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TRANSCRIPT
© Created by Diagon Consulting Ltd. – 2019 October
LEVERAGING DATA: MARKET
INTELLIGENCE AND THE CHALLENGE
OF CYBER THREAT
2PRIVATE & CONFIDENTIAL
PRESENTATION
AGENDA
The Great Hack
Data defined and the current view of
market intelligence
Where we are as a region?
Future view of data with two way
communication and immediate market
intel
Importance of security
01
02
04
05
03
06 It is all interconnected.
3PRIVATE & CONFIDENTIAL 3PRIVATE & CONFIDENTIAL
THE GREAT HACK
4PRIVATE & CONFIDENTIALPRIVATE & CONFIDENTIAL
►Data - Meaningless facts that when applied to a situation and context produces information
► Information – When correctly grouped, harmonized, synthesized and assimilated produces intelligence
WHAT IS DATA
GOLD < DATA > OIL
5PRIVATE & CONFIDENTIALPRIVATE & CONFIDENTIAL
Predictive analysis
analyst
Business Intelligence
prescrip
tive analysis
exploratory analysis
Machine learning
Descrip
tive
analytics
Data management
Data quality
Advanced analytics
Extraction Transformation Load
dashboard
Data lakes
datamarts
Data warehouses
visualisation
information
governance
aggregation
Multi-
dimentional
dat
abas
e
Real-time
Big d
ata
insight
KPI
regression
Decision trees
Neural network
Test data
Business performance
management
Master data management
Data store
Scenario building
Decision making
Data security
Adhoc reporitng
Power users
What will happen?
Why did it happen?
What can we do?Enterprise wide
THE PLETHORA OF TERMS
6PRIVATE & CONFIDENTIAL
VISUALISATIONS
ADVANCED ANALYTICS
TRANSACTION SYSTEMS
DATA CAPTURE TRANSFORM & STORE DELIVER
SIMPLISTIC DATA CYCLE – CURRENT STATE
Segments Channels
Mass(Natural)
Mass Affluent
Affluent
High End
MassBusiness
Small Business
Enterprises
Corporations
Contact Center
Internet Banking
Branches
Face to FaceSpecialized
IVR
ATM
Moble Banking
RELATIONAL DB AND DATA STORES
Market insight is limited to traditional data capture via channels
7PRIVATE & CONFIDENTIAL
Cross sell ratio
Customer retention rate
Customer segmentation/ profiling
Customer churn prediction
Customer insights
Product mix determination
Customer profitability measure
Marketing cost and marketing campaign effectiveness analysis
Sales channel effectiveness
Credit analysis
Visualisation
Exploratory analyticsAdvanced Analytics incl
machine learning
Data warehuses/ Data marts
DELIVER: MARKET INTELLIGENCE THROUGH ANALYTICS
Prescriptive
Descriptive/Exploratory
Predictive
KEY
DescriptiveDiagnostic PredictivePrescriptive
8PRIVATE & CONFIDENTIAL
Forward looking/ structured data/ enterprise wide
Backwards looking/structured data/
inter-divisionBackwards looking/ structured data/ divisional focus
Val
ue
Forward looking/ structured and non-
structured data/ enterprise wide
Complexity
10 %
Very few organizations have the infrastructure to support and use analytics effectively
WHERE WE ARE AS A REGION
9PRIVATE & CONFIDENTIAL
WHY ARE WE HERE?
ABSENCE OF THE RIGHT AND QTY OF DATA
INSUFFICIENT DATA ARCHITECTURES
Big Data?The "single versionof the truth"
10PRIVATE & CONFIDENTIAL
ADMIN
COMPANY A.com
TeleMar
MMB
Data SourceFunction
Cust Prof
Wel Ltr
Cust Hier
Up/XSell
Self Svc Performance
Management
Including KPI
Calculation
Customer
Segmentation
Management
Reporting
Product Mix Decisions and
Product Profitability Index
Calculation
Dashboard
UNTIDY DRAWER ARCHITECTURE
11PRIVATE & CONFIDENTIAL
MDM
ADMIN
COMPANY A.com
TeleMar
MMB
Data SourceFunction
Cust Prof
Welc Ltr
Cust Hier
Up/XSell
Self Svc
TIDY DRAWER ARCHITECTURE
Datamart
Datamart
12PRIVATE & CONFIDENTIAL
PREDICTING THE PROBABILITY OF MY SON PASSING
AGE X + STUDY TIME Y + IQ SCORE Z + PAST SCORES R
HOWEVER – WE DON’T HAVE DATA ON THE FOLLOWING:- Exam difficulty- Sleep before an exam- Productive study time%- Who he sat next to this term
