Southeast Asia’s banking sector is poised for significant digital transformation. With projected Net Interest Income reaching USD 148 billion by 2024, the market is ripe for continued growth. While traditional banks still hold a dominant position, digital players are making significant inroads. To thrive in this evolving landscape, financial institutions must adapt to rising customer expectations, stringent regulations, and the imperative for resilience. This will require a seamless collaboration between technology and business teams.
To uncover how banks in Southeast Asia are navigating this complex landscape and what it takes to succeed, Ecosystm engaged in in-depth conversations with senior banking executives and technology leaders as part of our research initiatives. Here are the highlights of the discussions with leaders across the region.
#1 Achieving Hyper-Personalisation Through AI
As banks strive to deliver highly personalised financial services, AI-driven models are becoming increasingly essential. These models analyse customer behaviour to anticipate needs, predict future behaviour, and offer relevant services at the right time. AI-powered tools like chatbots and virtual assistants further enhance real-time customer support.
Hyper-personalisation, while promising, comes with its challenges – particularly around data privacy and security. To deliver deeply tailored services, banks must collect extensive customer information, which raises the question: how can they ensure this sensitive data remains protected?
AI projects require a delicate balance between innovation and regulatory compliance. Regulations often serve as the right set of guardrails within which banks can innovate. However, banks – especially those with cross-border operations – must establish internal guidelines that consider the regulatory landscape of multiple jurisdictions.
#2 Beyond AI: Other Emerging Technologies
AI isn’t the only emerging technology reshaping Southeast Asian banking. Banks are increasingly adopting technologies like Robotic Process Automation (RPA) and blockchain to boost efficiency and engagement. RPA is automating repetitive tasks, such as data entry and compliance checks, freeing up staff for higher-value work. CIMB in Malaysia reports seeing a 35-50% productivity increase thanks to RPA. Blockchain is being explored for secure, transparent transactions, especially cross-border payments. The Asian Development Bank successfully trialled blockchain for faster, safer bond settlements. While AR and VR are still emerging in banking, they offer potential for enhanced customer engagement. Banks are experimenting with immersive experiences like virtual branch visits and interactive financial education tools.
The convergence of these emerging technologies will drive innovation and meet the rising demand for seamless, secure, and personalised banking services in the digital age. This is particularly true for banks that have the foresight to future-proof their tech foundation as part of their ongoing modernisation efforts. Emerging technologies offer exciting opportunities to enhance customer engagement, but they shouldn’t be used merely as marketing gimmicks. The focus must be on delivering tangible benefits that improve customer outcomes.
#3 Greater Banking-Fintech Collaboration
The digital payments landscape in Southeast Asia is experiencing rapid growth, with a projected 10% increase between 2024-2028. Digital wallets and contactless payments are becoming the norm, and platforms like GrabPay, GoPay, and ShopeePay are dominating the market. These platforms not only offer convenience but also enhance financial inclusion by reaching underbanked populations in remote areas.
The rise of digital payments has significantly impacted traditional banks. To remain relevant in this increasingly cashless society, banks are collaborating with fintech companies to integrate digital payment solutions into their services. For instance, Indonesia’s Bank Mandiri collaborated with digital credit services provider Kredivo to provide customers with access to affordable and convenient credit options.
Partnerships between traditional banks and fintechs are essential for staying competitive in the digital age, especially in areas like digital payments, data analytics, and customer experience.
While these collaborations offer opportunities, they also pose challenges. Banks must invest in advanced fraud detection, AI monitoring, and robust authentication to secure digital payments. Once banks adopt a mindset of collaboration with innovators, they can leverage numerous innovations in the cybersecurity space to address these challenges.
#4 Agile Infrastructure for an Agile Business
While the banking industry is considered a pioneer in implementing digital technologies, its approach to cloud has been more cautious. While interest remained high, balancing security and regulatory concerns with cloud agility impacted the pace. Hybrid multi-cloud environments has accelerated banking cloud adoption.
Leveraging public and private clouds optimises IT costs, offering flexibility and scalability for changing business needs. Hybrid cloud allows resource adjustments for peak demand or cost reductions off-peak. Access to cloud-native services accelerates innovation, enabling rapid application development and improved competitiveness. As the industry adopts GenAI, it requires infrastructure capable of handling vast data, massive computing power, advanced security, and rapid scalability – all strengths of hybrid cloud.
Replicating critical applications and data across multiple locations ensures disaster recovery and business continuity. A multi-cloud strategy also helps avoid vendor lock-in, diversifies cloud providers, and reduces exposure to outages.
