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    Home»Virtual Banking»AI Neobanks McKinsey Study: Long-Term Success of Virtual Banks Hinges on Ability to Leverage AI, Data Analytics
    Virtual Banking

    AI Neobanks McKinsey Study: Long-Term Success of Virtual Banks Hinges on Ability to Leverage AI, Data Analytics

    Fintechnews SwitzerlandFintechnews SwitzerlandJuly 13, 20236 Mins Read
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    Neobanks’ Long-Term Success Hinges on Ability to Leverage AI, Data Analytics: McKinsey
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    Neobanks are proliferating around the world on the back of strong trends including technological advancements, regulatory changes and evolving customer expectations. And yet, despite the favorable market conditions, many are still struggling to turn a profit. For neobanks to be successful in the long run, these companies will need to embrace an artificial intelligence (AI)-powered banking model, a report by global consulting firm McKinsey and Company says.

    Titled “Building a Winning AI Neobank”, the report discusses the rise of neobanks and explores how launching a successful neobank in today’s uncertain environment requires firms to target specific characteristics and capabilities in their strategy and execution plans, suggesting that incorporating AI technology can increase the odds of success.

    Around 400 licensed neobanks have been launched over the last decade, encompassing digital-only banks, virtual banks, and challenger banks, the report says. These companies are resetting the paradigm for the traditional banking industry in terms of customer experience, product innovation, and pricing.

    Bottomline

    But when it comes to financial performance, however, only a handful of these players have actually found success and reached profitability. A 2022 report by consulting firm Simon-Kucher suggests that only a mere 5% of the world’s 400 digital banks are profitable. The firm estimates that most digital banks in the world earn less than US$30 in revenue per customer per year and that cash burn rates remain stellar high for many of them, with annual losses exceeding US$100 million in some cases.

    AI-powered digital banking

    Against this backdrop, McKinsey argues that AI capabilities and data analytics can help neobanks deepen customer relationships This is made possible by enabling intelligent value propositions that solve unmet needs, hyper-personalized services and enhanced cross-selling. AI can also help neobanks improve financial performance and increase efficiencies by maximizing customer lifetime value, lowering the cost to serve through automation, and adopting superior data-driven risk management practices, the report says.

    The report outlines a framework of winning characteristics and capabilities that new entrants should incorporate in their strategy and execution to become a future-ready neobank. These characteristics are:

    • Launching products at high velocity: Winning neobanks are rapidly launching and adapting new products to meet evolving customer needs. Neobanks with an AI-first mindset accomplish this in months or even weeks, rather than years. They invest significantly in gathering and analyzing customer data, employ full-stack teams, and maintain flexible tech platforms that enable the easy creation of new products. Revolut, for example, started with two products in 2015 but expanded to 20 products and services by 2020, launching a new product every quarter, according to fintech research firm WhiteSight.
    • A focus on customer engagement: Successful neobanks prioritize customer engagement as a precursor to monetarization. They offer more than just transactional experiences or bundled core products, extending their services to include complementary offerings that provide utility, information, and entertainment. Swedish buy now, pay later (BNPL) leader Klarna, for example, uses a machine learning (ML)-based recommendation system to determine consumer purchase patterns, and offer appropriate shopping recommendations and financing offers.
    • Hyper-personalizing experiences and propositions: Successful neobanks excel in hyper-personalizing customer experiences and propositions through the use of ML and by leveraging customer context, historical behavior and movement patterns. Some also automate mundane tasks based on customer preferences. In the UK, digital bank Monzo offers automatic savings features that round up transactions and transfer the excess money to a separate account.
    • Adopt conversational design: AI-focused neobanks leverage conversational design, such as chatbots, voice assistants, and live video consultations, to enhance customer communication, replacing traditional forms and questionnaires with interactive conversations. In China, WeBank says it addresses 98% of customer queries through AI chatbots, allowing it to efficiently scale while serving millions of customers. This characteristic drives cost-efficiency. Juniper Research estimates that chatbots could help the global banking sector save up to US$7.3 billion in operational costs by 2023, equivalent to roughly 862 million hours of time saved.
    • Integration of open banking features: Successful neobanks gain a competitive edge by integrating open banking features. These companies prioritize an open-first approach from the start, investing in API-first architecture and experiences to tap into the wider open banking ecosystem and provide superior products and services. In the US, Chime utilizes open banking features through its partner Plaid, enabling customers to link all their bank accounts within the Chime app and get a comprehensive view of their finances. This helps Chime increase user engagement and app usage.
    • Leveraging partner ecosystems to scale: Winning neobanks embed their services within social media platforms, digital commerce, healthcare and lifestyle brands, providing customers with easy access to banking services whenever they engage with these partners. By doing so, neobanks increase their discoverability, accelerate growth, and are able to leverage partner data to offer contextually relevant offers to customers in real time. In South Korea, KakaoBank utilizes the scale and popularity of Kakao’s various ecosystems and digital platforms to successfully serve its 18 million customers.
    • Using customer-lifetime-value (LTV) to guide actions: Successful neobanks analyze customer-centric metrics like LTV, customer acquisition costs (CAC), and return on investment to guide their actions and create value. They go beyond traditional balance sheet metrics, analyzing granular data to tailor their strategies and operations. Block Finance’s mobile payment service Cash App, for example, tracks and reports customer LTV curves with the returns from its customer cohorts, plotted against the time since the customers started using Cash App. The company claims this strategy has allowed the Cash App to reach CAC breakeven within six months of acquiring a customer and earns six times CAC within 18 months.

    The rise of neobanking

    Digital banks and neobanking startups have gained ground these past years, owing to deregulation efforts from governments, changing customer habits and technological advancements.

    A 2023 report by banking and payment technology company BPC and strategy consultancy Fincog estimates that more than 500 digital banks are currently in operation around the world, providing services to approximately 1 billion customers.

    Data from statistics portal and market research provider Statista show that emerging markets are leading the way. Of the world’s 14 biggest digital banks by customer count, 10 originated from an emerging market, including China, India and Brazil.

    Number of customer accounts at selected digital challenger banks worldwide in 2021 (in millions), Source: Statista, Nov 2022
    Number of customer accounts at selected digital challenger banks worldwide in 2021 (in millions), Source: Statista, Nov 2022

    In Europe, 162 digital banks operated in the continent in 2022. As of Q1 2023, the region’s top ten biggest neobanks, which include Revolut, Wise and N26, served a combined 64 million customers. Some research studies estimate that user penetration stood at about 7–10% but expect the figure to hit about 14% by 2027.

     

    Featured image credit: Edited from freepik

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