13PRIVATE & CONFIDENTIAL
PUTTING IT TOGETHER
14PRIVATE & CONFIDENTIAL
VISUALISATIONS
ADVANCED ANALYTICS
TRANSACTION SYSTEMS
DATA CAPTURE TRANSFORM & STORE DELIVER
Segments Channels
Mass(Natural)
Mass Affluent
Affluent
High End
MassBusiness
Small Business
Enterprises
Corporations
Contact Center
Internet Banking
Branches
Face to Face Ppecialized
IVR
ATM
Moble Banking RELATIONAL DB AND DATA STORES
New channels, two way information exchange
FUTUREPROOFED DATA CAPTURE
BLOCKCHAIN
Other Bank’scustomers
API
Chatbots
PISp/ AISp
`
15PRIVATE & CONFIDENTIAL
INTERNET OF
THINGS
TWO WAY COMMUNICATION - RICHER INFO
APIS
CHATBOTS
ROBOADVISORS
16PRIVATE & CONFIDENTIAL
Bank Bank
Users Users
Internal API Public API
Third PartyApps
Proprietary Apps
Proprietary Apps
01GREATER
CUSTOMER
BASE
023RD PARTY
ACCESS TO
CUSTOMERS
OPEN API – ACCESS TO BANK’S DATA
17PRIVATE & CONFIDENTIAL
REGULATORS MOBILE ADOPTION
CUSTOMERS
DRIVERS FOR CHANGE
73% Mobile subscribers : total
population
in the Caribbean
MILLENNIALSBorn 1981-1998
Target group for most banks
GEN ZBorn 1998 to present
Greater than the Gen x but less than
Millennials
Truly mobile generation
18PRIVATE & CONFIDENTIAL
“TRADITIONAL BANKS KNOW THAT TO COMPETE, THEY MUST DEVELOP DIGITAL CAPABILITIES TO AVOID BEING DIS-INTERMEDIATED COMPLETELY BY NEW ENTRANTS WITH SUPERIOR, MORE AGILE OFFERINGS.”
“OPEN BANKING IS ABOUT MAKING EVERYTHING FOR SALE. IT PROVIDES A NEW WAY TO INCREASE DIGITAL REVENUE FOR THE BANKS THAT ARE WILLING TO THINK DIFFERENTLY...OPEN BANKS AND FINTECHS WILL CONTINUE TO ERODE MARGINS AND CUSTOMER RELATIONSHIPS FOR THOSE BANKS THAT DON’T.”
“IMAGINE A SIMPLE APPLICATION THAT WILL FIND THE CLOSEST ATM TO YOU. THE APPLICATION WILL SEND A REQUEST TO ALL FINANCIAL INSTITUTIONS USING THEIR OPEN API “
INTERESTING QUOTES
19PRIVATE & CONFIDENTIAL
2 MOST VALUABLE FORMS OF DATA
FINANCIAL DATA MEDICAL RECORDS DATA
HIPPAPCI
20PRIVATE & CONFIDENTIAL
BAD SECURITY PRACTICES RESULT IN….
• Litigation
• Brand and reputation damage
• Loss of customer and confidence
• Loss of market value
• Regulatory action
• Financial loss
• Lack of user awareness: Overuse of company credentials
• Poor application security: Easily accessible client data
• Defense in depth vs Detection and response strategies
Results in:
21PRIVATE & CONFIDENTIAL
DATA LEAKAGE – GOES UNDETECTED
22PRIVATE & CONFIDENTIAL 22PRIVATE & CONFIDENTIAL
WHERE IT ALL BEGINS – USERS ARE THE WEAK LINK MOST TIMES
23PRIVATE & CONFIDENTIAL
1. Your Asset and Network Terrain
2. Threats Targeting Your Environment
3. Valuable Data and Where it Resides
4. Adversaries’ Actions and their TTPs
5. How to Alter the Terrain to Your Advantage
Know Your Environment
Determine most likely paths of:• Exfiltration• C&C• Surveillance• Etc.
IN ORDER TO PROTECT DATA– YOU MUST UNDERSTAND……
24PRIVATE & CONFIDENTIAL
Dwell Time = The time that a threat actor goes undetected on your network before they are found
and contained.
The 2018 Ponemon Breach Study indicated the following:
“The faster a data breach can be identified and contained, the lower the costs. The Average Time to identify a threat is 197 days andto contain it is 97 days.
On average companies that identify a breach in less than 100 days can save more than amillion dollars.”
REDUCING DWELL TIME
25PRIVATE & CONFIDENTIAL 25PRIVATE & CONFIDENTIAL
SIMULATED ATTACK UNFOLDING
26PRIVATE & CONFIDENTIAL
WHAT’S NEXT FOR CARIBBEAN BANKS
REDEFINE
ARCHITECTURE
New channels, new data
structures, two-way and
immediate
START WITH SIMPLE
VISUALISATON
02
03
01
04
REMAIN RELEVANT
Strategic decisions need to be
made re digital strategy
listening to the market and the
direction of the banking world
ROBUST SUPPORT
INFRASTRUCTUREI
Security etc.