Appier predicting customer behavior in financial services shared by worldline technology

$ How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI White paper September 2019 Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI The last decade has seen a swift uptake in digital technology by Disruptors & Challengers consumers, and the financial services sector is no different Although many traditional financial institutions have already started their digital transformation, which has equipped them with the data to better understand their customers, so have organizations in other fields¹ The disruptors and challengers in the market, particularly those from non-finance sectors such as Baidu, Tencent and Grab, as well as giants Google and Facebook, also have access to customer data – but from different digital touchpoints Marketing in the financial services sector has changed as well, with a personalized approach considered more effective than broad brushstrokes The new breed of marketing recognizes that customers want to make educated decisions about their money, but the information must be timely, relevant, trustworthy and accessible The challenge for marketers is to build a meaningful relationship with customers and keep them informed so their brand is top of mind when the right moment to engage with consumers arises, whether that is to capture a new client or renew an existing relationship Artificial intelligence (AI) helps marketers create a holistic view of their potential customers by collating and analyzing information from a broad spectrum of data points By identifying intent, marketers can then segment users, predict behavior and expand a business’ reach through lookalike audiences This white paper addresses some of the questions marketers in the financial services sector have and illustrates how AI can help analyze data, make precise predictions and offer insights that enable marketers to create more effective strategy and campaigns https://www.mckinsey.com/~/media/McKinsey/Industries/Financial%20Services/Our%20Insights/Reaching%20Asias%20digital%20banking%20customers/ Asias-digital-banking-race-WEB-FINAL.ashx Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI The top five biggest banks in the world are located in Asia, and four of those belong to China² Additionally, the banking market in emerging Asia-Pacific (APAC) countries is the fastest growing in the world While ‘big’ and ‘growing’ are important factors to provide scope for financial services marketers, it is in the fine print that they will find the gold – these markets are driven by an increasing focus on digitization Early adopters include China and India, where mistrust due to counterfeit banknotes hastened the uptake of cashless payment systems³ Other countries such as Japan and Malaysia have adopted boosting digital payments as government and national bank policy4 Greenfield markets like The Philippines, where fewer than 35% of people over the age of 15 have a bank account5, are also ripe for digital transformation, bypassing traditional financial institutions This also leaves the markets open for new digital-only lenders, including peer-to-peer platforms such as Funding Societies and CreditEase Digital adoption in banking Early adopters: China, India Markets that adopted digital payments: Japan, Malaysia Greenfield markets: The Philippines https://www.forbes.com/sites/peterpham/2018/01/16/why-is-asia-home-to-the-worlds-biggest-banks/#641abcd733fe https://issuu.com/adellegrisaffe/docs/rfimedia-tabm-august_2018 https://www.japantimes.co.jp/news/2018/12/03/reference/japan-grudgingly-heads-toward-cashless-society/#.XAdT5ydoRj1 https://issuu.com/adellegrisaffe/docs/rfimedia-tabm-august_2018 Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI The APAC fintech market will be worth US$72 billion by 20206 and the rising adoption of digital payment systems gives financial institutions and challenger service platforms unprecedented insights into their customers What this means for marketers is a vast amount of data to sift through and find patterns in to better target existing customers, determine lookalike clients and predict their behavior This is where AI will come to the fore A recent Forrest Study stated that already 51% of the financial services firms in APAC had adopted AI tools in 2018, while 27% were planning to so in the next 12 months7 AI adoption among financial services firms in APAC have adopted were planning to so in the next 12 months Moving Towards AI An increasing number of financial services customers will interact with chatbots during their on-boarding in the near future, according to a survey of ASEAN and Hong Kong financial institutions More than 30% of respondents predicted that AI and chatbots would be the top technology influencer for financial services over the next 12-18 months8 Moreover, Gartner states that by 2020, 25% of all online customer service operations will use some sort of assistive technology such as chatbots9 https://ww2.frost.com/news/press-releases/asia-pacific-fintech-market-reach-us72-billion-2020-finds-frost-sullivan/ https://www.appier.com/asias-financial-services-industry-embraces-ai-led-future/ https://www.ey.com/Publication/vwLUAssets/EY-white-paper-driving-digital-into-the-heart-of-asias-financial-services-industry-final/$File/ EY-white-paper-driving-digital-into-the-heart-of-asias-financial-services-industry-final.pdf https://www.gartner.com/en/newsroom/press-releases/2018-02-19-gartner-says-25-percent-of-customer-service-operations-will-use-virtual-customer-assistants-by-2020 Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI The main challenge for the financial services industry in the region also offers plenty of opportunity Different maturity levels across Asian countries with diverse economies and varying sophistication of infrastructure may appear frustrating at first but, in effect, digitization is well accepted across the region and individual countries are simply at different stages of transitioning Those leading the fintech evolution, such as China, Singapore and South Korea, have influence over less mature economies, and this could give marketers insights into customers coming from societies where many citizens not have bank accounts, such as Indonesia, Thailand, The Philippines and Vietnam, who are making the leap to digital-only financial services¹0 The kind of education marketers need to impart in less financially mature markets will drive trust factors and may need to accommodate technological as well as financial literacy 10 https://www.ey.com/Publication/vwLUAssets/EY-white-paper-driving-digital-into-the-heart-of-asias-financial-services-industry-final/$File/ EY-white-paper-driving-digital-into-the-heart-of-asias-financial-services-industry-final.pdf Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI $ $ The convergence between incumbent financial institutions with fintech, telecommunications and e-commerce is also a trend to watch A recent survey of executives from ASEAN and Hong Kong financial institutions revealed that 77.2% believed there would be more convergence in the space¹¹ Players like Tencent, which owns China’s social media and messaging app WeChat and its payment system WeChat Pay, and China Pacific’s partnership with Baidu to create an online auto insurance business¹², have shown what convergence might look like in the social and e-commerce space It also hints at the significant advantages they hold in data aggregation and analytics capability Consumer expectations have also changed, with ‘on-demand’ requests for information and services becoming the norm This reflects an emerging trend to capture the micro-moment – the reflexive point at which a consumer turns to a device to find, learn or buy something – an important battle to win¹³ While financial marketers have historical data to help them predict consumer behavior and ensure they present timely information, ‘a-commerce’, the ability to purchase from ‘anywhere’, including social media platforms, will have the advantage of drawing from a different, more dynamic dataset¹4 11 https://www.ey.com/Publication/vwLUAssets/EY-white-paper-driving-digital-into-the-heart-of-asias-financial-services-industry-final/$File/ EY-white-paper-driving-digital-into-the-heart-of-asias-financial-services-industry-final.pdf 12 https://www.ey.com/Publication/vwLUAssets/ey-2017-asia-pacific-insurance-outlook/%24FILE/ey-2017-asia-pacific-insurance-outlook.pdf 13 http://www.adnews.com.au/opinion/from-neo-banks-to-micro-moments-financial-marketing-trends-for-2019 14 http://info.microsoft.com/rs/157-GQE-382/images/EN-US-CNTNT-Report-2019-Finance-Trends.pdf Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI To promote a suite of complex banking, investment and insurance products in this environment presents an interesting problem for marketers: how to inform and educate consumers, and tailor products and services to their personal needs while remaining accessible 24/7? Data alone is not enough, marketers require a way to visualize and analyze that data to make better decisions Key questions remain: How to consolidate data into a single customer view? The volume of data is not an issue The increasing digitization of payment systems and wholesale rejection of cryptocurrency¹5 across the region has ensured data collection from both immature and sophisticated markets The challenge is to collate data gathered from different sources, including websites, campaigns, apps, customer relationship management (CRM), API integration and more With data from such disparate sources, how can marketers extract any meaningful insights? Do their audiences act differently across devices? How marketers know the right timing and right device to engage? How to identify the right audience? The financial services sector is not just for wealthy professionals; there are many different audiences for different services When is the best time for an insurance provider to target a new homeowner? How does a business lender know if it’s worth approaching a micro business owner? And when will that real estate investor have spare capital for her next property? 