When the FinTech revolution started, traditional banking felt the heat of competition from the ‘new kid on the block’. FinTechs promised (and often delivered) fast turnarounds and personalised services. Banks were forced to look at their operations through the lens of customer experience, constantly re-evaluating risk exposures to compete with FinTechs.
But traditional banks are giving their ‘neo-competitors’ a run for their money. Many have transformed their core banking for operational efficiency. They have also taken lessons from FinTechs and are actively working on their customer engagements. This Ecosystm Snapshot looks at how banks (such as Standard Chartered Bank, ANZ Bank, Westpac, Commonwealth Bank of Australia, Timo, and Welcome Bank) are investing in tech-led transformation and the ways tech vendors (such as IBM, Temenos, Mambu, TCS and Wipro) are empowering them.
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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.
More than ever before you are having to cater to digital-savvy customers and create a competitive edge through the customer experience (CX) that you provide. In this two-part feature, I explore the barriers organisations face in their goal to create a memorable CX; and what the organisations that are getting it right have in common.
Spend on digital services, technologies, platforms, and solutions is skyrocketing. As businesses adapt to a new normal, they are increasing their spend on digital strategies and initiatives well beyond the increase they witnessed in 2020 when all customer and employee experiences went digital-only. But many digital and technology professionals I meet or interview maintain that their digital experiences are poor – offering inconsistent and fragmented experiences.
The Barriers
Digital, CX and tech leaders highlight their laundry list of challenges in getting their digital experiences to deliver a desired and on-brand customer experience:
A poorly informed view of the customer and their journey. Sometimes the customer personas and journey maps are simply wrong – they were developed by people with an agenda or a fixed idea of what problems need solving.
Inconsistent data. Too much, too little, or plain incorrect data means that automation or personalisation initiatives will fail. Poor access to data or lack of data sharing between teams, applications and processes means that businesses cannot even begin to build a consistent CX.
Too many applications and platforms. As digital initiatives took hold, technology teams witnessed an explosion of applications and platforms all conquering small elements of the digital journey. While they might be great at what they do, they sometimes make it impossible to create a simple and consistent customer journey. Some are beyond the control of the technology team – some are even introduced by partners and agencies.
Inconsistent content. For many businesses, content is at the heart of their digital experience and commerce strategy. But too often, that content is poorly planned, managed, and coordinated. Different teams and individuals create content; this content is then inconsistently delivered across customer touchpoints; the content is created for a single channel or touchpoint; and delivers to customers at the wrong stage of the journey.
Little co-ordination across channels. Contact centres, retail or other physical locations and digital teams often don’t sing from the same songbook. Not only is the customer experience inconsistent across different physical and digital touchpoints, but it may even be inconsistent across digital touchpoints – chat, web and mobile offer different experiences – even different parts of the web experience can be inconsistent!
Knowledge is not shared between channels. Smart customers will “game” a company – finding the best offer across different customer touchpoints. But more often than not, inconsistent knowledge leads to very poor customer experiences. For example, a telecom provider might give different or conflicting information about their plans across web, mobile, contact centre and retail outlets; and with the increasing popularity of marketplaces, customers receive inconsistent product information when they deal with the brand directly than through the marketplace. Knowledge systems are often created to serve individual channels and are not trusted by customer service or retail representatives. We see this in Ecosystm data – when customer service agents are asked a question, they don’t know the answer to, the first place they look is NOT their Knowledge Management tool.
Poor prioritisation of customer pain points. Customer teams may find that it is easier to tackle the small customer challenges and score easy points – and just deprioritise the bigger ones that will take significant effort and require considerable change. Unifying the customer journey between the contact centre and digital is one big challenge that many businesses continue to delay.
And it gets worse… According to Ecosystm data, 55% of organisations consider getting board and management buy-in as their biggest CX challenge. This means that Chief Digital Officers, CX professionals and digital teams are still spending a disproportionate amount of time selling their vision and strategy to the senior management teams!
But some organisations are getting it right – creating a memorable digital experience that retains their customers and attracts more. I will talk about what is working for them in the next feature.
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?
One of the main questions that I have faced over the past week, since I wrote the Ecosystm Insight – Welcome to the Great Bounce Forward – is “How is this different to the “New Normal”? Many have commented that the concept of the Great Bounce Forward is more descriptive and more positive than the term “New Normal” – but I believe they are different, and require different strategies and mindsets.
