The Way Forward: 21 Ideas for Bank Leaders to Boost Business after the Crisis

DANIEL FASNACHT | March 25, 2020

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In the hardest times, there is always a way to get better. With the Way Forward, I’d like to share disruptive changes that shape industries, businesses, and societies in the context of financial services. The 21 notes synthesise the findings of openness, flexibility, and customer-centricity in a digital world driven by platform business models and ecosystems. The reading shall give you a glimpse of what you could do for your business after this unprecedented time.

Spotlight

Romulus Capital

Romulus Capital invests in early-stage technology companies that are looking to become industry leaders. We invest in brilliant – often first-time – entrepreneurs often affiliated with top universities and incubators; as a given company grows, our total investment can scale to $5M and beyond. We are focused on company-building, rather than betting, and we remain strong partners throughout the trajectory of growth. Our firm is youthful, entrepreneurial, and experienced, with a powerful investor base from around the world.

OTHER ARTICLES

Which Fintech sectors will emerge fighting fit from the current Covid-19 crisis?

Article | March 31, 2020

Whilst the current pandemic induced crisis is yet to reach its peak, and is leaving a trail of personal and economic destruction, we should expect a new landscape to emerge, in many respects, when the dust settles. What does this mean for the Fintech sector in terms of opportunities and how does this impact the individual?

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Banking-as-a-Service (BaaS) Empowers Any Brand to Offer Financial Services

Article | May 14, 2021

Digital banking is not new – major banks began to offer internet banking services in the mid-1990s. However, the traditional banking industry is facing significant pressure from rapidly shifting consumer expectations, changing regulations and increasing competition from digital-native disruptors. Younger Gen Z customers are more apt to use alternative transaction methods such as mobile wallets or P2P payments (e.g., PayPal or the Dutch payment app Tikkie), and businesses are beginning to favor real-time digital payments to improve efficiency, reduce cost and better manage their cash flow. Moreover the ongoing global health crisis is accelerating the movement toward real-time contactless digital payments. Fifty-six countries are now live with real-time payments, and six countries more than doubled their volume of real-time payments in the past year. [i] Due to a joint implementation of the major banks led by the Dutch Payments Association (Betaalvereniging Nederland), the Netherlands is a European leader in terms of the adoption of real-time payments. In the midst of this fast-changing landscape, new business models are arising as digital-natives, FinTechs and incumbent banks partner to offer new banking and payment services in the cloud. One example is Dutch Cobase – a subsidiary of ING Group that bundles business accounts – which recently signed a cooperation agreement with the Nordic bank Nordea and the French Crédit Agricole. Amsterdam-based banking platform Five Degrees supplies its technology to banks such as ABN Amro, Van Lanschot and Knab, among others. Collaboration like this is spurring further innovation as these digital ecosystems expand, attracting new participants. But successfully delivering these new digital services requires the direct and secure, low-latency, reliable exchange of data between partners that interconnection can provide. BaaS needs FinTechs AND banks FinTechs born in the cloud have the IT infrastructure, skills and agility to deliver digital banking and payment services on-demand. They can also offer these BaaS capabilities to any brand who wants to embed financial services in their customer experience. Sometimes referred to as “embedded finance,” BaaS enables businesses to create new products and services along the customer journey as the diagram below illustrates. However, FinTechs typically lack the assets and regulatory license to fulfill financial transactions, and that’s where banks come in. To ensure that deposits and money transfers stay safe, banks are heavily regulated and often insured up to a certain dollar amount for each depositor. This combined with a longer history with customers means that banks have an advantage when it comes to perceptions of how safe and secure a financial transaction will be. As a result, there are a few collaboration paths that FinTechs and banks generally pursue to bring BaaS services to the market: The FinTech buys a bank that already has a license such as Jiko purchasing Mid Central National Bank in the U.S. or Raisin GmbH buying MHG-Bank AG in Germany. The FinTech partners with a bank to borrow their license such as Chime partnering with Stride Bank, N.A. and The Bancorp Bank. The FinTech acquires its own license (a lengthy process that could take up to three years) such as Railsbank in the U.K. or Varo Money in the U.S. The bank partners with a FinTech to launch BaaS services such as Deutsche Bank partnering with Traxpay to integrate supply chain financing technologies and solutions within its own offerings. Regulations are shaping the partnering model The regulatory environment may also impact the partnering model. For example, open banking laws in the European Union and the U.K. require banks to open APIs to third-party developers, making it easier for FinTechs to gain access to bank data. Regulations like these are helping to reduce uncertainty for startups and accelerate innovation in the European banking system. Challenger banks such as U.K.-based Revolut have also benefitted from special licenses that allow them to directly accept deposits, process payments or lend. In the U.S., the Durbin Amendment is accelerating partnerships between small-medium banks and FinTechs in a different way. The Amendment, which has been in effect since 2011, aimed to lower prices for consumers by reducing the fees that retail stores pay to banks when customers use debit cards. In reality, banks just responded by increasing the fees that consumers pay to make up the lost revenue. However, the Durbin Amendment exempts financial institutions with less than $10 billion, making them ideal partnering candidates for FinTechs. How BaaS actually works A hybrid digital architecture for BaaS with a mix of on-premises, colocation and public/private cloud elements. In this example, the bank is the license holder partnering with the FinTech BaaS provider to deliver embedded financial services to a Brand (such as a retailer or transportation business). The bank has also partnered with other FinTechs for real-time and cross-border payments, although it handles any card transactions in-house. Interconnection will be critical for ensuring secure, low latency data flows between the partners and digital infrastructure across the regions where the BaaS is offered. Partnerships like these are steadily growing into ecosystems of digital exchange around financial services that include clouds, networks, banks, FinTechs, payment rails, fraud detection and other service providers. By placing their digital infrastructure close to these ecosystems, leveraging an interconnection approach, banks and FinTechs alike can maximize their competitive advantage. Interconnection provides a more scalable, reliable, secure approach to moving data between members of the value chain than the public internet. With an interconnection strategy, banks and FinTechs can deploy a digital core, extend across edge locations and enhance their capabilities through digital exchange to create new BaaS markets for any brand.

