How Retail Banks Use MongoDB.

1. How Retail Banks use MongoDB
Kunal Taneja
Business Architect, Financial Services
kunal.taneja@mongodb.com

2. 2
• About MongoDB
– The Company
– The Database (MongoDB)
• Challenges in Financial Services
• Case Study – Single View of Customer
Agenda

3. 3
MongoDB
NoSQL database
Document
Data Model
Open-
Source
General
Purpose
{
name: “John Smith”,
date: “2013-08-01”,
address: “10 3rd
St.”,
phone: {
home: 1234567890,
mobile: 1234568138 }
}

4. 4
MongoDB Overview
400+ employees 900+ customers
Over $231 million in funding
(More than other NoSQL vendors combined)
Offices in NY & Palo Alto and
across EMEA, and APAC

5. 5
Leading Organizations Rely on MongoDB

6. 6
• About MongoDB
– The Company
– The Database (MongoDB)
• The Community
• MongoDB in Financial Services
• Case Study – MongoDB as a Tick Store
Agenda

7. 7
MongoDB.
NoSQL Document based database.
Designed to build todays applications.
•Fast to build.
•Quick to adapt.
•Easy to scale
•Lessons learned from 40 years of RDBMS.

8. 8
Relational Model
PlanID BenFK Plan
100 1 PPO Plus
200 2 Standard
EmpID Name Dept Title Manage Payband
9950 Dunham,
Justin
500 1500 6531 C
EmpBenPlanID EmpFK PlanFK
1 9950 100
2 9950 200
BenID Benefit
1 Health
2 Dental
DeptID Department
500 Marketing
TitleID Title
1500 Product Manager

9. 9
Document Model
EmpID Name Dept Title Manage Payband Benefits
9950 Dunham,
Justin
Marketing Product
Manager
6531 C
EmpBenPlanID EmpFK PlanFK
1 9950 100
2 9950 200
Health PPO Plus
Dental Standard
PlanID BenFK Plan
100 Health PPO Plus
200 Dental Standard

10. 10
Document Model
EmpID Name Dept Title Manage Payband Benefits
9950 Dunham,
Justin
Marketing Product
Manager
6531 C Health PPO Plus
Dental Standard

11. 11
MongoDB - Agility
Dynamic Schemas
V 1.0 V 1.1 V 2.0
EmpID Name Dept Title Manager Payband Benefits
9950 Dunham,
Justin
Marketing Product
Manager
6531 C
EmpID Name Title Payband Bonus
9952 Joe White CEO E 20,000
EmpID Name Dept Title Manager Payband Shares
9531 Nearey,
Graham
Marketing Director 9952 D 5000
Health PPO Plus
Dental Standard

12. 12
Shell
Command-line shell for
interacting directly with
database
MongoDB - Usability
Drivers
Drivers for most popular
programming languages and
frameworks
> db.collection.insert({product:“MongoDB”,
type:“Document Database”})
>
> db.collection.findOne()
{
“_id” : ObjectId(“5106c1c2fc629bfe52792e86”),
“product” : “MongoDB”
“type” : “Document Database”
}
Java
Python
Perl
Ruby
Haskell
JavaScript

13. 13
“No SQL”, But Fully Featured
MongoDB
{ customer_id : 1,
first_name : "Mark",
last_name : "Smith",
city : "San Francisco",
accounts : [ {
account_number : 13,
branch_ID : 200,
account_type : "Checking"
},
{ account_number : 14,
branch_ID : 200,
account_type : "Savings"
} ]
}
Rich Queries
• Find all Mark’s accounts
• Find everybody who opened an account
last month
Geospatial
• Find all customers that live within 10
miles of NYC
Text Search
• Find all tweets that mention the bank
within the last 2 days
Aggregation
• What’s the average value of Mark’s
accounts
Map Reduce
• How many customers that have a
checking account also have an IRA

14. 14
MongoDB - Scalability
• High Availability
• Auto Sharding
• Enterprise Monitoring
• Grid file storage

15. 15
• About MongoDB
– The Company
– The Database (MongoDB)
• Challenges in Financial Services
• Case Study – Single View of Customer
Agenda

