With "Customer" becoming the de facto focal point of all decisions and strategies in banking, the industry has evolved from a standardised service offering model to a more personalised one, underpinned by technology to meet the evolving needs of customers. Undertaking continuous "Digital Transformation" is the key to embracing change and maintaining growth while remaining competitive. This trend is likely to continue over the next decade and the customer experience will continuously be redefined by leveraging the latest emerging technologies.
Further, the risk to the business model of traditional banks is continuously increasing as Neo Banks gain more acceptance, especially with the younger generation. By leveraging cutting-edge technologies like AI, ML, RPA and cloud, these digital-only banks have been quick to roll out customised services, while the traditional banks struggle to navigate through their legacy systems. By obviating the need for any physical infrastructure, these Neo Banks are far nimble, have lower operational costs and hence can pass on these savings to their consumers.
Banks are realising the threat these Neo Banks pose to their business model and are doing everything they can to adapt to the "Digital Era" in which customers have very high expectations and expect a quick response. As banks endeavour to remain relevant, some of the top tech trends that are unfolding in the banking industry are listed below.
- Super Apps
"Super Apps" combine products and services for a seamless customer experience, tailored to customers’ needs, removing all friction points along the user journey. This is creating an ‘Experience Economy’ for customers, which requires banks to invest heavily in machine learning and artificial intelligence to make "sense" of the data.
Apps of banks will increasingly be used as lifestyle apps and not merely for banking transactions. Customer journeys will become more personalised, segmented, and real-time to keep users on the app by increasing user engagement.
A study by the Economist Intelligence Unit (EIU) estimates that nearly 74% of customers believe their financial transactions will take place via a Super App in the next 5 years. The adoption of Open Banking Standards under PSD2 compliance will support the idea of customer data being available across banks.
Customers will no longer be required to complete transactions through banking channels alone. In fact, most of them will be started by non-banking channel apps as part of the ecosystem. This would be possible by exposing managed public APIs that are protected by digital tokens.
Banks will use these API assets as leverage, opening new markets in retail, travel, hospitality etc. by simply participating in the ecosystem. As more services and interdependencies are orchestrated, container platforms will be used to run the ecosystem.
Banking As A Service (BaaS) would increasingly gain acceptance wherein banking services would be integrated into the products of other third parties. Other options like "Buy Now - Pay Later", “Cross-Border QR based payments” and robo-advisors will be offered through Apps to enrich the customer experience.
- Cloud Infrastructure and Application Services
The emergence of Cloud Technologies has rendered the monolithic IT system designs redundant. Cloud Native Solutions, which serve the purpose of independent functional units of businesses, will be developed independently, utilising autonomous and discoverable microservice frameworks that will communicate with one another via APIs under the umbrella of composable architecture.
Banks will benefit by saving infrastructure costs, increasing operational efficiency, and developing the ability to scale on demand. Cloud Infrastructure will host the majority of the banking applications and Dev-SecOps would be used for automation to expedite the deployment of new features.
Amongst the first use cases will be the migration of commercial CRM and financial ERP systems to the cloud as SaaS; Customer Insights and Fraud Checks using AI/ML; and Transfer Learning, which tries to adapt previously taught models to new circumstances.
- Hyper Automation
According to a Gartner study, automation has the potential to cut operational costs in the banking industry by almost 66–68%. Banks will employ more open-source tools and technologies, signalling a paradigm shift from the use of proprietary solutions. Low-Code-No-Code (LCNC) development platforms will be used for the quick rollout of solutions and services.
Hyper automation in banking would essentially be a three-stage process combining people and software, beginning with prototypes that leverage a range of technologies and processes that are significant to various stakeholders and then developing the skillsets to enable enterprise-wide solutions. I will briefly explain these 3 stages below.
Stage 1: Recall and Recognise: At this level, RPA, BPM and LCNC technologies would be used to create tools that would replicate manual processes and integrate rules. For instance, automating the transfer of paper forms between systems and incorporating built-in procedures for loan processing in place of manual inspection.
Stage 2: Try and Examine: Using chatbots, NLP, AI and ML, information will be accessed at this level by combining it with data from other disconnected systems to spot trends and offer insights. For instance, creating a single view of the customer and automating loan decisions from tax authorities.
Stage 3: Gauge and Design: Enhance judgments based on trends for improved income and growth, eventually leading to prospects for new products and services. For instance, offering new loan products that have quicker payout time for the consumers.
- Client Onboarding
Digital onboarding of clients will be crucial for the growth and competitiveness of banks. To provide real-time products and offers to the client upon onboarding, optimised and automated onboarding workflows will provide able a frictionless experience for the customer to interact with the bank.
The mapping of the customer journey and value streams will come first in the underlying business models and workflows to streamline processes across divisions and geographical areas. The main drivers will be the increasing competition from Neo Banks and keeping pace with changing regulations while also improving customer loyalty.
Schemes like ‘Offshore Onboarding’ can make it possible for customers to join the global banking ecosystem by utilising AI and ML algorithms to detect fraud; offering clients an omni-channel experience; biometrics-based identification; using blockchain to streamline KYC procedures and give customers control over their secure digital identities.
- Impact of Web 3.0
Edge computing, decentralised data networks powered by distributed ledger technology, and AI will form the three layers that Web 3.0 will predominantly be built upon. Smart contracts would be used to transfer funds from one account to another as we move towards decentralised finance, with less importance placed on banking institutions adopting peer-to-peer relationships. To give their clients an immersive experience, banks will increasingly transition to the "Metaverse”, while riding on data governance and embedded finance.
A better FX can be provided by programs like "Cross Border Payments" that use digital assets like XRP to make real-time settlement of remittances possible. This will allow banks to offer important services like flexible payback terms without the need for prefunding, with lower pricing and 24*7 access.
- Cyber Security
The COVID-19 epidemic has further increased businesses' concerns as hacks and cyberattacks are on the rise. As more customers embrace digital banking, there has been a corresponding rise in fraud and identity theft.
The network is likely to remain hostile and only authenticated entities will be provided access, on a need basis. Hence banks will need to build their solutions with privacy and security at the core of their design, rather than an afterthought. They will need to embrace the latest AL/ML-driven predictive analytics systems to identify scams and early identification of potentially fraudulent transactions.
Elastic logs would make it possible to gather and evaluate data from various systems for more robust monitoring. The Secure Access Service Edge (SASE) network architecture, which connects security solutions with various other systems will be the logical choice for banks.
The adoption of a zero-trust strategy would become the norm, requiring all people, software, and devices to be verified, and security frameworks and tools will have to be integrated into the digital ecosystem of banks.
Conclusion
The future of banking is changing fast globally. As the usage of plastic cards declines, most payments will be made digitally through non-banking channels. Cryptocurrencies will gain more acceptance. Most operations of banks will transition to the cloud and the brick-and-mortar bank branches will decline.
Fintech firms will operate in collaboration with banks. Internet of Things, virtual reality, and augmented reality will be tapped by banks to enhance customer experience. Also, banks will use M&A and ecosystem play to enter other industries, such as retail, travel, hospitality, etc. Banking in future will need to be more purposeful, connected, invisible, and driven by insights.
This future of banking will also require banks to revisit their resourcing strategy and redefine their job roles. Upskilling the workforce will become a top priority.
For Banks to remain relevant and meet the aspirations of a digitally native generation, they will need resilient frameworks, strong innovation skills, agility, and the ability to draw insights from customer data. Only then will they be able to stay relevant, competitive and on a growth trajectory.