Hybrid cloud adoption offers benefits but also presents challenges for banks. Managing the environment is complex, needing coordination across platforms and skilled personnel. Ensuring data security and compliance across on-prem and public cloud infrastructure is demanding, requiring robust measures. Network latency and performance issues can arise, making careful design and optimisation crucial. Integrating on-prem systems with public cloud services is time-consuming and needs investment in tools and expertise.
#5 Cyber Measures to Promote Customer & Stakeholder Trust
The banking sector is undergoing rapid AI-driven digital transformation, focusing on areas like digital customer experiences, fraud detection, and risk assessment. However, this shift also increases cybersecurity risks, with the majority of banking technology leaders anticipate inevitable data breaches and outages.
Key challenges include expanding technology use, such as cloud adoption and AI integration, and employee-related vulnerabilities like phishing. Banks in Southeast Asia are investing heavily in modernising infrastructure, software, and cybersecurity.
Banks must update cybersecurity strategies to detect threats early, minimise damage, and prevent lateral movement within networks.
Employee training, clear security policies, and a culture of security consciousness are critical in preventing breaches.
Regulatory compliance remains a significant concern, but banks are encouraged to move beyond compliance checklists and adopt risk-based, intelligence-led strategies. AI will play a key role in automating compliance and enhancing Security Operations Centres (SOCs), allowing for faster threat detection and response. Ultimately, the BFSI sector must prioritise cybersecurity continuously based on risk, rather than solely on regulatory demands.
Breaking Down Barriers: The Role of Collaboration in Banking Transformation
Successful banking transformation hinges on a seamless collaboration between technology and business teams. By aligning strategies, fostering open communication, and encouraging cross-functional cooperation, banks can effectively leverage emerging technologies to drive innovation, enhance customer experience, and improve efficiency.
A prime example of the power of collaboration is the success of AI initiatives in addressing specific business challenges.
This user-centric approach ensures that technology addresses real business needs.
By fostering a culture of collaboration, banks can promote continuous learning, idea sharing, and innovation, ultimately driving successful transformation and long-term growth in the competitive digital landscape.
Over a century ago, the advent of commercial flights marked a pivotal moment in globalisation, shrinking the time-distance between cities and nations. Less than a century later, the first video call foreshadowed a future where conversations could span continents in real time, compressing the space-distance between people.
The world feels smaller, not literally, but in how we experience space and time. Messages that once took days to deliver arrive instantly. Distances between cities are now measured in hours, not miles. A product designed in New York is manufactured in Shenzhen and reaches London shelves within weeks. In essence, things traverse the world with far less friction than it once did.
Welcome to The Immediate Economy!
The gap between desire and fulfilment has narrowed, driven by technology’s speed and convenience. This time-space annihilation has ushered in what we now call The Immediate Economy.
Such transformations haven’t gone unnoticed, at the click of a button is now a native (sort of cliché) expression. Amidst all this innovation, a new type of consumer has emerged – one whose attention is fleeting and easy to lose. Modern consumers have compelled industries, especially retail and ecommerce, to evolve, creating experiences that not only capture but also hold their interest.
Beyond Usability: Crafting a Memorable User Experience
Selling a product is no longer about just the product itself; it’s about the lifestyle, the experience, and the rush of dopamine with every interaction. And it’s all because of technology.
In a podcast interview with the American Psychological Association, Professor Gloria Mark from the University of California, Irvine, revealed a significant decline in attention spans on screens, from 150 seconds in 2004 to 40 seconds in the last five years. Social media platforms have spoiled the modern consumer by curating content that caters instantly to desires. Influence spills into the retail sector, compelling retailers to create experiences matching the immediacy and personalisation people now expect.
Modern consumers require modern retail experiences. Take Whole Foods, and their recent partnership with Amazon’s Dash Cart, transforming the mundane act of grocery shopping into a seamless dance of efficiency. Shoppers can now glide through aisles with carts that tally selections and debit totals directly from their accounts, rendering checkout lines obsolete. It’s more than convenience; it reimagines retail – a choreography of consumerism where every step is both effortless and calculated.
Whole Foods can analyse data from their Dash Cart technology to gain valuable insights into shopping patterns. The Immediate Economy revolutionises retail, transforming it into a hyper-efficient, personalised experience.
Retail’s new Reality: The Rise of Experiential Shopping
Just as Netflix queues up a binge-worthy series; retailers create shopping experiences as engaging and addictive as your favourite shows.
