Leading banks eye APIs to leapfrog the competition

Leading | January 14, 2019

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The market for financial services is changing fast. To evolve, banks are transforming their organizations into digital ecosystems using APIs. APIs have emerged as critical enablers to help financial services firms meet new consumer expectations. Through collaboration with fin techs, banks will use APIs to add new functionality f

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WHY FINANCIAL INSTITUTIONS ARE ON CLOUD NINE POST-PANDEMIC

Article | June 4, 2021

Financial institutions have, for a while now, been operating in a highly cost challenged environment. These firms will continue walking the tight rope of executing on efficiency, digital transformation and supporting the business. Post-COVID when our dear planet begins to get back to some form of normality in the months ahead, it does not necessarily assume that wallets will be loser and further budget constraints are expected to be with us for some time. As we know the Genie is out of the bottle on the whole “agile” working theory and the Cloud providers have responded in kind such as providing virtual desktops and VPN solutions. Of course not forgetting the Video calling enablement which has coined a phrase never to leave our vocabulary “sorry I was on mute”. Cost pressures aside businesses are already reassessing the effectiveness of their technology stacks. I believe we will see an acceleration of an already giddy pace by firms to move parts of their estate and applications to the public cloud. It is not only essential from a practical basis covering the usual themes of cost, storage planning on demand compute etc but if you want to retain the best talent in technology you need to be exposing them to the likes of AWS, GCP and Azure in some form. Data is the new oil As to my world in data various analogies “data is the new oil” etc, but getting beyond the taglines the public cloud is shaking up the status quo. From off-the-shelf Amazon style access to data products via a web store or to throw in another term “supermarket”. Fundamentally the barrier to entry for clients to access data, storage and enormous compute resource is really down to what you can afford. Efficiencies on compute, serverless technologies pay for what you use not pay for standby is changing the paradigm in architecture. Thereby pushing boundaries in innovation, experimentation and exposing teams to AI/ML as a utility as opposed to things you read about in journals or online. No two businesses are the same which is why certain firms are further in the journey than others. But regardless of the path financial institutions decide to go down, it does not change the fact that data needs to be delivered to the right place, at the right time, and in a preferred format. Some firms will simply want their channel partners to ship data into the cloud as an end point. From Satellites to the Cloud This leads me into my next comparison. I was lucky enough (or unlucky) to be there when the internet created another paradigm shift as a delivery end point for data. Prior to that I spent many years plugging firms into Satellites or Leased lines for the delivery of Market Data. As a younger man I thought those days would never end! If the internet became the end point that people used to get data into their own network, then the cloud to a certain extent is the modern day equivalent. After all, if firms want to use cloud as an end point into a physical data centre or on-premise, they can do that. Alternatively, if the firm wants to use the data exclusively within the cloud, then that is also achievable in this day and age.

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HOW OPEN BANKING IS CATALYZING PAYMENTS CHANGE

Article | March 30, 2020

Since the adoption of PSD2 by the European Parliament in 2015, there’s been growing momentum behind Open Banking. This is set to reach new levels in 2020, as Open Banking catalyzes innovation and efficiency across the world of payments. That makes it one of the most important trends in the industry right now. Open Banking regulations require banks to open up their systems and data to third-party providers. This is causing banks to reinvent their payments business models and build ecosystems of services

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Will fintech change everyday lives in Africa and Asia?

Article | March 19, 2020

The modern world is constantly changing, offering more to societies across the globe than before. The recent technological development has proven to be unprecedented and revolutionary, changing the lives of millions in different corners of the world. The financial industry is one of the most affected sectors that is experiencing a major transformation due to a number of different factors. As a result, we now witness a diverse range of services in forms never seen before.

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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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Mercer Bradley

Mercer Bradley offers specialized recruitment of all levels of accounting professionals for preferred employers on a direct hire or temporary basis.

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