16. 16
FS/Banking Challenges
1. Changing Regulatory Requirements
2012 2013 2014 2015 2016 2017 2018 2019
ICB Ring-fencing
ICB Loss
Absorbency
Leverage
Ratio -
Basel III
NSFR –
Basel III
MiFID II
T2S
LCR –
Basel III
ICB /
Competition
Audit
Policy
Cross
Border Debt
Recovery
Financial
Transaction
Tax
Market
Abuse
Directive
(MAD II)
PRIP
Accounting
Directive
Review
AIFM
Directive
EU
Transparency
Directive
EU Reg on
Credit
Rating
Agencies
CRDV
Internal
Governance
GuidelinesFATCA
PD
EMIR
SWAPS Push
Out – Dodd
Frank
Securities
Law
Directive
(SLD)
Volker Rule –
Dodd Frank
Short
Selling
Close Out
Netting
Crisis
Management
Recovery &
Resolution

17. 17
Source LayerSource Layer BI Abstraction &
Reporting Layer
BI Abstraction &
Reporting Layer
Acquisition LayerAcquisition Layer
Extraction &
Staging
Cleansing
Atomic LayerAtomic Layer
MDM
Ad-hoc reports &
Analytics
Dashboards &
Web Reports
Web Services
Corporate Data WarehouseCorporate Data Warehouse
Data Lineage and Metadata
ETL
Transformation & Access
Layer
Transformation & Access
Layer
Transformation
& Calculation
Performance &
Access
Change Data
!
Reject Data
Normalisation
& Storage
FS/Banking Challenges
1. Changing Regulatory Requirements

18. 18
Primary:NYC
Secondary:NYC
Primary:LON
Primary:SYD
Secondary:LON
Secondary:NYC
Secondary:SYD
Secondary:LON
Secondary:SYD
FS/Banking Challenges
2. Latency and Global synchronisation of information

19. 19
FS/Banking Challenges
2. Latency and Global synchronisation of information
Source LayerSource Layer BI Abstraction &
Reporting Layer
BI Abstraction &
Reporting Layer
Acquisition LayerAcquisition Layer
Extraction &
Staging
Cleansing
Atomic LayerAtomic Layer
Ad-hoc reports &
Analytics
Dashboards &
Web Reports
Web Services
Corporate Data WarehouseCorporate Data Warehouse
Data Lineage and Metadata
ETL
Transformation & Access
Layer
Transformation & Access
Layer
Transformation
& Calculation
Performance &
Access
Change Data
!
Reject Data
Normalisation
& Storage
HK
London
New York
4pm EST4pm EST
4pm GMT4pm GMT
4pm UTC4pm UTC
Actual Risk
24 hours late
Actual Risk
24 hours late
Wait &
sync
Wait &
Sync
Wait &
Sync

20. 20
Web
Call
Center
Customers
Impact
•Similar processes and
systems duplicated
•Changes done in
multiple places
•Siloed view of
customer
•Siloed experience by
customer
•Cross-channel/silo
data is previous day
Central
Functions
•Risk
•Compliance
•Legal
•…
Loans Cards
Deposit
Accounts
…
Mobile
Com
puter
Call
Center
Mobile
ATM
Branch
EO
D
EO
D
EO
D
EO
D
Branch
Com
puter
Call
Center
…
FS/Banking Challenges
3. Multi-channel and 360 View of Customer

21. 21
Source LayerSource Layer BI Abstraction &
Reporting Layer
BI Abstraction &
Reporting Layer
Acquisition LayerAcquisition Layer
Extraction &
Staging
Cleansing
Atomic LayerAtomic Layer
MDM
Ad-hoc reports &
Analytics
Dashboards &
Web Reports
Web Services
Corporate Data WarehouseCorporate Data Warehouse
Data Lineage and Metadata
ETL
Transformation & Access
Layer
Transformation & Access
Layer
Transformation
& Calculation
Performance &
Access
Change Data
!
Reject Data
Normalisation
& Storage
FS/Banking Challenges
3. Multi-channel and 360 View of Customer
LoansLoans
Credit CardCredit Card
PaymentsPayments
Loans meets Card
Card meets Payments
….
Loans meets Card
Card meets Payments
….