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4 Fintech Trends to Watch For in 2020

Article | February 26, 2020

The fintech industry is one of the most visibly disruptive sectors since it can dramatically impact everyday consumers as well as the business of all sizes. It’s also potentially a highly regulated sector, with governments and regulators well aware of the need to both protect consumers and businesses, and to provide a fair, competitive environment for industry players.

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How Banks can use Artificial Intelligence to Constantly Innovate at Scale

Article | April 6, 2020

The world is digitizing, and the world is digitizing because we’re seeking low friction and immediacy. We want immediate responses; we want stronger commerce connections that can scale up to more rapidly. So, within that framework, one can’t expect banking and financial services to stay the same as it has been, because ultimately it has to shift. Artificial Intelligence is bubbling with a lot of energy at the moment, and so is Fintech. There has been a lot of investment going on in it, and it’s under so much spotlights. The rate of innovations and the abundance of new technologies have sprung up everywhere. Things from artificial intelligence, peer to peer lending, big data, block chain, crowd funding, digital payments, and Robo advisors, just to name a few. We need to think about FinTech with two capitals T’s that is, TECHNOLGY and TRANSPARENCY. It’s more about technology, enabling the banking industry to do the wonder, and Transparency because it’s a sector where customers can make much more informed choices. But what has made Fintech go so unmask is just the pace of innovations in this space. FinTech has now moved from prevention to resilience. We are just at the tip of the iceberg. Globally, the value of an investment in Fintech companies amounted to approximately 112 billion U.S. dollars in 2018, which was a record high for the sector. The annual value of global venture capital investment in Fintech companies is increasing and doubled between 2017 and 2018. This is an industry that is hungry for change because the consumers are hungry for change, and so the big corporations, the incumbents are also ready to change. Consumers want seamless, frictionless experiences. They want all the pain points removed from their banking journey. Table of Contents • Artificial Intelligence- Paving the Way for the Future in Banking - Embracing Conversational AI in Banking - Driving Personalization in Banking through Artificial Intelligence - AI-Model for Automated Credit-Scoring and Loan Processes - Transforming Wealth Management with AI - Utilizing Robotic Process Automation Software in Banking • In Conclusion Artificial Intelligence- Paving the Way for the Future in Banking Artificial Intelligence has the potential to revolutionize how consumers and businesses handle financial transactions. There will surely be hits and knocks along the way, but AI is not going away anytime soon. It is the future. FinTech companies want to deliver personalized and cost-effective finance products. To do so, they need to utilize large numbers of data from various touch-points. Introducing the financial sector with advanced techs like big data, artificial intelligence, and blockchaincan facilitate banking and finance go far beyond cashless payments and mobile services toward personalized customer experience that will transform FinTech in 2020. Financial institutions now know their customers' behavior and social browsing history. The accelerated rise of Artificial Intelligence and machine learning has resulted in banks being able to reduce the number of operations as they embrace the power of automation. Artificial Intelligence facilitates real-time omnichannel integration of these insights to deliver a personalized one-to-one marketing experience for their customers. AI’s potential can be looked at through versatile lenses in this sector, especially its implications and applicability across the operating landscape of banking. Learn more: https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/financial-services/deloitte-uk-world-economic-forum-artificial-intelligence-summary-report.pdf The three main channels where banks can use artificial intelligence to save on costs are front office (conversational banking), middle office (anti-fraud) and back office (underwriting). Let’s explore more on how banks can use Artificial Intelligence to constantly innovate at scale: Embracing Conversational AI in Banking An artificial intelligence feature that is redefining customer engagement is conversational AI. It has been viewed as a cost-effective