15 https://issuu.com/adellegrisaffe/docs/rfimedia-tabm-feb2018 Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI How to understand user intent? Historical data can churn out probable behavior based on past actions, $ but AI looks at data more dynamically What behavior does a potential investor exhibit when they are looking for a wealth management advisor versus a self-managed option? How can a marketer tell the difference between a user who is educating themselves and investigating their options and one who is ready to apply for a mortgage? How to predict user behavior? How can marketers know which factors will have the most influence over whether users convert into clients or not? Is a user more likely to convert when she has just asked a question on an online wealth forum or after she has read an article about Asia’s most successful investors? Demographics, past behavior and current context and circumstances need to be combined to make marketing hyper-relevant and predictive¹6 How to expand the reach and find new customers? Acquiring new customers is never easy, especially when the trust factor comes into play Who or what influences someone to bank with a certain institution? Which customers are a source of untapped potential, and how should organizations unlock them? How to prevent churn? Which customers are leaving the website, the mailing list, the app? Why are they leaving? How should financial services firms re-engage them? 16 https://www.accenture.com/t20180219T081429Z w /us-en/_acnmedia/PDF-71/Accenture-Global-DD-GCPR-Hyper-Relevance-POV-V12.pdf Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI Big data has been kind to marketers in the recent past, but making sense of an ever-growing collection of information is currently one of their toughest challenges In finance, that data comes from both financial transactions performed by customers as well as the information they are seeking online with regard to financial services Today’s AI platforms have been developed to unify data, provide predictive intelligence and assist with automation Combined, these AI functions will generate US$2.1 trillion in business value by 2021¹7 AI platforms like Appier’s Data Science Platform AIXON¹8 not only use historical data, such as transactions, previous campaign results and past user behavior, to develop patterns as an indicator of future behavior, but also transform this information to find new audiences and target them in a predictive way The more data marketers feed AI, the more accurate results it can produce, and the easier it is to address marketers’ questions and pain points Before running a campaign, marketers can also select datasets to focus on and preview likely results before deployment Consolidate fragmented data sources Many marketers are unable to truly leverage their customer data simply because they lack a single customer view that is essential for marketing success AI-powered data science platforms merge customer data from different marketing and customer service channels, including owned channels (website, app, CRM and offline data) and external channels (web and app), into one place This offers a more holistic and comprehensive view of customers beyond their demographics, revealing their interests, habits and cross-screen behavior Marketers can then use these insights to create better targeted and better timed marketing campaigns that boost interest, engagement and conversion 17 http://info.microsoft.com/rs/157-GQE-382/images/EN-US-CNTNT-Report-2019-Finance-Trends.pdf 18 https://www.appier.com/en/product.html#aixonPlatform Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI Find the right audience A user doesn’t need to have been a customer – nor even have held a bank account – to be in an organization’s potential market Advanced AI models can help track, unify and analyze cross-screen behavior across multiple devices to identify potential customers Consider Andy who has bought an ebook by a well-known entrepreneur, and later that day scans online listings of properties with retail leases Perhaps he is also an active Alibaba customer The data might also show that he has recently been made redundant from a well-paid job with a large payout A small business lender might consider him an interesting prospect Buys an ebook by an entrepreneur Views properties with retail leases online Alibaba customer Redundant from a well-paid job A small business lender might consider him an interesting prospect Understand user intent and behavior AI is also good at predicting a user’s next step by identifying where the customer is in the purchase cycle Matching campaigns with customer readiness can save marketers’ time and money A customer searching for more information on a type of insurance will respond well to a content marketing push, for example, whereas another customer comparing specific products is more than likely ready to interact with a chatbot to confirm a decision and apply Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI Marketers can also use AI to home in on spending Interested in interior design Renew Subscription habits and interests so they know exactly when a homeowner Jenny in Malaysia with a penchant for