This is a brief summary of some of the major differences between the New Normal and the Great Bounce Forward. I look forward with excitement and some trepidation towards this future. One where business success will be dictated not only by our customer obsession, but also the ability of our business to pivot, shift, change and adapt.
I can’t tell you what will happen in the future – a green revolution? Another pandemic? A major war? A global recession? Market hypergrowth? All the people living life in peace? Imagine that…
What I can tell you is what your organisation needs to do to be able to meet all of these challenges head-on and set yourself up for success. And to me, that won’t look like the new normal. There is nothing normal about these business capabilities at all.
Customer Experience teams are focused on creating a great omnichannel experience for their customers – allowing customers to choose their preferred channel or touchpoint. And many of these teams are aware of the challenges of omnichannel – often trying to prise the experience from one channel into another. Too often we create sub-optimal experiences, forcing customers to work harder for the outcome than if they were using other channels.
I know there have been times when I have found it easier to jump in the car and drive to a store or service centre, rather than filling in a convoluted online form or navigating a complex online buying process. I constantly crave larger screens as full web experiences are often better than mobile web experiences (although perhaps that is my ageing eyes!).
One of the factors that came out in a study conducted by Ecosystm and Sitecore is that customers don’t just want personalised experiences – they want optimised experiences. They want to have the right experience on the right device or touchpoint. It is not about the same experience everywhere – the focus should be on optimising experiences for each channel.
We call this “opti-channel”.
Use an Opti-Channel Strategy to Guide Investment and Effort
This is what you are probably doing already – but by accident. I suggest you formalise that strategy. Design customer experiences that are optimised for the right channel or touchpoint – and personalised for each customer. Stop forcing customers into sub-optimal experiences because you were told to make every customer experience an omnichannel one.
The move towards opti-channel accelerates your ability to provide the best experience for each customer, as you ask the important question “Does this channel suit this experience for this customer?” before the fact – not after the experience has been designed. It also eliminates the rework of existing experiences for new channels and provides clear guidance on the next-best action for each employee.
There Will be Conflict Between Opti-Channel and Personalisation
The challenge for opti-channel strategies will be to align them to your personalisation strategy. How will it work when you have analytics driving your personalisation strategy that say customer X wants a fully digital experience but your opti-channel strategy says part of the digital experience is sub-standard? And the answer to this lies in understanding the scope of your experience creation – are you trying to improve the existing experience or are you looking to create a new improved experience?
- If you are improving the existing experience, then you have less license to shift transactions and customer between channels – even if it is a better experience.
- If you are creating a new experience, you have the opportunity to start again with the overall experience and prove to customers that the new experience is actually a better one.
For example, when airlines moved away from in-person check-in to self-check-in kiosks, there was an initial uproar from customers who had not yet experienced it – claiming that it was less personal and less human. But the reality is that the airlines took the check-in screen that the agents were using and made it customer-facing. Travellers can now see the seats and configuration and select what is best for them.
This experience was reinvented again when the check-in moved to web and mobile. By turning the screen around to the customer, the experience actually felt more human and personal – not less. And by scattering agents around the screens and including a human check-in desk for the “exceptions”, the airlines could continue to optimise AND personalise the experience as required.
Opti-Channel Opens Many New Business Opportunities
Your end-state experience should consider what is the best channel or touchpoint for each step in a journey – then determine the logic or ability to shift channels. Pushing customers from a chatbot to web chat is easy. Moving from in-store to online might be harder, but there are currently some retailers looking to merge the in-store and digital experience – from endless aisle solutions to nearly 100% digital in-store. Some shoe and clothing stores offer digital foot and body scans in-store that help customers choose the right size when they shop online. And we are beginning to see the rollout of “magic mirrors” – such as one retailer who has installed them in fitting rooms and you can virtually try different colours of the same item without actually getting them off the shelf.
Businesses are trying to change customer behaviour – whether it is getting them into stores or mainly shopping online or encouraging them to call the contact centre or to even visit a service centre. Creating reasons for why that might be a better option, while also providing scaled-back omnichannel options is a great way to meet the needs of existing customers, create brand loyalty and attract new customers to your company or brand.