way to interact with customers. Nowadays, conversational interfaces represent one of the biggest shifts in banking user interfaces to date and are modifying how they obtain and retain customers and enhance their brand identity. According to a study conducted by Juniper Research, chatbots can save at least 4 minutes of a customer service agent’s time. While saving 0.70 USD per query, in the process. Conversational AI has now become the preferred solution for productive customer communication among banks. The universality of messaging apps, like Facebook Messenger, WhatsApp, Slack, Microsoft Teams or SMS, and the adoption of voice-activated assistants such as Amazon Alexa, Google Home, or Apple’s Siri are bringing conversations back into our banking experiences. Conversational Banking Experience For example, the Swiss bank UBS partnered with tech giant Amazon to merge its “Ask UBS” service with Amazon Echo. Customers can communicate with multiple banking processes, via the chat interface, such as reporting potential fraud on their banking cards, applying for an increase on their credit card limit, or getting a breakdown of their recent transactions, and more. Driving Personalization in Banking through Artificial Intelligence Customers need banking on the go. They are looking for more personalized experience and expect to transact with banks from the convenience of wherever they are. Data advises that businesses that offer personalized services achieve far better business outcomes. Giving the right individual experience through the right channel at the right time can make banking more personalized. AI can play a significant role in assisting banks to understand customer behavior by leveraging transactional and other data sources. The Boston Consulting Group has estimated that a bank can garner as much as $300 million in revenue growth for every $100 billion it has in assets. All by personalizing its customer interactions. • Artificial Intelligence enables banks to customize financial products and services by adding personalized features and intuitive interactions to deliver meaningful customer engagement and build strong relationships with their customers. • Artificial Intelligence enables a higher degree of personalization and customization by tapping into information such as customer behavior, social interaction, and even health or important event dates, all to create a well-rounded picture of their customers’ profile. • AI can classify prospects based on financial capability, family size, etc. and offer tailored products. To carry out extensive personalization projects, banks are looking to collaborate. They’re now teaming up with fintech and software corporations to provide technological capabilities they do not maintain. In 2019, the total value of transactions in the personal finance segment will amount to $1,092,496 million according to Statista. Remarkably, the market’s largest segment is robo-advisors, with total assets under management of $980,541 million. In 2023, the number of people using robo-advisors is predicted to be 147 million. Organizations like Optimizely, Braze, and Crayon Data offer the financial sector the means to personalize the customer experience. Crayon’s proprietary AI-led recommendation engine, maya.ai, allows banks to create personalized digital experiences for their customers. All that with the help of machine learning algorithms. AI-Model for Automated Credit-Scoring and Loan Processes Artificial intelligence not only automates menial and repetitive tasks. It can be trained to take business decisions that normally require a specific level of cognitive thinking. Lending and credit scoring are the critical business for banks and directly or indirectly touches almost all parts of the economy. Banks always relied on models and experts to make effective credit decisions. Now models are becoming sophisticated enough to replace experts. Banks and credit scorers are employing machine learning models to track customers’ credit records. And make well-informed decisions on loan approvals. Banks and credit scorers are employing machine learning models to track customers’ credit records and data. And make well-informed decisions on loan approvals. The AI-based credit scoring model can score potential borrowers on their ‘creditworthiness’ by factoring in alternative data. The more data available about the borrower, the better you can assess their creditworthiness. This data could include candidates' social media/internet activity and websites visited and online purchases history. By examining the online behavior of a borrower, these models can predict the most credit-worthy candidates for loans. And also predict who