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December 21, 2018Moving Beyond the Hype: Six Real-Life ApplicationsMoving Beyond the Hype: Six Real-Life Applicationsof AI in FinTechof AI in FinTechOlga Ezzheva

Artificial intelligence (AI) may well be at the peakof its hype cycle now. The World Economic Forumdubbed AI — and a suit of other fast-evolvingnovel technologies — a herald of the FourthIndustrial Revolution

(https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/), acknowledging the tech’s potential to drive transformativechanges across economies and impact society at scale.

From advanced computational power to understanding natural language to recognizingvisual objects, AI brings a multitude of capabilities and augments human intelligence.Industries are leveraging AI to automate complex workflows, create new efficiencies,surface underlying patterns, and support decision making.

As an industry that relies heavily on technology and innovation, FinTech became one ofthe first to move past the buzz and start reaping real-world benefits brought by artificialintelligence. In this article, we’ll explore six practical ways how forward-thinking financialcompanies can implement AI tools and get a jump on the competition.

Better Customer ServiceBetter Customer ServiceCustomer centricity is not only a growing trend but

a winning strategy for businesses that try to attractand retain prospects, foster loyalty, and improve theirbottom line. And a customer-focused approach gainseven more prominence as tech-savvy Millennials andGeneration Z flood the consumer market cravingconvenient, accessible, and customized products.

To better serve their customers, FinTech companiesemploy a new type of assistants — conversationalchatbots. Powered by AI, these tools can easilyautomate repetitive tasks, provide 24/7 customersupport, and instantly inform users on their balance,credit limit, or transaction history — all without humanintervention.

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Chatbots are typically poweredby AI (denvitruk/Shutterstock)

(https://2s7gjr373w3x22jf92z99mgm5w-wpengine.netdna-ssl.com/wp-content/uploads/2016/09/shutterstock_show_me_the_money_Elegant-Solution.jpg)

AI can help build wealth (ElegantSolution/Shutterstock)

To further enhance customer satisfaction, AI chatbotsleverage Natural Language Processing (NLP). This techenables chatbots to understand the sentiment — toneand emotions — behind a user’s input and to tailortheir response accordingly.

Data-Driven PersonalizationData-Driven PersonalizationAnother way that AI helps financial firms put their customers at the heart of theirbusiness is through personalization. By leveraging the tech, financial service providersare able to shift from “one-size-fits-all” products to personalized offers aligned withcustomers’ needs and expectations.

To hit a customer’s sweet spot with a tailored product, FinTech firms invest in powerfulmachine learning (https://www.oxagile.com/solutions/machine-learning-development-services/) solutions that automatically collect and analyze loads of data includingfinancial transactions and account details, real-time and historical market data, as well asnuggets of information mined from social media for a 360-degree view of a prospect.

Based on this input, AI-powered tools recognize behavior patterns and return clues in theform of actionable insights and highly accurate predictions. Suppose your users dogrocery shopping twice a month — a smart virtual financial assistant can send themtimely personalized offers with discounts and promo campaigns to save money. Or, if auser sets a savings goal, develop a personal spending plan based on a user’s budget,which would not send them into overdraft.

Informed Wealth ManagementInformed Wealth ManagementIn a $79 trillion wealth management industry

(https://www.statista.com/statistics/323928/global-assets-under-management/),artificial intelligence is gaining traction as both wealth advisors and tech-savvy investorsacknowledge AI’s potential in delivering better business results. In fact, 99% of wealthmanagers (https://www.temenos.com/globalassets/mi/rep/ai-and-the-modern-wealth-manager.pdf) are planning to implement AI in the next three years, and 84% of high-net-worth individuals (HNWI) are very optimistic about the technology.

With hundreds of accounts under management, a wealth advisor might find it difficult notto lose human touch with their clients through all the repetitive, time-consumingoperations. AI does not only take mundane tasks off a wealth manager’s hands but alsodelivers data-driven insights tied directly to a client’s goals. AI-powered algorithmsidentify market trends, monitor stock prices, recognize correlations, and empower wealthadvisors with optimized recommendations for risk management and asset allocation.

