the future of information - experian knows big data analytics

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What is the Future of Information?

2©2014 Experian Information Solutions, Inc. All rights reserved.Experian Public.

Big data and analytics

“Information is the oil of the 21st century, and analytics is the combustion engine”

- Peter SondergaardSenior Vice President

Gartner


It’s a whole new world

It’s a radical shift in how people and businesses interact

A 440% increase in digital media content over the next 10 years

Real-time, data-driven processes are the new standard

Solving client problems that were unsolvable before

Consumers expect a higher level of service in exchange for loyalty


Understanding, managing and analysing data is the core of our success

Trusted expert for delivering insight from large volumes and varieties of information

Balancing a business and science approach to help decision makers understand what matters most

Helping clients across 70 countries build meaningful customer relationships

30 years of global leadership


We have the people and tools: data, analytics, talent and experience; plus the global footprint

We help our clients transform their business through data science

DataLabs creating breakthroughs in data experimentation and innovation

Credit, fraud and marketing information unmatched for breadth, depth, and quality

Helping clients with the improvement of data and model risk management practices

Data is in our DNA


Experience-driven design

More than 2,800 technologists and over 400 data scientists worldwide, including Global DataLabs in 3 major markets

Applied research teams in advanced analytics, machine learning and computer science

Ensuring the best fit of data and analytics to optimize business performance

Bringing our analytic expertise to you


Answering the challenges of big data

Harnessing the power of data to better understand your customers and drive competitive advantage

Safeguarding and promoting the proper use of data in consumer strategies and decisions

Client confidence in decisions


Why Experian?


The data universe is growing

We’re constantly exploring new data Mobile network operator data

Linking social media to commercial credit

Transaction and payment data

Location data

Psychographic and economic data

Experian knows big data 19 credit information

and 13 business information bureaux

Credit data on 600 million consumers & 60 million businesses

Demographic data on 260+ million households

Online behaviour data for 25 million users across 5 million websites


… and expanding

Experian knows big data

4TB of raw Internet usage each day

Processing 45 billion small business records a year

Segmenting 2.3 billion consumers & 700 million households across 28 countries

7.8 billion vehicle records globally


Gradient-boosted decision trees Latent Dirichlet allocation Deep network and deep learning

Pattern extraction and model

development

Extracting patterns

Advanced analytics Descriptive

Gain insights with use of scorecards and reporting

PredictiveIdentify risks and potential from patterns in transactions

Prescriptive Improve decisions through simulation and optimisation


Extracting patterns

Income/wealth estimation

Social network analysis

Churn/attrition management

Consumer propensities

Customer journey

Digital audience

Attribution

analysis

Loss forecasting

Trended behaviours

Sequence mining

Risk exposure

Channel strategies

Targeted strategic insight

Financial services and banks

Telecommunications and utilities

Insurance

Healthcare

Retail

Travel

Leisure and media

Automotive

Public sector

Deployed across multiple markets


Putting analytics into action

We create client solutions using the very best analytical tools to build our models

We deploy algorithms and models into our client’s operational environment to deliver on big data needs for speed and agility

Our technology aptitudeMarketSwitchPowerCurve

HadoopHive

MALLETR

Python


Practical applications of big data and analytics


What can you tell about business performance through social media?

METHODOLOGY RESULTSOPPORTUNITY

“French toast is so good and the portions are pretty large"

Not all information is structured to give you simple insight. By pulling unstructured data such as online reviews, you can dive deeper into performance than looking at the star rating or number of likes.




Using Yelp! HTML, we parsed reviews through Natural Language Processing

Parsing reviews into sentences Parsing sentences into words and punctuation Part-of-speech tagging Phrase structure tree parsing Typed dependency




We were able to convert unstructured business reviews into modelling attributes and to identify main aspects of business

Aspect discovery Sentiment analysis – Do consumers feel good

about your product or services? Business performance – Are people purchasing

goods and services?


Can we improve analytics to increase the speed and accuracy of fraud detection?


