Covid outbreak has changed the world around us and the banking sector is no different. Be it the dynamically changing requirements of customers or the need to ensure continuity and resilience, the sector is rapidly undergoing transformations to maintain its ever enthusiastic attitude towards technology-driven changes. In our quest to delve into the changing mood of the sector, challenges, priorities and future projections, Rashi Aditi Ghosh of Elets News Network (ENN), interacted with Sonali Kulkarni, Lead – Financial Services, Accenture in India. During the exclusive, Kulkarni spoke to us on issues pertaining to the global workforce in a hybrid environment, risk-calibrated growth, cloud computing, Artificial Intelligence, digital-native banking models, and a lot more.
1.What are the top business priorities of banks in India? How has the COVID-19 pandemic accelerated digital adoption in the Indian banking sector?
Given the shifting economic realities, changing consumer habits as well as fluctuating income patterns, banks in India are focused on driving risk-calibrated growth. For example, during the pandemic, the inherent credit profile of some bank consumers changed due to fluctuating income patterns or a short-term liquidity crunch. Being able to forecast credit risks helps banks proactively re-align collections strategies and restructure their customer portfolio to manage asset quality.
It has become equally important for banks to develop a scalable and resilient operating model, which has the ability to handle sudden surges in consumer demand and which enables enhanced experiences not just for their customers but also for their employees, many of whom have been working remotely.
Thirdly, banks have realised that consumer behavior will continue to evolve and hence, they need to adapt their business models so as to achieve the right cost to serve. For instance, customer visits to physical bank branches did decrease during the national lockdown whereas interactions on digital touchpoints increased. Given that this is an ongoing phenomenon, banks need to adapt and repurpose some of their existing physical infrastructure investments and rethink the role of branches in the long-term.
Lastly, redefining their future of work strategy is a key priority. Banks will need to think of how they can build and sustain a world-class workforce in a hybrid environment and the talent pool that they will hire from given that traditional location-centric parameters may become less relevant.
The pandemic has reinforced that no business priority can be fulfilled without the right impetus and focus from a technology perspective. In line with the behavioral shift towards more digital experiences, banks in India have been prioritising the transformation of their business models and making strategic investments in technology. They have also accelerated their digital transformation plans – plans which were earlier envisaged to take three to five years to fructify, are now being advanced for completion in 18-24 months.
2. How can banks in India transition to or develop digital-native business models? How feasible is this in a market like India which has an eclectic customer base?
Globally, neo banks have built digital native business models which not just have a completely digital front-end but also a digital backend and core. Being digital and cloud-native makes these systems scalable, resilient, helps banks go to market faster and offer more personalised experiences to their customers.
In India, we have a fairly diverse set of retail banking customers. People in the urban and the metro city markets are more digitally savvy from a banking perspective due to higher digital consumption and easy availability of data and connectivity. However, this is not the case in smaller cities and rural India. That said, there is potential to build digital-native models in banking for all segments. Banks need to adopt a differentiated digital strategy to drive adoption and usage such as adopting more digitally assisted models with video and voice interfaces and creating content in local languages.
3. Cloud adoption sits right in the center of technology transformation – with most banks realising the potential and value of cloud adoption. Where are Indian banks placed in their journey to the cloud?
Indian banks are perhaps four to five years behind in their cloud adoption journey as compared to peers in other markets such as the United States. Having said that, the traditional global reasons for moving to cloud – such as cost optimisation – are not necessarily the most compelling reasons for driving adoption in Indiasince the cost of hardware in India is relatively low and there are existing investments in data centers. Instead, building digitally native business models to enable advanced real-time analytics, deliver enhanced storage and compute, and a resilient and scalable operating model are the real benefits that Indian banks can derive from cloud adoption.
The post-pandemic lockdowns forced banks to take a hard look at their cloud adoption strategy due to an explosion in the customer demand for digital banking solutions and their own employees’ need for secure work-from-home systems. Banks have demonstrated a strong intent to move to the cloud to harness the benefits of scalability, resilience and cost elasticity. We are seeing a lot of underlying payments infrastructure and loan origination moving to the cloud. In fact, a lot of the new software and services that banks are signing up, for now, are cloud-native. We expect this journey into Cloudtocontinue picking up pace. It is important that banks conduct a thorough assessment of their technology landscape to evaluate which new or existing applications are to be replaced or moved to the cloud, consider new capabilities, cloud costs metering and governance requirements and then undertake their cloud transformation journey.
