predictive analytics innovation summit

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Confidential | Copyright © Fractal Analytics 2012 1

Art

Science

The world of payments and business intelligenceA peek into the future

Sankar Narayanan, Fractal AnalyticsDirector – Client Servicing

Kamran Ashraf, Visa EuropeHead of Analytics and Information Services

Predictive Analytics Innovation SummitLondon, 18 April 2012

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An awareness test


®Hypotheses are great, but remember you seldom see what you are not looking for!


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The world of payments and business intelligence


1. Predictive and accessible analytics

2. Sub-optimal models - Type

‘0’ and ‘A’

3. Critical success factors - T3 scorecard

4. Mobile and

convergence

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1. What good is data if we don’t use it!A leading online grocery retailer, Competing on Analytics


1. The classic NYC traffic problem 2. The case of the broken egg

®1. Police department benefits from real-time and accessible analytics solutions


Key wins for the Police department: real-time updated models and accessibility everywhere from police captain’s PC to the patrol cop’s car monitor

Support real-time patrolling decisions (suspicious activity)

Manage overtime & budgets in a resource constrained environment

Visual map overlay analysis to ensure quick reallocation

Applications

“Real time visualization, predictive analytics and geospatial analysis provide answers.” – Lt. Dale Peet, Michigan State PD

®2. Sub-optimal ‘Type 0’ and ‘Type A’ analytics engagement models


Digitisation of data, new data feedsDigitisation of data, new data feeds

Big data solutionsBig data solutions

Cutting edge modelsCutting edge models

Investment in pure science, no growth objectives

Investment in pure science, no growth objectives

Type AType A

Data governance, especially regulatoryData governance, especially regulatory

StrategicStrategic

Data warehouse consolidationData warehouse consolidationOperationalOperational

OptimisationOptimisation

Type 0Type 0‘0’ investment, no growth objectives‘0’ investment, no growth objectives

PlansPlansObjectivesObjectives

Longer lifecyclesLonger lifecycles

®3. Critical success factors (CSFs) in the BI/IT domain – T3 scorecard


…ever closer collaboration

Talent

Tangible

Trust



Talent

Tangible

Trust

®3. Critical success factors (CSFs) in the Business domain


Move from product to customer view – value, behaviours, triggers and touch points

‘Must-have’ requirements which

WILL be applied to business problems

1. Leadership

2. Business application

3. Ownership

Vision, prototyping

ROI themes and ‘test & learn’

Metrics, KPIs = Data dictionary, quality

1Product

Product

Form

Form

TransactionTransaction

ChannelChannel

32

Usage – petrol offer in

cents or %

Activation – restaurant offer +50%

Test & learnThemes

Dormancy – holiday towel

offer +15%

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4. Mobile as an engine for growth


Technology convergence and rise of mobile paymentsTechnology convergence and rise of mobile payments

Within ten years:

50 billion devices will be connected to the Web

Payments initiated by mobile will outnumber transactions on plastic cards

38 years 13 years 4 years 3 years

It took….It took….

….to reach 50m users….to reach 50m users2 years 2 years 1 year

Telephone Television Internet iPod iPhone Facebook Android

Avoid extinction…Avoid extinction…

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4. Impact on the payments landscape


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In summary & thank you for listening!



2. Sub-optimal models - Type ‘0’ and ‘A’

3. Critical success factors – T3

scorecard

4. Future (of payments) is mobile and managing convergence is key


2. Sub-optimal models - Type ‘0’ and ‘A’

3. Critical success factors – T3

scorecard

4. Future (of payments) is mobile and managing convergence is key

Art

Science

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In case you didn’t know…


®Fractal’s clients achieve competitive advantage by institutionalising analytics


®Fractal’s clients achieve competitive advantage by institutionalising analytics


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predictive analytics innovation summit

Technology

visa europehead of analytics

critical success factors

mobile payments

suboptimal type

years2 years2 years

data dictionary

digitisation of data

years13 years