Uniphore, a provider of Conversational Automation solutions, has announced their intention to acquire Jacada, an Israel-based autonomous customer experience solution provider. Jacada’s low-code/no-code platform will help Uniphore solve complex contact centre challenges using AI and automation. Jacada’s strengths include a low-code optimised interface and AI-enabled contact centre capabilities leading to automation across agent and customer engagements, enhanced knowledge-based guidance for agents and end-to-end analytics and insights.
Jacada has been in the market for around three decades and over time they have built various unified desktop and process optimisation products including RPA for customer service and support.
The acquisition follows Uniphore’s USD 140 million Series D funding round led by Sorenson Capital Partners in March 2021. Earlier this year, Uniphore acquired Emotion Research Lab to add AI and machine learning video capabilities that identify the emotion and engagement levels over video-based communications.
Growing Importance of Agent Assist Solutions
With agents facing pressure in offering customers satisfactory outcomes and at the same time having to manage the high volume of inbound transactions, Agent Assist solutions are high on the agenda for organisations. Remote working has made things even more complex where agents are cut off from their supervisors and not able to walk up to them to seek guidance. These “immediate challenges” have not yet been addressed in every contact centre even a year after the crisis. This presents a good opportunity for Uniphore to own the front and back-office integration piece. The back-office integration segment has become increasingly important as there is a need to fulfill customer requests by ensuring the conversation thread with back-office systems is followed through and communicated back to the agent. This need was heightened during the pandemic due to delays in product arrivals, in shipments, and other delays and miscommunication.
The big challenge also lies in making Agent Assist help the agent perform better and not make their lives more stressful! The design element of Agent Assist is critical. The solution must fit well into the other systems and applications such as CRM, Knowledge Management, and Speech Analytics. You don’t want another solution being pushed on to the agents when they are under pressure to meet customer demands during a 15-minute call.
Conversational Automation and Agent Assist must be evaluated carefully as you are integrating the solution into multiple environments with the clear objective of ensuring that agents only get the right information, in a manner that makes sense for them and at appropriate intervals.
The Growing Importance of Low-code No-code (LCNC)
As contact centres focus on business agility and pivoting fast to cope with sudden market shifts, organisations will benefit from moving programming closer to the contact centre – requiring very little assistance from IT teams.
Having a LCNC platform will now allow Uniphore to build front and back-office experiences in a multi-vendor environment. The need to use intelligent APIs to build workflows is high on the agenda and it helps eradicate the costly efforts and time spent on developers to further extract and build new capabilities at speed.
Jacada has been pushing their value proposition on RPA and Conversational Automation for some time now and this blends well with where Uniphore is going with AI and Automation in the contact centre space. The acquisition will also give Uniphore access to other contact centre technologies that will help them to compete better with a wider range of solutions. With the challenges in managing the agent experience, we can also expect the Workforce Experience Management (WEM) segment to play an important role and intersect with Agent Assist to manage and elevate the agent experience.
Many years ago – back in 2003 – I spent some quality time with BMC at their global analyst event in Phoenix, Arizona and they introduced the concept of “Business Service Management” (BSM). I was immediately a convert – that businesses can focus their IT Service Management initiatives on the business and customer services that the technology supports. Businesses that use BSM can have an understanding of the impact and importance of technology systems and assets because there is a direct link between these assets and the systems they support. A router that supports a customer payment platform suddenly becomes a much higher priority than one that supports an employee expense platform.
But for most businesses, this promise was never delivered. Creating a BSM solution became a highly manual process – mapping processes, assets, and applications. Many businesses that undertook this challenge reported that by the time they had mapped their processes, the map was out of date – as processes had changed; assets had been retired, replaced, or upgraded; software had been moved to the cloud or new modules had been implemented; and architectures had changed. Effectively their BSM mapping was often a pointless task – sometimes only delivering value in the slow to change systems – back-end applications and infrastructure that delivers limited value and has a defined retirement date.
The Growth of Digital Business Strategies
Our technology systems are becoming more important than ever as digital business strategies are realised and digital interactions with customers, employees, and partners significantly increase. Many businesses expect their digital investments to remain strong well into 2022 (Figure 1). More than ever, we need to understand the link between our tech systems and the business and customer services they support.
I recently had the opportunity to attend a briefing by ServiceNow regarding their new “AI-Powered Service Operations” that highlighted their service-aware CMDB – adding machine learning to their service mapping capabilities. The upgraded offering has the ability to map entire environments in hours or minutes – not months or weeks. And as a machine learning capability, it is only likely to get smarter – to learn from their customers’ use of the service and begin to recognise what applications, systems, and infrastructure are likely to be supporting each business service.
