Big Picture Mutuality

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2 Big Picture Mutuality Chaired by Alan Goddard, Cornish Mutual Daniel Tischer, Centre for Mutual and Employee-Owned Business, Oxford Steve Barry, ICMIF Roy Jubraj, Accenture

3 TECHNOLOGY AND INSURANCE A NATURAL MARRIAGE 12 OCTOBER 2015

4 General Insurance Trends Innovative insurers must balance digitalisation, customer centricity and legacy modernisation to compete effectively in an evolving market. Accenture Research have identified the following key trends for P&C insurers over the medium term Internet of Me A personalised world Outcome Economy Traditional business models are under threat. Outcomes over Products The Platform (R)evolution Digital platforms are becoming the tools of choice The Intelligent and Changing Enterprise Huge data, smarter systems - better business Future Products and Pricing Consumption and composite propositions Distribution in a Mobile World A dynamic, accessible and continuous consumer interaction model Workforce Reimagined Collaboration at the intersection of humans and machines Insurance is inherently about managing risk, and the key to surviving these challenges is flexibility and insight Global Insurance CEO 4

5 Customers are empowered Engagement is on their terms Platforms and devices change the playing field There is a new face of competition New Profit Pools The changing realities we can t escape 5

6 Digital Has Disrupted Customers In the last decade, consumer dynamics across sectors have deeply changed. Compared to 10 years ago Today 44% / 68% Informed and self-directed Wants access to relevant content in real time 48% Social Relies on wisdom of crowds (social media, blogs, ) 52% Online Prefers to buy insurance online 64% Price-sensitive Wants to be in control 72% Connected Wants to interact with insurers in his digital environment 78% Willing to share Will provide personal information in exchange for better, more personalised insurance cover 6

7 and transformed the industry Aggregator Telematics Usagebased insurance Connected Home Life Style Insurance The industry is being transformed by disruptive new technologies Big data & Analytics Connected people & devices Mobility Automated advice Seamless omnichannel experience Remote sensors Social media 7

8 Different Customer, Different Intensity, Different Speed Every Customer is a Digital Customer Need to pivot to the multispeed customer organisation for all customer types. Traditional They rely on traditional channels & interactions. Even then, they leave digital traces. Experimental They selectively engage in digital for utility value, discovering how the experience improves. Transitional They strive to leverage digital more broadly but may not always be able to do so. Digital Savvy They make digital technology part of all dimensions in their life. Mobile access is key. Increased Speed Higher Digital Customer Intensity 8

9 Yet Customers are being let down Findings in the review revealed that insurers are failing to engage consumers on digital channels, with just 20% responding to questions asked on Twitter and via , and only 30% answering questions satisfactorily. Sector failing on customer experience (June 2015) Report says insurance firms customer relationships are bland and undistinguished. The insurance sector has been criticised for offering its clients a "bland and undistinguished" customer experience. The review warned that companies in the insurance sector are failing to use customer experience to differentiate themselves and forcing customers to make decisions solely on price - a situation exacerbated by the aggregator sites. Review, by MyCustomer.com, a customer relationship management expert 9

10 Eight Trends Highlight Providers Struggle to Keep Pace Globally, problems of the past and digital challenges of today are key hurdles Missing out on customer growth Push customers to the exit Under-exploiting own channels Sub-optimising digital service Service still falling short Dis-Loyalty Programs Not winning back defectors Unprepared to face disruptors Intent to buy less from current companies grew (+40%) in same period. First contact resolution is consistently the top frustration over past 5 years Impact of company websites decreased versus other channels. Low digital adoption due to lack of right information (30%) or spam risk (22%) Switching due to poor service is flat or slight decreasing very slowly For 60%, key driver is access to best deals focused on short-term loyalty Many companies miss this opportunity, as switch back drivers are not compelling. Many established providers are slow to adapt to new business models 10

11 The Digital Consumer What does this mean for you? 11

12 Analytics & Insights Snapshot Data / Insights Proactive vs. Re-active Customer Analytics Claim Analytics

13 Harnessing analytics to drive growth & profit Leading organisations not only use data historically to evaluate best actions but also employ advanced analytics methods to predict and optimise future business outcomes to gain competitive advantage Analytics- Enabled Decision Making Predictive Insight to Outcome Business Intelligence Managing Information Analytical Maturity Optimisation Predictive Modelling Forecasting / Extrapolation Statistical Analysis Alerts Query / Drill Down Ad hoc reports Standard Reports What s the best that can happen? What will happen next? What if these trends continue? Why is this happening? What actions are needed? What exactly is the problem? How many, how often, where? What happened? Business Value Proactive (looking forwards at what will happen) Reactive (looking back at what has happened) Optimised Decisioning Big Data Exploitation Predictive Modelling Forecasting & Next Best Action Behavioural Analysis Advanced Data Segmentation Data Visualisation Dashboards Data Warehousing Operational Reporting Ad-hoc Query Data Management Copyright 2015 Accenture All rights reserved. 13

14 The Analytics Leap-frog Our point of view Analytics early adopters have an opportunity to get ahead and stay ahead by focusing and investing in the right areas, and emulating analytics leaders, not their industry competitors To Cross-industry leader Analytics Embedded in Every Decision From Current state - primarily Product-centric models across functional areas Batch execution of manually built models Actuarial GLM Regressions Data Built for BI Leaping the capability the industry is pursuing Big Data Lakes Uplift Modelling Voice Analytics Claims Forecasting Aggregator Quote Modelling Real-time Rules Customer-centric models Real-time digital channel connectivity Data Built for Analytics Continuous Test & Learn - Always on Personalised Next Best Action Industrialised Machine Learning Copyright 2015 Accenture All rights reserved. 14

