Preferences
Store
Simulation
(In/out data)
Decision Management Portal
User
Management
Rules
Management
Simulation
Controller
Decision
Warehouse
Decision
Svc 1
Decision
Svc 2
Decision
Svc 3
Deployment Manager
Server Monitor
Rules
Source
Decision Server
Decision
Warehouse
Decision
Svc 1
Decision
Svc 2
Decision
Svc 3
Deployment Manager
Server Monitor
Rules
Source
deploy deploy
 Design data pattern
 Decision configuration pattern Decision server pattern
 Decision server data pattern
 Decision server pattern
 Decision server data pattern
StageLive Dev
JSON
JSON
JSON
JSON
Client applications
Model
Management
CEP
Service
Framework
Confidential and Proprietary10
• Each tenant should be configurable by adding parts
• Built with parts
− A database part (for user, preferences, rules, simulation data etc.)
− A simulation application part for running simulations on eligible decision services
− A rules maintenance part for managing decisions and creating new.
• Group parts into patterns
− A pattern for design time authoring. Some patterns may omit parts (for e.g.
simulation not required all the time)
− Another pattern for executing decisions (runtime).
• Group patterns into virtual systems deployed in virtual environments
− The design time data pattern and app pattern assembled together to form a virtual
system for decision maintenance.
INDIVIDUAL TENANT ORGANIZATION
Confidential and Proprietary11
Hadoop
DATA PROCESSING FOR DECISIONINGData
CacheEvent Data
Rollup
Offline
Variables
Clients
• Transparently merges
real time event data
with offline data
• Combined data blends
the reliability of offline
with the low latency of
online data
• Heavy calculations and
large rollups are all
done offline.
• All data stored in highly
available cache for fast
access
Data
Warehouse Data
Events
DS DS DS
CEP
Filter
Aggreg
ate
Data
Window
Pattern
Join
Variables
PaaS
Confidential and Proprietary12
DECISION SERVICE DEVELOPMENT
WORKFLOW
Development workflow
CloudliveCloudstaging
Analysis&
Design
Cloud
environment
Select pattern and
provision
Is data model
available?
Design a data
model
Import data model
into environment
Create new
decision service
using the data
model
no
yes
Configure
decisions & test
Test REST end
point from
application
Ready to
deploy
no
yes
Ready to
deploy
no
Deploy decision
service
yes
Deploy decision
service
Design a decision
model, identify
decision points
All environment settings
are preconfigured in the
pattern.
Development process
starts here early!
One click deploy
process reduce
admin overhead
Operationalize strategies,
models and business rules
quickly and scale them to meet
market demands.
13 Confidential and Proprietary
WE ARE HIRING
If you are interested in helping us solve
these problems, you can contact us at:
dwilfred@paypal.com
http://www.ebaycareers.com

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PayPal Decision Management Architecture