interior design is ready to think about refinancing her Scanned Carpenters mortgage Perhaps she has just renewed her subscription to the CreativeHome magazine and has recently scanned Houzz for the Best 15 Carpenters in Malaysia – a sign that an extension or renovation is on the horizon that will need to be funded by her existing loan Create predictive audience segments AI can also combine data in surprising ways By analyzing user intent and behavior, AI can create predictive segments from seemingly obscure demographic information, habits or interests outside of an organization’s own online environment, using data from offline sources or third-party data For example, a Vietnamese man in his early 20s could be a potential client for his first bank account, and his recent review praising a restaurant for its good value meals might indicate he is becoming more serious about saving AI can create a segment like ‘Vietnamese man who is a foodie and likes sushi’ based on these thin threads of data Such actionable insights enable marketers to deploy the best campaign – including the right message, visuals, products and pricing – that is likely to resonate with their audience at the best time in order to entice a user to convert € Age: 20+ Prefers good value meals Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI Expand with new customers Creating a lookalike audience is not just about replicating CRM information AI finds invisible patterns that go beyond demographics and dive deep into habits and behavior, including combinations that may include keywords plus sites recently visited, and recent purchases on non-finance-related websites As AI works across multiple channels and devices, it can help marketers tap into unrealized potential among lookalikes Let's look at a building society in Singapore that wants to increase its share of the home loan market AI can create a 'lookalike' audience based on mortgage data in the institution's CRM system, plus other data collected from external channels As an example, perhaps the leads most likely to convert had visited a particular shopping website in the month prior to visiting the institution’s, used the search term ‘what is conveyancing’ in the last five days and tried out the home loan calculator on the site before making contact AI finds hidden signals in the data to indicate potential borrowers that not need to be demographically similar to existing mortgagors to be ripe for conversion Prevent churn $ AI can also identify existing customers who display behavior that indicates they are about to churn This gives marketers a chance to use re-engagement tactics to lift their retention rate and convert potential losses into opportunities Consider Andy who hasn’t used his credit card for more than a month, when there are usually five regular deductions for bill payments in each cycle The bank can remind him of how a credit card is convenient for bill payments because it can help with cash flow to realign its value with his needs and desires, and then take steps to move him along the funnel again via personalized engagement Predicting Customer Behavior in Financial Services How Artificial Intelligence and Data Science Enable Better Marketing and Higher ROI The rapid digitization of the financial services sector and the increasing convergence of technology platforms to provide financial services give marketers an unprecedented amount of data about their existing and potential customers This vast data bank requires a teller, however – one that will provide actionable insights to help marketers attract and retain customers AI platforms such as AIXON supports marketers to develop a more detailed understanding of users so they can be targeted with the appropriate campaign at different stages in the purchase cycle The power of AI and its analytical capabilities helps marketers deliver the right campaign at the right time to ensure every opportunity is golden About AIXON AIXON is a Data Science Platform that unifies and enriches existing customer data to help you better understand your audience and run AI models easily to predict their future actions.  Learn More Watch Video Case Studies About Appier Appier is a technology company that provides AI platforms to help enterprises solve their most challenging business problems Appier was established by a passionate team of computer scientists and engineers with expertise in AI, data analysis and distributed systems Learn More Making Artificial Intelligence Easy www.appier.com ... technology influencer for financial services over the next 12-18 months8 Moreover, Gartner states that by 2020, 25% of all online customer service operations will use some sort of assistive technology. .. marketers create a holistic view of their potential customers by collating and analyzing information from a broad spectrum of data points By identifying intent, marketers can then segment users, predict... Enable Better Marketing and Higher ROI The last decade has seen a swift uptake in digital technology by Disruptors & Challengers consumers, and the financial services sector is no different Although