This heralds a new era in service management – one where the actual business and customer impact of outages is known immediately; where the decision to delay an upgrade or fix to a known problem can be made with a full understanding of the impacts. At one of my previous employers, email went down for about a week. It was finally attributed to an upgrade to network equipment that sat between the email system and the corporate network and the internet. The tech teams were scratching their heads for days as there was no documented link between this piece of hardware and the email system. The impact of the outage was certainly felt by the business – but had it happened at the end of the financial year, it could have impacted perhaps 10-20% of the business bookings as many deals came in at that time.
Being able to understand the link between infrastructure, cloud services, applications, databases, middleware and business processes and services is of huge value to every business – particularly as the percentage of business through digital channels and touchpoints continues to accelerate.
If you are a digital leader in the Financial Services industry (FSI), you have already heard this from your customers: ‘Why is it that Netflix and Amazon can make more relevant and personalised offers than my bank or wealth manager?’ Digital first players are obsessed with using data to understand their customer’s commercial and consumer behaviour. Financial Services will need to become just as obsessed with personalisation of offerings and services if they want to remain relevant to their customers. Ecosystm research finds that leveraging data to offer personalised service and product offerings to their clients is the leading digital priority in more than 50% of FSI organisations.
Banks, particularly, are both in a strong position and have a strong incentive to offer this personalisation. Their retail customers’ expectations are now shaped by the experience they have received from their favorite digital first firms, and they are making it increasingly clear that they expect personalised offerings from their banks. Furthermore, they are well positioned as a facilitator of commercial relationships between two segments of customers – consumers and merchants. The amount of data they hold on consumer interactions is comprehensive – and more importantly they are a trusted custodian of their customers’ data and privacy.
The Barriers to Personalisation
So, what is stopping them? Here are three insights from over 12 years of experience driving digitisation of Financial Services:
- Systems Legacy. Often the data and core banking systems do not allow for easy access and analysis of the required data across the data sets required (eg. Consumers and Merchants).
- Investment Priorities. There is still a significant investment happening in compliance and modernisation of core banking systems. Too often the focus of these programs can be myopic, and banks miss the opportunity to solve multiple pain points with their investments driven by overly focused problem statements.
- Culture and Purpose. Are banks stuck in a paradigm of their own making – defining their business models by what has served them well in the past? Will Amazon think about its provision of working capital to their small and medium business partners the same way as a bank does?
Vendor Focus – Crayon Data
Thankfully, there is a new breed of tech vendors who is making it easier for banks to drive personalisation of their offerings and connect customers from across segments. Crayon Data is a good example, with their maya.ai engine unearthing the preferences of customers and matching them to offerings from qualified merchants. It benefits all parties:
- The Consumer receives relevant offers, is served from discovery to fulfillment on a single platform and all personal data and information guarded by their bank.
- For Merchants, it allows them to reach the right customers at the right moment, develop valuable marketing and insights and all this directly from their bank partner’s platform.
- For Banks, it provides a scalable model for offer acquisition and easily configurable and measurable consumer engagement.
maya.ai leverages patented AI to create a powerful profile of each customer based on their buying habits and comparing these with millions of other consumers drawn in from their unstructured data sets and graph-based methodology. They then use their algorithms to assist their Financial Services client to make relevant offerings from qualified merchants to consumers in the right channel, at the right moment. All of this is done without exposing personal client information, as the data sets are based on behaviour rather than identity.
Conclusion
There are significant considerations for banks in offering these types of capabilities, such as:
- Privacy. While the technology operates on non-identifiable information, the perception of clients being ‘stalked’ by their bank in order to drive business to a merchant is one that would need to be managed carefully.
- Consumer opt-out. The ability for customers to opt out of this type of service is critical.
- Consumer financial wellbeing. It may be in the best interests of some consumer to not receive merchant offers, for instance where they are managing to a strict budget. These considerations can be baked into the overall customer journey (eg. prompts when the consumer is nearing their self-imposed monthly budget for a category), but care will need to be taken to keep customers’ best interests at heart.
While there are multiple challenges to overcome, the fact remains that personalisation is quickly becoming a core expectation for consumers. How will banks respond, and will we see AI use cases like Crayon Data become more prominent?