It’s been a financially rough year for Nike, but that hasn’t stopped them from expanding their immersive retail experience. Nike’s “House of Innovation” leverages 3D holographic tech. Customers can inspect intricate details of sneakers, including the texture of the fabric, the design of the laces, and the construction of the sole. The holographic display can also adjust to different lighting conditions and present the sneaker in various colours, providing a truly immersive and personalised shopping experience.
Fashion commerce platforms like Farfetch are among many integrating Virtual Try-On (VTO) technology. Leveraging the camera and sensors of customer devices, their AR technology overlays a digital image of a handbag onto a live view of a customer, enabling them to see how different styles and sizes would look on you. This approach to ecommerce enhances experiences, elevating interaction.
The 3D holographic display and the AR tech, are unique and visually appealing ways to showcase products, allowing customers to interact with products in a way that is not possible with traditional displays. Each shopping trip feels like the next episode of retail therapy.
The Evolution of Shopptertainment
The bar for quick content consumption is higher than ever thanks to platforms like TikTok and Instagram.
A prime example of this trend is Styl, a tech startup from two Duke students, with their “Tinder for shopping” application. Styl offers a swipeable interface for discovering and purchasing fashion items, seamlessly integrating the convenience and engagement of social media into the retail experience.
Styl goes beyond a simple swipe. By leveraging AI algorithms, it learns your preferences and curates a personalised feed of clothing items that align with your taste. Streamlining the shopping process, they deliver a tailored experience that caters to the modern consumer’s desire for convenience and personalisation.
Interestingly, Styl isn’t even a retail company; it pools items from websites, redirecting the users with relevant interest. They combine ecommerce with AI, creating the ultimate shopping experience for today’s customer. It’s fast, customised, and changing the way we shop.
Styl is not the first ones to do this, Instagram and TikTok provide individualised suggestions within their marketplace. But they differ by selling an experience, a vibe. That’s what sets them apart.
Tech-Powered Retail: The Heart of the Immediate Economy
History is filled with examples of societal innovation, but the Immediate Economy is transforming retail in exciting ways. In the 21st century, technology is both the catalyst and the consequence of the retail industry transformation. It began by capturing and fragmenting the average consumer’s attention, and now it’s reshaping consumer-brand relationships.
Today’s consumers crave personalised shopping. Whole Foods, with its AI-driven Dash Carts, is redefining convenience. Nike and Farfetch, through immersive AR and 3D tech, is making shopping an interactive adventure. Meanwhile, startups like Styl are leveraging AI to bring personalized fashion choices directly to consumers’ smartphones. The world is shrinking, not just in miles, but in the milliseconds it takes to satisfy a desire. From the aisles of Whole Foods to the virtual showrooms of Farfetch, The Immediate Economy offers an immersive world, where time and space bend to technology’s will, and instant gratification is no longer a perk; it’s an expectation. The Immediate Economy is here, and it’s changing how we interact with the world around us. Welcome to the future of retail, and everything else.
Innovation is a driving force behind new approaches, often occurring at the point of adoption rather than technology development. As public sector organisations increasingly focus on improving citizen services through technology, it is important to adopt a strategic approach that considers innovation as a complex journey of systemic and cultural transformation. This strategic approach should guide the integration of technology into citizen services.
Here is a comprehensive look at what public sector organisations should consider when integrating technology into citizen services.
Download ‘Future-Proofing Citizen Services: Technology Strategies for the Public Sector‘ as a PDF
1. Immediate View: Foundational Technologies
The immediate view focuses on deploying technologies that are widely adopted and essential for current digital service provision. These foundational technologies serve as the backbone for enhancing citizen services.
Foundational Technologies
Web 2.0. Establishing a solid online presence is usually the first step, as it is the broadest channel for reaching customers. Web 2.0 refers to the current state of the internet, encompassing dynamic content and interactive websites.
Mobile Applications. Given that mobile usage has surpassed desktop, a mobile-responsive platform or a dedicated mobile app is crucial. Mobile apps provide a more specialised and immersive user experience by utilising device-specific features like GPS, document scanning, and push notifications.
2. Second-Generation Enablers: Emerging Technologies
As organisations establish foundational technologies, they should look towards second-generation enablers. Although less mature, these technologies offer emerging digital opportunities, and can significantly enhance service differentiation.
Emerging Technologies
Interactive Voice Response (IVR) systems improve the efficiency and effectiveness of digital services by routing callers to self-service options and providing relevant information without human intervention. These systems operate outside typical government agency working hours, ensuring continuous accessibility. Additionally, IVRs generate valuable data for future Voice of the Customer programs, improving overall service quality and responsiveness.