  • 1. June 2013 Risk & Compliance Engineering, PayPal Pradeep Ballal Staale Nerboe Greg Berry This deck contains generic architecture information, and does not reflect the exact details of current or planned systems. Decisions as a Service
  • 2. Confidential and Proprietary2 • Encompasses processes to improve, streamline and automate operational decision making within organizations. • Use all available organizational resources to increase precision, consistency and agility of decisions. • Treat decisions as reusable assets and leverage technology at key decision points to automate the process. • Uses tools such as Predictive Analytics Business Intelligence Business Rules Adaptive Control Artificial Intelligence DECISION MANAGEMENT
  • 3. Confidential and Proprietary3 IMPORTANCE OF OPERATIONAL DECISION MANAGEMENT Low High LowHigh Strategic Decisions e.g. New markets, M&A Tactical Decisions e.g. New products, pricing, cu stomer segmentation Operational Decisions e.g. Loan approvals, insurance application approvals, customer upgrades, cross-sell/up- sell, marketing offers Decision Volume DecisionValue
  • 4. Confidential and Proprietary4 Decision Simulation Decision Optimi- zation Business Intelligence Business Rules Optimiz- ation Predictive models DECISION MANAGEMENT CYCLE Insights into Improvement Operational Decision Data Business Data Operational Strategic
  • 5. Confidential and Proprietary5 AN ARCHITECTURE FOR DECISION MANAGEMENT Data warehouse External Data Industry Data Analytic Workbench Models Rules Operational Data stores Rules Management Rules Policy Documents Code Data Business Experts Adaptive Control Business Decisions Insights Feedback Loop Operational Systems Channels – web, mobile, contact center etc. Decision Service Analytic process Decision Modeling
  • 6. Confidential and Proprietary6 COMPONENTS OF A DECISION ENGINE Designer Configuration center Repository Deployment Container rules rules rules rules Decision Service Decision Service Decision Service Client applications Design time Run time • Distinct components targeted to distinct roles • Design time − Define frameworks within which operational decisions are managed − Configure models and rules that make up the decision − E.g. setting up data models, rule structures, invocation models etc. • Run time − Managed execution of business rules to output decisions − Consumed by client applications via “Decision Services” Developers Business users End users System Admins
  • 7. Confidential and Proprietary7 • Clients - internal cloud or external cloud? • Self service – all components need to be provisioned on a self service basis. Provide flexibility to cherry pick from various available components. • Multi-tenancy – for internal cloud, each team/domain can be a tenant within the cloud decision management infrastructure. Each tenant is isolated and gets all the services in the cloud based decisioning infrastructure. • Web based rules & models management – Web based interface to manage policies that lead up to the decision as well perform verification & validation. • Managed APIs – Provide REST APIs to interact with both design time aspects (repository, rule definitions, data models etc.) and run time (execute rules, rule analytics etc.). • Simulations – Invoke decisions against a sample set of input data to determine impact and optimize decisions. • Data Mining – Capture decisions for adaptive controls or corrections DECISION ENGINE IN THE CLOUD - CONSIDERATIONS
  • 8. Confidential and Proprietary8 MULTI-TENANCY PaaS IaaS Tenant1 Tenant2 Tenant3 • One instance of the software system serves one tenant. • Tenant data fully isolated and not visible to each other. • Configuration center should have much of the functionality to enable self-service. • No technical development effort is required. • Rules can be configured immediately. Designer Automation Interface Configuration center Repository Deployment Container rules rules rules rules Decision Service Decision Service Decision Service Client applications Design time Run time Developers Business users End users System Admins Tenant4
  • 9. Confidential and Proprietary9 Decision Server INDIVIDUAL TENANT ORGANIZATION Rules Repository User & Preferences Store Simulation (In/out data) Decision Management Portal User Management Rules Management Simulation Controller Decision Warehouse Decision Svc 1 Decision Svc 2 Decision Svc 3 Deployment Manager Server Monitor Rules Source Decision Server Decision Warehouse Decision Svc 1 Decision Svc 2 Decision Svc 3 Deployment Manager Server Monitor Rules Source deploy deploy  Design data pattern  Decision configuration pattern Decision server pattern  Decision server data pattern  Decision server pattern  Decision server data pattern StageLive Dev JSON JSON JSON JSON Client applications Model Management CEP Service Framework
  • 10. Confidential and Proprietary10 • Each tenant should be configurable by adding parts • Built with parts − A database part (for user, preferences, rules, simulation data etc.) − A simulation application part for running simulations on eligible decision services − A rules maintenance part for managing decisions and creating new. • Group parts into patterns − A pattern for design time authoring. Some patterns may omit parts (for e.g. simulation not required all the time) − Another pattern for executing decisions (runtime). • Group patterns into virtual systems deployed in virtual environments − The design time data pattern and app pattern assembled together to form a virtual system for decision maintenance. INDIVIDUAL TENANT ORGANIZATION
  • 11. Confidential and Proprietary11 Hadoop DATA PROCESSING FOR DECISIONINGData CacheEvent Data Rollup Offline Variables Clients • Transparently merges real time event data with offline data • Combined data blends the reliability of offline with the low latency of online data • Heavy calculations and large rollups are all done offline. • All data stored in highly available cache for fast access Data Warehouse Data Events DS DS DS CEP Filter Aggreg ate Data Window Pattern Join Variables PaaS
  • 12. Confidential and Proprietary12 DECISION SERVICE DEVELOPMENT WORKFLOW Development workflow CloudliveCloudstaging Analysis& Design Cloud environment Select pattern and provision Is data model available? Design a data model Import data model into environment Create new decision service using the data model no yes Configure decisions & test Test REST end point from application Ready to deploy no yes Ready to deploy no Deploy decision service yes Deploy decision service Design a decision model, identify decision points All environment settings are preconfigured in the pattern. Development process starts here early! One click deploy process reduce admin overhead Operationalize strategies, models and business rules quickly and scale them to meet market demands.
  • 13. 13 Confidential and Proprietary WE ARE HIRING If you are interested in helping us solve these problems, you can contact us at: dwilfred@paypal.com http://www.ebaycareers.com

Editor's Notes

  1. Mr. Pradeep Ballal works as a Senior Architect in the Core Service Product Development with specific focus on Compliance and Risk products with PayPal Singapore. Mr. Ballal is a software generalist with 13 years of technology experience and has special interest in decision management, business rules, enterprise software and architectures.Mr. Staale Nerboe (snerboe@paypal.com) works as a Senior Architect in the Core Service Product Development organization withPayPal Singapore. Mr. Nerboe has 15+ years of Technology Consulting and Software Architecture experience for large global companies world-wide.Mr. Greg Berry (gberry@paypal.com) works as a Principal Architect at PayPal in the Core Services organization. Greg has been an architect in the payments industry for more than 15 years.
  2. A pattern for organizing design time database parts A pattern for organizing decision configuration parts A pattern for organizing decision runtime parts A pattern for organizing decision runtime data parts