is most likely to back out. In the new digital reality, AI-powered credit decision permits lenders to: • Fast and secure loan origination process • Automate borrower`s digital journey • Find and filter unfit borrowers based on sophisticated proprietary models powered by deep neural networks • Lessen the operational costs of origination • Authorize unhindered scalability of the lending business Transforming Wealth Management with AI Wealth managers are positively deploying artificial intelligence (AI) to answer the needs of a new generation of tech-savvy high net worth individuals. According to the 2018 Asia-Pacific Wealth Report (APWR) released by Capgemini, the APAC region witnessed a 12.1 percent growth in HNWI population in 2017, and a 14.8 percent rise in wealth, with the region, now forecast to exceed US$42 trillion by 2025. One of the AI trends in wealth management is the potential for the technology to move beyond traditional tasks, such as KYC and risk management, to new centers of enhancing relationship management and client experience. On the one hand, firms are investigating how they can make their relationship managers more productive. On the other, the new generation of clients wants predominant online services, assisting banks to examine how they can optimize their digital offerings. “Consumers’ and SME’s behavior and needs are changing fast,” said Rosali Steenkamer. There is an immense data explosion with structured and unstructured data. Only big data-driven models, Machine Learning algorithms and Artificial Intelligence can tackle this to serve the right solution to the right customer. Traditional technology is simply not able to deal with these challenges. -CCO and Co-Founder at AdviceRobo. Relationship Managers are not motivated to capture datasets. The only solution is to encourage the front office to collect new data, as well as collaborate with colleagues who develop AI-powered products and services. Doing this will drive productivity for Relationship Managers and an enriched experience for their end clients. Everyday tasks can be handled by AI systems, releasing wealth managers to concentrate on higher-level investment strategies. AI systems can also analyze client data to adequately create packages prepared for specific financial and social demographics. Utilizing AI in finance expands service offerings while also making them more customizable. With a variety of AI tools at their disposal, wealth managers are outfitted with the research and data insights essential to make quicker, more informed decisions for various clients. Learn more: https://capital.report/blogs/how-fintech-is-shaping-the-future-of-wealth-management/8244 Utilizing Robotic Process Automation Software in Banking This year robotic process automation (RPA) will continue to impact financial institutions, to help them be more efficient and effective, as well as help ensure they meet federal and state compliance requirements. RPA is growing rapidly. Recent RPA trends and forecasts anticipate that the market for robots in knowledge-work processes will reach $29 billion by 2021. For the banking industry, robotics outlines a unique and underutilized way to increase productivity while minimizing traditional repetitive and manual-labor-intensive processes. In Conclusion The accelerated rise of AI and machine learning has resulted in banks being able to reduce the number of operations as they embrace the power of automation. AI facilitates real-time omnichannel integration of these insights to deliver a personalized one-to-one marketing experience for their customers. So, when we look at these phases of development in the Banking Industry, we understand that it’s not just about inserting technology into banking; there is a larger shift here. Part of the shift is around trust and the utility of the bank. Artificial intelligence and machine learning technologies allows banks to turn vision into reality. Whether you are ready for it or not the AI revolution is poised to provide exciting avenues for innovations.

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Spotlight

Romulus Capital

Romulus Capital invests in early-stage technology companies that are looking to become industry leaders. We invest in brilliant – often first-time – entrepreneurs often affiliated with top universities and incubators; as a given company grows, our total investment can scale to $5M and beyond. We are focused on company-building, rather than betting, and we remain strong partners throughout the trajectory of growth. Our firm is youthful, entrepreneurial, and experienced, with a powerful investor base from around the world.

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