Digital Wallets facilitate transactions by expediting fund transfers and enhancing transparency through meticulous transaction records. They streamline administrative tasks, simplify transactions, and encourage service usage and adoption.
AI-driven Virtual Agents or chatbots revolutionise customer interactions by providing 24/7 support. They offer prompt, efficient, and personalised services, enhancing customer satisfaction and trust. In resource-limited public sectors, virtual agents are cost-effective, optimising resource allocation and meeting growing service demands. Specialised virtual agents for specific sectors can further differentiate service providers.
3. Futuristic View: Ambitious Innovations
The futuristic view focuses on forward-looking technologies that address long-term roadblocks and offer transformative potential. These technologies are currently speculative but hold the promise of significantly reshaping the market.
Innovations
Subscription Management models enable public sector information services to be accessed in highly personalised ways, thereby enhancing citizen engagement. This model supports regulatory oversight by providing common data insights and improves the management of services, ultimately benefiting the public by ensuring more responsive and tailored information delivery.
AI concierge leverages advanced technologies like Natural Language Processing, Computer Vision, and Speech Technologies to provide personalised and proactive customer service. They redefine customer management, ensuring a seamless and tailored experience.
Immersive reality technologies, such as augmented and virtual reality (AR/VR) create captivating customer experiences by allowing interactions in virtual environments. These technologies establish a shared virtual environment, helping customers to engage with businesses and each other in new and immersive ways. As an emerging customer management tool, immersive reality can transform the dynamics of customer-business relationships, adding substantial value to the service experience.
Governments worldwide struggle with intricate social, economic, and environmental challenges. Tight budgets often leave them with limited resources to address these issues head-on. However, innovation offers a powerful path forward.
By embracing new technologies, adapting to cultural shifts, and fostering new skills, structures, and communication methods, governments can find solutions within existing constraints.
Find out how public sector innovation is optimising internal operations, improving service accessibility, bridging the financial gap, transforming healthcare, and building a sustainable future.
Click here to download ‘Innovation in Government: Social, Economic, and Environmental Wins’ as a PDF
Optimising Operations: Tech-Driven Efficiency
Technology is transforming how governments operate, boosting efficiency and allowing employees to focus on core functions.
Here are some real-world examples.
Singapore Streamlines Public Buses. A cloud-based fleet management system by the Land Transport Authority (LTA) improves efficiency, real-time tracking, data analysis, and the transition to electric buses.
Dubai Optimises Utilities Through AI. The Dubai Electricity and Water Authority (DEWA) leverages AI for predictive maintenance, demand forecasting, and grid management. This enhances service reliability, operational efficiency, and resource allocation for power and water utilities.
Automation Boosts Hospital Efficiency. Singapore hospitals are using automation to save man-hours and boost efficiency. Tan Tock Seng Hospital automates bacteria sample processing, increasing productivity without extra staff, while Singapore General Hospital tracks surgical instruments digitally, saving thousands of man-hours.
Tech for Citizens
Digital tools and emerging technologies hold immense potential to improve service accessibility and delivery for citizens. Here’s how governments are leveraging tech to benefit their communities.
Faster Cross-Border Travel. Malaysia’s pilot QR code clearance system expedites travel for factory workers commuting to Singapore, reducing congestion at checkpoints.
Metaverse City Planning. South Korea’s “Metaverse 120 Center” allows residents to interact with virtual officials and access services in a digital environment, fostering innovative urban planning and infrastructure management.
Streamlined Benefits. UK’s HM Revenue and Customs (HMRC) launched an online child benefit claim system that reduces processing time from weeks to days, showcasing the efficiency gains possible through digital government services.
Bridging the Financial Gap
Nearly 1.7 billion adults or one-third globally, remain unbanked.
However, innovative programs are bridging this gap and promoting financial inclusion.
Thailand’s Digital Wallet. Aimed at stimulating the economy and empowering underserved citizens, Thailand disburses USD 275 via digital wallets to 50 million low-income adults, fostering financial participation.
Ghana’s Digital Success Story. The first African nation to achieve 100% financial inclusion through modernised platforms like Ghana.gov and GhanaPay, which facilitate payments and fee collection through various digital channels.
Philippines Embraces QR Payments. The City of Alaminos leverages the Paleng-QR Ph Plus program to promote QR code-based payments, aligning with the central bank’s goal of onboarding 70% of Filipinos into the formal financial system by 2024.