Another example of implementing AI in wealth management services is robo-advisors.With higher availability and fees lower than those of a financial advisor, these AI-supported solutions open up investment opportunities to larger population groups. Robo-advisors help construct, manage and optimize an investment portfolio in line with aclient’s needs and risk tolerance.

Smarter InsuranceSmarter InsuranceAI capabilities to unlock insights and inform decisions underpin transformations in theinsurance sector. In particular, insurers tap into the power of machine learning tostreamline the underwriting process and better serve their clients. ML-enabled solutionsanalyze thousands of data points from diverse sources and deliver accurate riskassessment, resulting in intelligent and automated underwriting.

This intelligent automation is also bringing new efficiencies to сlaim settlement.Tractable (https://tractable.ai/) has rolled out its new AI solution for motor claimshandling, which leverages deep learning and computer vision to analyze a policyholder’spictures, assess vehicle damage and provide a repair estimate — in seconds.

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applications-of-ai-in-fintech%2F&title=Moving%20Beyond%20the%20Hype%3A%20Six%20Real-Life%20Applications%20of%20AI%20in%20FinTech)

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AI can drive alternative creditscoring methodologies (WrightStudio/Shutterstock)

Ubiquitous connectivity and the Internet of Things encourage insurers across industriesto diversify their offerings with usage-based insurance plans. In health insurance, clientdata collected from fitness trackers and smartphones enable insurance service providersto fine-tune their pricing policies and allow people with healthier lifestyles to pay less.

Global Financial InclusionGlobal Financial InclusionThe World Bank estimates that globally 1.7 billion adults have no bank account(https://www.worldbank.org/en/news/press-release/2018/04/19/financial-inclusion-on-the-rise-but-gaps-remain-global-findex-database-shows) and, as a result, no access tobasic banking products — credit, savings, insurance, or money transfer services.Excluded from the financial system, the unbanked households struggle to take controlover their financial health.

The financial sector is embracing AI and machinelearning to bring the underserved segment back intothe economy. The proliferation of mobile phonesenables FinTech firms to use both traditional andnon-traditional data to determine a user’screditworthiness.

One example includes Lenddo’s(https://www.lenddo.com/index.html) sophisticatedML algorithms that analyze a person’s digitalfootprint — social media, browsing history, onlinetransactions, etc. — and deliver a credit score. Byusing these scores, financial institutions candistinguish good and bad borrowers and significantlyimprove their loan approval rate.

Better Fraud DetectionBetter Fraud DetectionMachine learning technology lends itself well todetecting fraud — another pressing issue forfinancial institutions. According to The Nilson Report(https://nilsonreport.com/index.php), by 2020 worldwide losses from payment cardfraud will amount to $35,4 billion.

To stay on top of any fraudulent activity, banks are increasingly adding ML solutions totheir arsenal. The pre-trained algorithms analyze a multitude of data points and comparethe result against global sets of fraud data and an individual’s historical data to spot anyoutlier activity in real time. Likewise, insurance companies boost their toolkit withadvanced AI tools to detect fake claims that cost industry billions of dollars.

Summing UpSumming UpThe buzz around artificial intelligence has been going on for decades now. And while thetechnology still has a lot of maturing to do, it has advanced to the point of deliveringreal-world value. In a data-intensive financial sector, AI emerges as a key enabler of afront-to-back digital transformation as FinTech companies leverage the tech to enhancecustomer service with personalized offerings, automate business operations, informdecision making, and combat fraud.(https://2s7gjr373w3x22jf92z99mgm5w-wpengine.netdna-ssl.com/wp-content/uploads/2018/12/Olga-Ezzheva.png)

About the author: Olga Ezzheva is a Technology Writer atwww.oxagile.com (http://www.oxagile.com), a provider ofsoftware engineering and IT consulting services for SMEs andFortune 500 companies alike. You can reach Olga atolga.ezzheva@oxagile.com or connect via LinkedIn(https://www.linkedin.com/in/olga-ezzheva-46aa6690/).

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