15 Embedding Analytics Into The Insurance Lifecycle Our experience and credentials enable analytics to add value to every decision along the insurance lifecycle Stimulus Market better Price / quote better Manage claims better Build profit Zero Moment of Truth First Moment of Truth Predict Claim Events Manage Third Parties Customer Experience Brand and direct marketing Apply data to controlled marketing experiments to understand and attribute marketing activity and understand the impact and interaction with the brand Targeting models Develop a unique data insight to build separate quote and conversion uplift models combining customer insight with underwriting knowledge to improve marketing efficiency and grow sales Price and Purchase Identify customers during the sales process in real time, and respond with the right, tailored offer Understand what enriched data tells you about the insurance risk beyond the standard 10 u/w questions Predictive Analytics through the Claims Lifecycle Apply data to power claims management processes with automated predictive decisions to reduce claims costs by up to 5% and manage fraud proactively Know Your Supplier / Opponent Understand your customers and their preferences better to manage third parties during claims to improve customer outcomes and maximise value Single Customer View Embed partner data and predictive / prescriptive decision models to improve cross sales, retention and improve customer experience 15

16 Accenture Customer Analytical Record Accenture s Customer Analytical Record (CAR) is a virtual single view of the customer combining multiple disparate data sources and made available for rapid predictive modelling and real-time predictive / prescriptive applications CAR made available to: Applications / Products Historical Model Build Enable analysts to recreate single views of the customer at any historical point to enable rapid predictive / prescriptive model builds Web / mobile logs Accounts Transactions / Events External Behavioural Data Customer Journey ETL Big Data NOSQL Store Cloud In-House Hybrid Real-time Decision Management The Customer Record is made available in real-time across all channels for customer-level decisions at every customer touch-point Real-time Prescriptive / Predictive Analytics Prescriptive analytics / machine learning running at <0.3ms isolating the Individual Marketing Effect 16

17 Accenture Claims Analytical Record Accenture s Claims Analytical Record (CAR) is a virtual single view of the claimant combining multiple disparate data sources and made available for rapid predictive modelling and real-time predictive / prescriptive applications CAR made available to: Claims Notes Historical Model Build Enable analysts to recreate single views of the claim at any historical point to enable rapid predictive / prescriptive model builds Fraud Status Financial s Demographics Event History External Behavioural Data Claims Journey ETL Big Data NOSQL Store Cloud In-House Hybrid Real-time Decision Management The Claims Record is made available in real-time across all channels for claims-level decisions throughout the claims lifecycle Real-time Prescriptive / Predictive Analytics Prescriptive analytics / machine learning running at <0.3ms isolating the likelihood of adverse claims outcomes variables CAR Facts & Figures 0.3ms response time 20+ Insurance clients 2-4 Weeks custom development 13 Years of development 17

18 Next Best Action for Claims Powering a claims department s claims processes with automated predictive decisions is helping insurers identify opportunities to reduce claims losses by up to 5% Post-FNOL Assignment Identifies claims that are more sensitive to the experience of the claims handler and enables predictive assignment post- FNOL Factors include: Text mining of claims notes FNOL detail capture Age of claimant Large Loss Prediction Although large losses contribute less than 2% of claims volume, machine learning can be used to identify claims earlier in the process that have a significant chance of becoming a large loss Preventative action can then be taken including re-ass ignment to an experienced operator and proactive claimant contact Cross-sell / Retention Messages Following a successful claims process, advanced analytics was used to test and learn the most valued treatment to apply to a satisfied customer including: Product cross-sell Up-sell of any missing cover Retention messages and offers FNOL Assessment Liability Triage Negotiate Settlement Straight Through Processing Prescriptive analytics can use integrated rules based dec isi oni ng to: optimise various processing points reducing handler effort; and improve the customer experience Subrogation & Complaints Prediction Subrogation models can help identify recovery opportunities for both historic and current claims A combination text mining claims notes and predictive analytics can be used to identify those claims which are most likely to result in a complaint Settlement Sensitivity Prescriptive analytics can be integrated with external data sources to evaluate price points and determine the optimal settlement method Price and timing are key components with some claimants accepting lower offers at certain points in the process and/or month 18

19 Know Your Supplier The Claims Analytical Record can be rolled up to Supplier level to optimise which claims should be routed to which suppliers and help reduce claims loss cost and potential complaints Improve supplier assignment by identifying those claims which are more likely to result in complaints if routed to particular repairers Insight-to-Action-to -Outcome Identify opportunities to reduce claims loss cost by leveraging nuanced insight into every supplier and comparable cost breakdowns Supplier Analytical Record Use analysis to re-tier supplier network and feed a claimant level prescriptive model to optimise customer journey 19

20 What we d like to talk about 1hr 45min 20

21 How are Accenture Achieving This? The Insurance Labs Drivers Changing Consumer Digital Mobile, apps Cloud, In memory Next Gen Applications Data is the new currency Demands Radical Cost reduction Flexibility Pace & Agility Certainty& reliability Simplicity Power & Capability to differentiate Insight Key Facts Integrated, Omni Channel Online capabilities, Policy, Rating, Billing and Claims, CRM and Analytics, using best of breed assets and products Performance tuned, 20m quotes a day with sub second response times Configuration based assets built on a modern flexible architecture Duck Creek & Best of Breed Software Hub for Alliance partners to integrate OOTB Best-of- Breed software solutions Many organisations talk about digital insurer we decided to build it Cloud Cloud (Azure) Hosted, rapid release and scalable {logo} Investment $87m globally in FY15 $4m in UK Insurance Labs alone over 24 months Deployment Factory Agile labs environment deployment factory CRP approach for delivery at scale Content & Product accelerators Available Now Available Now Available Now Available Now 21

22 The Digital Insurer 22

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