Building a Sustainable Future
Governments around the world are increasingly turning to technology to address environmental challenges and preserve natural capital.
Here are some inspiring examples.
World’s Largest Carbon Capture Plant. Singapore and UCLA joined forces to build Equatic-1, a groundbreaking facility that removes CO2 from the ocean and creates carbon-negative hydrogen.
Tech-Enhanced Disaster Preparedness. The UK’s Lincolnshire County Council uses cutting-edge geospatial technology like drones and digital twins. This empowers the Lincolnshire Resilience Forum with real-time data and insights to effectively manage risks like floods and power outages across their vast region.
Smart Cities for Sustainability. Bologna, Italy leverages the digital twins of its city to optimise urban mobility and combat climate change. By analysing sensor data and incorporating social factors, the city is strategically developing infrastructure for cyclists and trams.
Tech for a Healthier Tomorrow
Technology is transforming healthcare delivery, promoting improved health and fitness monitoring.
Here’s a glimpse into how innovation is impacting patient care worldwide.
Robotic Companions for Seniors. South Korea tackles elder care challenges with robots. Companion robots and safety devices provide companionship and support for seniors living alone.
VR Therapy for Mental Wellness. The UAE’s Emirates Health Services Corporation implements a Virtual Reality Lab for Mental Health, that creates interactive therapy sessions for individuals with various psychological challenges. VR allows for personalised treatment plans based on data collected during sessions.
Healthcare delivery and healthtech have made significant strides; yet, the fundamental challenges in healthcare have remained largely unchanged for decades. The widespread acceptance and integration of digital solutions in recent years have supported healthcare providers’ primary goals of enhancing operational efficiency, better resource utilisation (with addressing skill shortages being a key driver), improving patient experience, and achieving better clinical outcomes. With governments pushing for advancements in healthcare outcomes at sustainable costs, the concept of value-based healthcare has gained traction across the industry.
Technology-driven Disruption
Healthcare saw significant disruptions four years ago, and while we will continue to feel the impact for the next decade, one positive outcome was witnessing the industry’s ability to transform amid such immense pressure. I am definitely not suggesting another healthcare calamity! But disruptions can have a positive impact – and I believe that technology will continue to disrupt healthcare at pace. Recently, my colleague Tim Sheedy shared his thoughts on how 2024 is poised to become the year of the AI startup, highlighting innovative options that organisations should consider in their AI journeys. AI startups and innovators hold the potential to further the “good disruption” that will transform healthcare.
Of course, there are challenges associated, including concerns on ethical and privacy-related issues, the reliability of technology – particularly while scaling – and on professional liability. However, the industry cannot overlook the substantial number of innovative startups that are using AI technologies to address some of the most pressing challenges in the healthcare industry.
Why Now?
AI is not new to healthcare. Many would cite the development of MYCIN – an early AI program aimed at identifying treatments for blood infections – as the first known example. It did kindle interest in research in AI and even during the 1980s and 1990s, AI brought about early healthcare breakthroughs, including faster data collection and processing, enhanced precision in surgical procedures, and research and mapping of diseases.
Now, healthcare is at an AI inflection point due to a convergence of three significant factors.
- Advanced AI. AI algorithms and capabilities have become more sophisticated, enabling them to handle complex healthcare data and tasks with greater accuracy and efficiency.
- Demand for Accessible Healthcare. Healthcare systems globally are striving for better care amid resource constraints, turning to AI for efficiency, cost reduction, and broader access.
- Consumer Demand. As people seek greater control over their health, personalised care has become essential. AI can analyse vast patient data to identify health risks and customise care plans, promoting preventative healthcare.
Promising Health AI Startups
As innovative startups continue to emerge in healthcare, we’re particularly keeping an eye on those poised to revolutionise diagnostics, care delivery, and wellness management. Here are some examples.
DIAGNOSTICS
- Claritas HealthTech has created advanced image enhancement software to address challenges in interpreting unclear medical images, improving image clarity and precision. A cloud-based platform with AI diagnostic tools uses their image enhancement technology to achieve greater predictive accuracy.
- Ibex offers Galen, a clinical-grade, multi-tissue platform to detect and grade cancers, that integrate with third-party digital pathology software solutions, scanning platforms, and laboratory information systems.
- MEDICAL IP is focused on advancing medical imaging analysis through AI and 3D technologies (such as 3D printing, CAD/CAM, AR/VR) to streamline medical processes, minimising time and costs while enhancing patient comfort.