Develop a product that makes use of all the analytical power available and can scale

Market demands faster response time Over 8TB of records to process 19 structured and semi-structured files Current technology focuses on batch processing No single commercial or open source tool offers

this functionality Maximise data usage Cost effective




Created new PreciseMatchSM platform from two open source platforms and custom components

Two Step Process► Created indexed repository shards

► Allowed loading of new search cluster

Fraud Big Data cluster► Built 32 physical hardware instances

► Two PreciseMatch core engines, 14 active-active search engines, 16 batch map-reduce engines




We are able to improve match rates and fraud scores allowing us to introduce smarter, real time fraud detection

Allowed for creation of 400 new results codes Absolute improvement of 25%+ fraud

detection rate High-confidence match improves 14% Medium-confidence match improves 17% Serves as base for new real-time search

platform Places product in competitive advantage


What insights can be gained from customer spend data?


Gain deep insights into customer preferences and behaviours through card transaction data

Opportunities► Increase share of wallet► Greater credit risk insight► Stimulate spend activity► Impact attrition and loyalty► More targeted product offers

Challenges► Massive amount of data► Continuously updated and changing► Incredible variance between customers




Applied new technologies and techniques to analyse card spending across multiple dimensions

New technologies► Parallel processing techniques to efficiently

process “Big Data”● Hadoop – Hive – Pig

New analytical techniques► New techniques to effectively interpret messy,

complex data● Latent Dirichlet Allocation / Topic Modelling● Collaborative filtering● Signal processing




A suite of transaction driven tools to encourage growth in customer relationships and stimulate spending

Lifestyle Segmentation► Machine driven segmentation based on spend patterns

to identify customer groups with “like” spending preferences

Merchant Offer Recommendations► Similarity Index allows for recommendations of similar

merchants ► Leverage recommendations by target, channel and

offer through customer or merchant

Customer Spend Alerts► Timely alerts on attrition risk allowing for intervention► Uniquely customised based on customers’ historical

spend behaviour


Can budget allocation across marketing channels be improved to achieve better results?


Rise above campaign measurements to see across all channels to reduce number of uneducated-guesses and ad hoc processes

Ability to measure lift of specific campaigns in email, direct mail, bill insert and messaging promotions

Data disintegration prevents sound decisions Lack of attribution solution and organisational

reluctance Transparency at the micro-level, but not across

macro-channel




Needed to create a hybrid of current best-practice solutions and custom analytics model

Technology► Based on Experian Marketing Services Response

Attribution Platform

Analytical Techniques► Proportionally allocate response across campaign

touches

► Measure all channels and correlate response volume

► Strength of correlation calculates pair-wise channel weights without individual level campaign data




Ability to move 13.5% in budget from one channel and redistribute gaining 220,000 new responses

Creating smarter marketing spending Now able to create what-if analysis against

channels Creating flexible platform, modelling portfolio

and process Enhancing media mix guidance Creating dashboard for daily results allowing for

real time budget adjustments


How can we improve customer engagement in a retail marketing campaign?


51M logged campaign events including transactions to give us greater insight into increasing smarter engagement

Measure positive/negative trends in engagement

Impact email click through Improve purchases of new product or increasing

value of existing product




Factor analysis with class clustering and hierarchical clustering

Technology► Alteryx, R and Tableau

Analytical Techniques► Dynamic segmentation (Frequency/trends/interest)

► Factor analysis

► Two-stage clustering




Developed ability to increase marketing pressure and improve campaign planning

Marketing content used to measure which campaign performs better

15% less email allows for a decrease in marketing frequency and increases smarter engagement

Increase revenue and click rate more than 27% Spam decreased more than 50%


Can you identify the key influencers in a group?


Identify the opinion leaders of health care to boost sales and awareness of pharmaceuticals

Ability to determine real influence rather than just popularity

Use professional and academic data to pinpoint individuals




Build a real network relationship around individual doctors

Technology: Gephi and SQL 14 unique data sources including building specific

bots to scrape web data Over 288M diverse data points Network analysis including

► Reputation both academic and professional

► Geographic area of influence

► Degrees of relationship




Able to identify and score influencers in a professional group

Scored individual doctors on ability to influence their peers

Able to measure the intensity of a relationship Ability to reach a specific target for research,

sales, thought leadership, recommendations


What insight can Experian help you draw from data?

What do you want the audience to do?

Let’s work together to help

your organisation unlock

big data to benefit both

your customers and your

bottom line.

Contact us at:

[email protected]

the future of information - experian knows big data analytics

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