22. 22
Approaches tried in the past
Siloed Data Marts
Source
Layer
Source
Layer
BI Abstraction &
Reporting Layer
BI Abstraction &
Reporting Layer
Acquisition LayerAcquisition Layer
Extraction &
Staging
Cleansing
Atomic LayerAtomic Layer
Ad-hoc reports &
Analytics
Dashboards &
Web Reports
Web Services
Corporate Data WarehouseCorporate Data Warehouse
Data Lineage and Metadata
ETL
Transformation & Access
Layer
Transformation & Access
Layer
Transformation
& Calculation
Performance &
Access
Change Data
!
Reject Data
Normalisation
& Storage

23. 23
Polymorphic Operational Data Store
Source
Layer
Source
Layer
BI Abstraction &
Reporting Layer
BI Abstraction &
Reporting Layer
Acquisition LayerAcquisition Layer
Extraction &
Staging
Cleansing
Atomic LayerAtomic Layer
Ad-hoc reports &
Analytics
Dashboards &
Web Reports
Web Services
Corporate Data WarehouseCorporate Data Warehouse
Data Lineage and Metadata
ETL
Transformation & Access
Layer
Transformation & Access
Layer
Transformation
& Calculation
Performance &
Access
Change Data
!
Reject Data
Normalisation
& Storage

24. 24
Where MongoDB is being used
Business Domain Solution Areas to Consider
Customer Engagement Single View of a Customer
Customer Experience Management
Responsive Digital Banking
Gamification of Consumer Applications
Agile Next-generation Digital/Social/Mobile Platform
Marketing Multi-channel Customer Activity Capture
Real-time Cross-channel Next Best Offer
Location-based Offers
Risk Analysis & Reporting Firm-wide Liquidity Risk Analysis
Transaction Reporting and Analysis
Regulatory Compliance Flexible Cross-silo Reporting:
- Basel III, Dodd-Frank, etc.
Online Long-term Audit Trail
Aggregate Know Your Customer (KYC) Repository
Reference Data Management [Global] Reference Data Distribution Hub
Payments Corporate Transaction Reporting
Fraud Detection Anti-Money Laundering

25. 25
• About MongoDB
– The Company
– The Database (MongoDB)
• Challenges in Financial Services
• Case Study – Single View of Customer
Agenda

26. Retail Banking
How MongoDB and Infusion are helping Banks in the
Digital era
Andy Ross (Infusion) and Kunal Taneja (MongoDB)
5 August 2014

27. Overview of
InfusionWe help leading companies navigate the digital era

28. With over 600
employees worldwide
and 15 years of
success and growth,
Infusion
is focused on
innovation as the way
for business to flourish.
Infusion helps leading
companies navigate
the digital era.
A bit about us

29. How we help clients
Data &
Analytics
Mobilit
y
Digitalized
Customer
Experience
Web
Digital
Strateg
y
Innovation
Design Agency
Enterprise software development
Managed services

30. A history of success with the largest
customers

31. Trends in Retail Banking
Drivers and themes

32. Drivers of change
Regulation
Customer v product
focus
Return of the branch
New entrants
New technology

33. Digital themes
Mobility
Deliver
faster and
for less
Personalis
ation
Big data
Customer
experience
The challenge: how does a big company act
like a start-up?

34. The MetLife story

35. One day we got an email from our friend
Gary…
New MetLife CIO with a (30/60/90) plan
Get a slow moving company to move fast
Attract talented technologists
Solve long-standing and difficult business problems
Business context

36. One day we got an email from our friend
Gary…
Asked if we could build an application that
would produce a 360° view of his new customers
using innovative technology
and have a Facebook style interface?
Business challenge
70
different systems
140yrs
customer data
45million
policies
100million
transactions

37. Our approach: GO FAST!
9
0
days
2
weeks
Sold the idea
Delivered the application

38. Our approach: act like a start-up
Get software built and optimize

39. The Wall unmasked
User-centric
design

40. Dramatic productivity enhancements

41. Gone viral
Changing how they “do projects”
Is something the organization can, and is, rallying
around and aligning to
The Wall lives
Additional benefits

42. Why were we successful?
Strong champion
Modern
technology
Enterprise ready
Incubation
Behaved like a start-
up

43. You can do things differently!
You can
push harder
than you
think
You need a
strong
champion
Sell the idea
Lessons learned

44. Questions?
Stay tuned after the webinar and take our
survey for your chance to win MongoDB
swag.