- Verge Genomics is a biopharmaceutical startup employing systems biology to expedite the development of life-saving treatments for neurodegenerative diseases. By leveraging patient genomes, gene expression, and epigenomics, the platform identifies new therapeutic gene targets, forecasts effective medications, and categorises patient groups for enhanced clinical efficacy.
- X-Zell focuses on advanced cytology, diagnosing diseases through single atypical cells or clusters. Their plug-and-play solution detects, visualises, and digitises these phenomena in minimally invasive body fluids. With no complex specimen preparation required, it slashes the average sample-to-diagnosis time from 48 hours to under 4 hours.
CARE DELIVERY
- Abridge specialises in automating clinical notes and medical discussions for physicians, converting patient-clinician conversations into structured clinical notes in real time, powered by GenAI. It integrates seamlessly with EMRs such as Epic.
- Waltz Health offers AI-driven marketplaces aimed at reducing costs and innovative consumer tools to facilitate informed care decisions. Tailored for payers, pharmacies, and consumers, they introduce a fresh approach to pricing and reimbursing prescriptions that allows consumers to purchase medication at the most competitive rates, improving accessibility.
- Acorai offers a non-invasive intracardiac pressure monitoring device for heart failure management, aimed at reducing hospitalisations and readmissions. The technology can analyse acoustics, vibratory, and waveform data using ML to monitor intracardiac pressures.
WELLNESS MANAGEMENT
- Anya offers AI-driven support for women navigating life stages such as fertility, pregnancy, parenthood, and menopause. For eg. it provides support during the critical first 1,001 days of the parental journey, with personalised advice, tracking of developmental milestones, and connections with healthcare professionals.
- Dacadoo’s digital health engagement platform aims to motivate users to adopt healthier lifestyles through gamification, social connectivity, and personalised feedback. By analysing user health data, AI algorithms provide tailored insights, goal-setting suggestions, and challenges.
Conclusion
There is no question that innovative startups can solve many challenges for the healthcare industry. But startups flourish because of a supportive ecosystem. The health innovation ecosystem needs to be a dynamic network of stakeholders committed to transforming the industry and health outcomes – and this includes healthcare providers, researchers, tech companies, startups, policymakers, and patients. Together we can achieve the longstanding promise of accessible, cost-effective, and patient-centric healthcare.
The first impact of the pandemic and the disruption it caused, was organisations scrambling to empower their remote employees. Over the last 2 years, significant investments have been made on collaboration platforms and tools. Now organisations are having to work towards making these workplaces truly hybrid where organisations have to ensure that all employees get the same experience, irrespective of where they choose to work from.
In 2022, organisations will continue to invest in building the Digital Workplace and address the associated technology, people, and process challenges.
Read on to find out what Ecosystm Analysts, Audrey William, Tim Sheedy and Venu Reddy think will be the key trends for the Digital Workplace in 2022.
Click here to download Ecosystm Predicts: The Top 5 Trends for the Digital Workplace in 2022 as PDF
In this Insight, guest author Anupam Verma talks about how a smart combination of technologies such as IoT, edge computing and AI/machine learning can be a game changer for the Financial Services industry. “With the rise in the number of IoT devices and increasing financial access, edge computing will find its place in the sun and complement (and not compete) with cloud computing.”
The number of IoT devices have now crossed the population of planet earth. The buzz around the Internet of Things (IoT) refuses to go down and many believe that with 5G rollouts and edge computing, the adoption will rise exponentially in the next 5 years.
The IoT is described as the network of physical objects (“things”) embedded with sensors and software to connect and exchange data with other devices over the internet. Edge computing allows IoT devices to process data near the source of generation and consumption. This could be in the device itself (e.g. sensors), or close to the device in a small data centre. Typically, edge computing is advantageous for mission-critical applications which require near real-time decision making and low latency. Other benefits include improved data security by avoiding the risk of interception of data in transfer channels, less network traffic and lower cost. Edge computing provides an alternative to sending data to a centralised cloud.
In the 5G era, a smart combination of technologies such as IoT, edge computing and AI/machine learning will be a game changer. Multiple uses cases from self-driving vehicles to remote monitoring and maintenance of machinery are being discussed. How do we see IoT and the Edge transforming Financial Services?
Before we go into how these technologies can transforming the industry, let us look at current levels of perception and adoption (Figure 1).
There is definitely a need for greater awareness of the capabilities and limitations of these emerging technologies in the Financial Services.
