Digitally Disrupted to Digital Disruptor

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1 Digitally Disrupted to Digital Disruptor Disrupt your enterprise (before someone else does...) Per Uno Österman Managing Director Analytics Nordics mobile

2 Digital is changing the world... Reviews and Word of Mouth are increasing their influence on consumer trust (3-5X more than TV/radio ads) 98% of consumers move between screens & devices to complete a task The wearable devices market will grow from $1.4 billion this year to $19 billion by 2018 Amazon.com and ebaytm are the only pure retailers on the list of the top 100 brands 4 of the 5 top global brands are digital at the core (Apple, Google TM, IBM and Microsoft ) 59% Mobile Internet Penetration in Sweden, 89% are searching for local information Sources: Accenture, Interbrand, Juniper Research, Google, Jack Morton 2 2 B2B Needs to Think Like B2C 2014 Acquity Group, All rights reserved. 2

3 It s all about the data and how to leverage it... 38,000+ photos shared 4,000,000+ searches on Google IN 3,100,000 likes on Facebook 277,000+ snapchats received 347,000+ tweets 100+ hours of video uploaded SECONDS 3,500+ pins $275,000+ transactions (USD) 2.4 billion people connected to the internet interact 3

4 Big Success with Big Data OVERWHELMING SATISFACTION Companies that have completed one or more big data projects are satisfied with the business outcomes 4

5 From the target clients interviewed by Accenture Analytics: 90% 89% 89% 76% Users are fully satisfied with their business outcomes Users believe big data is very important to their transformation into digital Users believe big data will revolutionize operations the same way the Internet did Users report that Big Data bring clear value to the organisation 5

6 HOW ORGANIZATIONS USE BIG DATA TODAY 65% identifying new revenue streams 57% analyzing customer behavior 54% attract and retain customers 6

7 FOUR KEY FINDINGS 7

8 KEY FINDING #1 Broad learning required Organizations are learning about the complexities of big data and how to address challenges 8

9 SECURITY, BUDGET, TALENT & INTEGRATION WITH EXISTING SYSTEMS ARE CHALLENGES 44% Security 40% Integration with existing systems 38% Budget 34% Talent to implement 9

10 KEY FINDING #2 Help needed Companies are finding ways to get help with big data, whether bringing in external resources for a project, hiring new talent or training their teams 10

11 MOST USED EXTERNAL HELP FOR IMPLEMENTATION AND PLAN TO HIRE 95% 55% used one or more sources of external help for big data installation plan to increase data science expertise within the next year 11

12 KEY FINDING #3 Company size makes a difference Larger companies are seeing better results by doing more with big data 12

13 Big data is seen as extremely important by more large companies More large companies report that big data completely met their needs 67% 58% LARGER COMPANIES 43% 32% SMALLER COMPANIES 13

14 KEY FINDING #4 Potential for disruptive transformation Organizations see big data as transforming the way business is done 14

15 THE TOP 3 IMPACTS IN THE NEXT FIVE YEARS BEING 63% Customer relationships 58% Redefining product development 56% Changing the way we organize operations 15

16 Big Success with Big Data Key Findings Overall satisfaction Companies that have completed one or more big data projects are satisfied with the business outcomes Broad learning required Organizations are learning the complexities of big data and how to address challenges including security, budget, lack of talent and integration with existing systems Help needed Companies are finding ways to get help with big data, whether bringing external resources for a project, hiring new talent or training their teams Company size makes a difference Larger companies are seeing better results by doing more with big data. Potential for disruptive transformation Organizations see big data as transforming the way business is done in the next five years. 16

17 GET THE MOST FROM BIG DATA Start small, scale fast test and learn be agile Launch business pilots with available data and use available cloud solutions Expand pilots with internal and external data sources In parallel develop a Digital value creation road map aligned with group strategy Develop Digital Factory / Big Data CoE capability on back of pilot streams Industrialize successful initiatives Build and expand real-time capabilities

18 Data visualizations example Now this is art! No?... Autodesk, Inc. Used with Permission. Source: Matejka, Justin. AutoDesk Research. (2012). The Organic Organization Chart (OrgOrgChart). Retrieved from

19 Big Data is changing the finance industry And this is what it allows us to do Real-time digital mortgage Seamless PFM with auto-categorization New Generation branch format User-centric service design mobile app Real-time and pre-approved credit Suggest products in the moment Predict when people churn before they do Monetize big data insights 19

20 A large Asian bank offers a fully digital mortgage in real-time with 1.5 days to get your money Real-Time Digital Mortgage Augmented Reality to understand property and neighbourhood $4.3bln e-mortgages in 2 years Up to 50% branch resources moved to virtual bank and personalized support Smartphone app Virtual branch Paperless mortgage 20

21 A European on-line Bank uses notifications and geofencing to serve their clients with right on time information Seamless PFM with auto-categorization drives the partner ecosystem Real time nearby offer notification Helps user select desired offer and find destination Real-time promotion effectivity metrics Direct mailing and paper reduction 21

22 Insurance Companies can Benefit from Evolving Technology and Big Data e.g. connected car is part of an eco-system were possibilities are endless Telematics will emerge through a car App, forcing insurers to underwrite and price based on behaviour and/or per km Demographics Stated Prefs. Driver Analytics Record (DAR) Products Facts Preferences Inferred Prefs. Lifetime Value Value Driving Behaviours Price Sensitivity Marketing Response Web Usage Mobile App Usage 22

23 Big Data is revolutionizing Underwriting, Risk Scoring and Cap Market predictions as it exposes all the causal and correlation patterns 23

24 Everyday Financial Shop Everyday Banks position themselves at the centre of Ecosystems in order to stay relevant for the Digital Consumer by capturing the ZMOT My Home Ecosystem partners My Consumption My Savings & Pension My Health My Money ATM Customer Agent My Education My Transportation My Protection My Communication My Car FS player providing FS services via API (e.g. financing) Ecosystem partners providing non-fs to be bundled in FS offering (e.g. real-time discounts) My Travel 24

25 Soon the standard will be one click Real-Time and Pre-Approved Credit Straight-through credit scoring combining classic credit scoring and customer behavioral data Loan Approval + 20% performance lift over existing model % automated decisions % approvals at constant portfolio loss rates Loan Sourcing campaign-driven sales +42% Personalized firm offer of credit Loan Funding Fulfillment ratios % Enabling customers to customize loan Streamlined offer generation enhancing UX Manual Underwriting Optimized routing Estimated 15% drop in Loan Processing Time Statefarm, Garanti, mbank Accenture references 25

26 Clients advisors view on Uno today Uno Transactional History Uno Österman Savings Goals Savings, Loans, Investments Copyright 2014 Accenture All rights reserved. 26

27 Clients advisors view on Uno tomorrow today Uno Lifestyle Savings, Loans, Investments Uno Österman Social Network Savings Goals Transactional History Life stage goals Value Channel preferences Copyright 2014 Accenture All rights reserved. 27

28 What we have covered today Big Data Research o Companies that have completed one or more big data projects are satisfied with the business outcomes o 4 key learnings Visualisation o Data does not need to be Big to be disruptive o Visualization of Big Data allows us to look for interesting trends and detect patterns Big Data is changing the finance industry o Real-time digital mortgage o Seamless PFM with auto-categorization o... and make sure you are the every-day-bank/insurer 28

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