4. What are the most common goals of AI adoption in India and what are the challenges? What is your take on the maturity of AI investments by Indian banks?
Currently, the most common goals of AI adoption by banksare to significantly improve business operations, customer experience, employee productivity and risk mitigation.
Banks in India have started to make investments in artificial intelligence (AI) and robotic process automation (RPA) to bring in variability into their operations. However, even though adoption has grown in certain pockets, the technology has not significantly lived upto its expected potential and customer experience has been sub-optimal. For example, forced by the lockdowns, banks started using more AI for customer interactions by way of automated call center conversations and through chat bots. But the customer experience has not been great – these chatbots continue to be menu-driven or FAQs-driven and are rarely able to truly converse with customers. More work is required to ensure that conversations enabled by AI and chatbots are as natural and free-flowing as possible.
Another reason for lower efficacy is because currently the bots are only learning from information available on one channel and donot have access to information across various customer interaction channels. Let’s take the illustration of a customer who has received a response to her query from the bank’s e-mail bot orhas interacted with a chat bot, today. If the same customer calls up the bank’s call center with a follow-up query tomorrow, the call center executive should ideally have access to a holistic view of the customer’s previous interactions with the bank including those with bots, so that the conversation can be picked up from where it was left off. The true power of AI can be harnessed only if there is a complete and seamless integration of data and the human + machine workforce. Continued human intervention is key to maximising the power of AI.
Going forward, banks need to go beyond point solutions and adopt AI in a holistic manner in order to unlock trapped value across the banking value-chain.
5. With the growth of the digital economy, banks are encountering risks that are different from what they have traditionally dealt with. How are AI and analytics helping them with risk discovery and mitigation?
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During the pandemic, a large number of banks have discovered the merits of smart, data-driven risk discovery and mitigation to get early warnings on market and credit risk and identify pressure points in their business.
From a sectoral credit risk perspective, newer analytical models use external data including macroeconomic trends, micro-segmentation and data modeling techniques to offer a predictive analysis of which sectors will likely be stressed. Banks are using ML-based algorithms for smarter underwriting of consumer credit risk and improving their ability to identity delinquency patterns and manage collections risk better. Analytics has also been helping banks with fraud detection.
6. Banks in India are faced with regulatory scrutiny on the issue of digital outages and technical glitches. How do banks ensure that their IT systems are scalable and resilient? Is there a way of preventing outages altogether?
Outages are a reality, and it may not be possible to prevent them altogether. However, banks need to put in place measures to minimise business disruption during the outages and enhance their ability to bounce back faster. There are three aspects to build resiliency.
On an immediate-term basis, banks need to identify applications where they see high usage and those that need to be available 24*7. Thereafter, they need to envisage the future capacity requirement by forecasting growth in terms of volumetrics and the demand for these services and ensure high availability. They also need to periodically test the data center and disaster recovery (DCDR) systems resiliency for such applications.
On an ongoing basis, banks should adhere to certain ‘brilliant basics’ of building resilient systems. An onslaught of new digital features and shorter release cycles make it all the more crucial to adopt these ‘brilliant basics’ – such as factoring in not just the user experience but also non-functional requirements such as scalability (compute), performance, reliability, concurrency and capacity. They need to ensure performance testing, load testing and end-to-end integration testing before new releases to avoid disruptions later on. These are critical to determine if the application can operate under different loads, volumes and environments. Banks need to build capabilities for proactive end-to-end business monitoring– these will not just send them proactive alerts but will also help identify the root cause of the outage and resume their services quickly.
From a long-term perspective, banks need to decouple applications from their core banking system, implement a layered, microservices-based and event-driven technology architecture to manage high volumes of transactions, and adopt a cloud-first strategy and a cloud-native approach to new digital assets so as to ensure adequate compute, scalability and flexibility.
7. How should banks prepare for the future of work and hybrid working models from a technology standpoint?
In the long term, we expect the future of work at banks to be driven by a human plus machine model. The role of human capital can be reimagined through the use of technology. For instance, the role of contact center staff is expected to evolve to higher-value tasks as people work alongside AI to address customer queries. Similarly, a lot of routine tasks will get automated. The role of people who are working at branches will also need to evolve to a much more advisory one.
From an employee experience perspective, banking processes will need to become fully digital to enable employees and partner staff to operate out of anywhere. While we are already seeing some banks move forward in this direction, this phenomenon will become more pronounced in the future.