Transformation of Financial Services
The BFSI sector is increasingly moving away from selling a product to creating a seamless customer journey. Financial transactions, whether it is payment, transfer of money, or a loan can be invisible, and Edge computing will augment the customer experience. This cannot be achieved without having real-time data and analytics to create an updated 360-degree profile of the customer at all times. This data could come from multiple IoT devices, channels and partners that can interface and interact with the customer. A lot of use cases around personalisation would not be possible without edge computing. The Edge here would mean faster processing and smoother experience leading to customer delight and a higher trust quotient.
With IoT, customers can bank anywhere anytime using connected devices like wearables (smartwatches, fitness trackers etc). People can access account details, contextual offers at their current location or make payments without even needing a smartphone.
Use Cases of IoT & Edge in Financial Services
IT and Digital Leaders in Financial Services are aware of the benefits of IoT and there are some use cases that most of them think will help transform Financial Services (Figure 2).
However, there are many more potential use cases. Here are some use cases whose volume will only grow every day to fuel incessant data generation, consumption and processing at the Edge.
- Smart Homes. IoT devices like Alexa/Google Home have capabilities to become “bank in a speaker” with edge computing.
- In-Sync Omnichannels. IoT devices can be synced with other banking channels. A customer may start a transaction on an IoT device and complete it in a branch. Facial recognition can be used to identify the customer after he/she walks in and synced IoT devices will ensure that the transaction is completed without any steps repeated (zero re-work) thereby enhancing customer satisfaction.
- Virtual Relationship Managers. In a digital branch, the customer may use Virtual Reality (VR) headsets to engage with virtual relationship managers and relevant experts. Gamification using VR can be amazingly effective in the area of financial literacy and financial planning.
- Home and Auto Purchase. VR may also find use in home and auto purchase processes with financing built into it. The entire customer journey will have a much smoother experience with edge computing.
- Auto and Health Insurance. Companies can use IoT (device installed in the vehicle) plus edge computing to monitor and improve driving behaviour, eventually rewarding safety with lower premiums. The growth in electric mobility will continue to provide the basis for auto insurance. Companies can use wearables to monitor crucial health parameters and exercising habits. The creation of real-time dynamic rewards around it can change behaviour towards a healthier lifestyle. Awareness, longevity, rising costs and pandemic will only fuel this sector’s growth.
- Payments. Device to device contactless payment protocol is picking up and IoT and edge computing can create next-gen revolution in payments. Your EV could have an embedded wallet and pay for its parking and toll.
- Branch/ATM. IoT sensors and CCTV footage from branches/ATMs can be utilised in real-time to improve branch productivity as well as customer engagement, at the same time enhancing security. It could also help in other situations like low cash levels in ATMs and malfunctions. Sending live video streams for video analytics to the cloud can be expensive. By processing data within the device or on-premises, the Edge can help lower costs and reduce latency.
- Trading in Securities. Another area where response time matters is algorithmic trading. Edge computing will help to quickly process and analyse a large amount of data streaming real-time from multiple feeds and react appropriately.
- Trade Finance. Real-time tracking of goods may add a different dimension to the risk, pricing and transparency of supply chains.
Cloud vs Edge
The decision to use cloud or edge will depend on multiple considerations. At the same time, all the data from IoT devices need not go to the cloud for processing and choke network bandwidth. In fact, some of this data need not be stored forever (like video feeds etc). As a result, with the rise in the number of IoT devices and increasing financial access, edge computing will find its place in the sun and complement (and not compete) with cloud computing.
The views and opinions mentioned in the article are personal.
Anupam Verma is part of the Leadership team at ICICI Bank and his responsibilities have included leading the Bank’s strategy in South East Asia to play a significant role in capturing Investment, NRI remittance, and trade flows between SEA and India.
It is true that the Retail industry is being forced to evolve the experiences they deliver to their customers. However, if Retail organisations are only focused on creating digital experiences, they are not creating the differentiation that will be required to leap ahead of the competition.
It is time for Retail organisations to leverage data to empower multiple roles across the organisation to prepare for the different ways customers want to engage with their brands.
So what are the phases of customer engagement? How are companies such as Singapore Airlines and TikTok preparing for the future of Retail?
Last week I wrote about the need to remove hype from reality when it comes to AI. But what will ensure that your AI projects succeed?
It is quite obvious that success is determined by human aspects rather than technological factors. We have identified four key organisational actions that enable successful AI implementation at scale (Figure 1).
#1 Establish a Data Culture
The traditional focus for companies has been on ensuring access to good, clean data sets and the proper use of that data. Ecosystm research shows that only 28% of organisations focused on customer service, also focus on creating a data-driven organisational culture. But our experience has shown that culture is more critical than having the data. Does the organisation have a culture of using data to drive decisions? Does every level of the organisation understand and use data insights to do their day-to-day jobs? Is decision-making data-driven and decentralised, needing to be escalated only when there is ambiguity or need for strategic clarity? Do business teams push for new data sources when they are not able to get the insights they need?
Without this kind of culture, it may be possible to implement individual pieces of automation in a specific area or process, applying brute force to see it through. In order to transform the business and truly extract the power of AI, we advise organisations to build a culture of data-driven decision-making first. That organisational mindset, will make you capable implementing AI at scale. Focusing on changing the organisational culture will deliver greater returns than trying to implement piecemeal AI projects – even in the short to mid-term.
#2 Ingrain a Digital-First Mindset
Assuming a firm has passed the data culture hurdle, it needs to consider whether it has adopted a digital-first mindset. AI is one of many technologies that impact businesses, along with AR/VR, IoT, 5G, cloud and Blockchain to name a few. Today’s environment requires firms to be capable of utilising a variety of these technologies – often together – and possessing a workforce capable of using these digital tools.
A workforce with the digital-first mindset looks for a digital solution to problems wherever appropriate. They have a good understanding of digital technologies relevant to their space and understand key digital methodologies – such as Customer 360 to deliver a truly superior customer experience or Agile methodologies to successfully manage AI at scale.
AI needs business managers at the operational levels to work with IT or AI tech teams to pinpoint processes that are right for AI. They need to make an estimation based on historical data of what specific problems require an AI solution. This is enabled by the digital-first mindset.
#3 Demystify AI
The next step is to get business leaders, functional leaders, and business operational teams – not just those who work with AI – to acquire a basic understanding of AI.
They do not need to learn the intricacies of programming or how to create neural networks or anything nearly as technical in nature. However, all levels from the leadership down should have a solid understanding of what AI can do, the basics of how it works, how the process of training data results in improved outcomes and so on. They need to understand the continuous learning nature of AI solutions, getting better over time. While AI tools may recommend an answer, human insight is often needed to make a correct decision off this recommendation.
#4 Drive Implementation Bottom-Up
AI projects need alignment, objectives, strategy – and leadership and executive buy-in. But a very important aspect of an AI-driven organisation that is able to build scalable AI, is letting projects run bottom up.
As an example, a reputed Life Sciences company embarked on a multi-year AI project to improve productivity. They wanted to use NLP, Discovery, Cognitive Assist and ML to augment clinical proficiency of doctors and expected significant benefits in drug discovery and clinical trials by leveraging the immense dataset that was built over the last 20 years.
The company ran this like any other transformation project, with a central program management team taking the lead with the help of an AI Centre of Competency. These two teams developed a compelling business case, and identified initial pilots aligned with the long-term objectives of the program. However, after 18 months, they had very few tangible outcomes. Everyone including doctors, research scientists, technicians, and administrators, who participated in the program had their own interpretation of what AI was not able to do.
Discussion revealed that the doctors and researchers felt that they were training AI to replace themselves. Seeing a tool trying to mimic the same access and understanding of numerous documents baffled them at best. They were not ready to work with AI programs step-by-step to help AI tools learn and discover new insights.
At this point, we suggested approaching the project bottom-up – wherein the participating teams would decide specific projects to take up. This developed a culture where teams collaborated as well as competed with each other, to find new ways to use AI. Employees were shown a roadmap of how their jobs would be enhanced by offloading routine decisions to AI. They were shown that AI tools augment the employees’ cognitive capabilities and made them more effective.
The team working on critical trials found these tools extremely useful and were able to collaborate with other organisations specialising in similar trials. They created the metadata and used ML algorithms to discover new insights. Working bottom-up led to a very successful AI deployment.
We have seen time and again that while leadership may set the strategy and objectives, it is best to let the teams work bottom-up to come up with the projects to implement.
#5 Invest in Upskilling
The four “keys” are important to build an AI-powered, future-proof enterprise. They are all human related – and when they come together to work as a winning formula is when organisations invest in upskilling. Upskilling is the common glue and each factor requires specific kinds of upskilling (Figure 2).
Upskilling needs vary by organisational level and the key being addressed. The bottom line is that upskilling is a universal requirement for driving AI at scale, successfully. And many organisations are realising it fast – Bosch and DBS Bank are some of the notable examples.
How much is your organisation invested in upskilling for AI implementation at scale? Share your stories in the comment box below.
Written with contributions from Ravi Pattamatta and Ratnesh Prasad
