Rob Brown, Associate Vice President at Cognizant’s Centre for the Future of Work
Chatbots are gaining in popularity in a number of industries as an important customer service tool, with financial services and insurance particularly keen to roll them out: Crédit Agricole Assurance has Marc, and Bank of America recently announced it was introducing Erica. Barclays, Société Générale, USAA, BBVA, and Capital One have all also begun investigating the technology.
The rise of chatbots is being driven by several converging trends: the popularity of messaging apps, the explosion of the app ecosystem, advancements in artificial intelligence (AI) and cognitive technologies, conversational user interfaces and a wider reach of automation. Their adoption is accelerating so quickly that Oracle believes that 80% of brands will be using them by 2020. But will the current hype be sustainable over time without a stronger business rationale and better short-term results?
We live in an age of instant gratification, and this certainly applies to exchange of information – the core mission of financial services. So why are customers confronted with long wait-times on hold, being transferred department-to-department, or having to wait through a list of phone prompts? In the context of chatbots, it is actually not about “the robot” at all, it is all about how easy the end-user finds it to use, and simply whether it works or not. To get it right, businesses should start preparing for the coming bot age now if they have not begun to already. This means peeking into the future and designing bots to respond to today’s customer needs, such as personalisation, context, meaning, first contact resolution, management, as well as bot-human interaction and interface design.
Here are four areas chatbots will evolve.
- Specialisation and Personalisation
For chatbots to be effective, they need to become far more specialised in topics and tasks, and have the ability to personalise interactions. As time goes by, we will begin to see this happen. Very soon we will see expert chatbots that specialise in providing information about different banking solutions, while there will be some like x.ai’s Amy, Apple’s Siri or Microsoft’s Cortana that are experts in making calls and scheduling meetings, or helping to orchestrate process steps. For example, your close of escrow got delayed due to unforeseen disclosures from the seller – was the bank notified not to fund the mortgage loan? In-the-moment examples like these will make chatbots more utilitarian and dependable.
On the flip side, users will also then need to understand what the chatbots does, specialises in, excels in and – most importantly – where it has limitations. This leads to one of the most crucial design decisions: the history of continuity and personal connection. Consider this element as a “tuning fork” of sorts that brings together and harmonises all interactions a person may have on a given subject.
If the user were to stray from a central line of main dialogue, for example, from Siri to Facebook Messenger, a chatbot will need the history and context of other discussions with people, places, and things in order to provide continuity and personal connection. In turn, this will dictate how much personalisation can be brought into the interaction itself. For instance, can the system remember user profiles, previous interactions, the interactions of other users in the system, the current context and the situational bigger picture? Chatbot creators will then need to design them so that they can access this information using a multitude of systems and derive meaning from that information, all while keeping the central “plot line” of context intact.
- Speed of Response
One of the things that makes most present-day browsers so useful is their ability to answer questions at almost the speed of the user’s thoughts – sometimes faster. The experience of a good chatbot interaction is not judged only on its capacity to answer a question correctly but also the speed at which such a response is provided. In the bot world, solving a problem after a first contact with a customer will become a key performance metric.
Chatbots that can provide basic solutions in the first instance without the need to paraphrase or explain the problem in greater detail will be the most useful and, by extension, the most popular.
- “Superbots” – Your Personal Assistant
The concept of a superbot is not yet well known but will be a significant element in the future of bots. Indeed, as bots become more specialised and popular, they will proliferate. For many companies, managing them could become as overwhelming and complex as managing apps is today. The solution could come in the form of a superbot.
A superbot, or “bot of bots,” would act as a personal assistant, getting things done on behalf of the user. That would mean calling other bots to complete tasks such as scheduling meetings, dialing conference call numbers or redirecting the customer to the appropriate page to make a claim. The superbot would know which bot to call for a particular task and instruct that bot to provide feedback to the user, therefore being faster and more efficient. Some platforms already use “global managers”, automated robots that orchestrate workflow, and delegate which process transactions should be worked on by myriad other robots.
- Humanising Chatbots
Many of us will have seen an example of a gimmicky, humanoid “greeter robot” deployed in your high-street bank branch but the chances are, it fell short on actual needs-based problem solving for the customer. Chatbots, to the rescue – customers actually want solutions to process common choke-points in the gaps between information flows. Most of today’s technology exploration focuses on enhancing features and improving functionality to enable chatbots to mimic human responses, engaging in a more natural, intelligent conversation with users. Despite the merits of this work, the continued success of chatbots will not wholly depend on their ability to conduct a natural conversation but on the accuracy of their responses to customers’ questions at the moment-of-truth: when the tax bill is due, when the overdraft charge kicks in or when the mortgage documents are being finalised.
Humans can sense when they are interacting with a machine, and any attempt to make it appear more human rather than intelligent may end up triggering negative emotional responses in humans— this phenomenon has been called “the uncanny valley” by a Japanese roboticist in the 70s. That is why some novelties robots are merely a distracting detour on the road to real breakthroughs in applying automation that matters to the financial services sector for real and lasting results.
Chatbots will be the vanguard of these efforts, and success will hinge upon their ability to become useful, maybe even indispensable, to human beings. Automation has its limits — and there are some things that robots just cannot do. That is where a blended model of automation augmenting people in their daily lives, conversations, and information requirements can provide extraordinary outcomes. By connecting conversations with meaning, context and intelligence, and providing people with relevant information in real-time and after absences, chatbots will provide as higher quality service and outcomes.
For companies in financial services, in addition to other industries, it requires striking a balance between speed, specialisation, and personalisation provided by chatbots and the ability to cater to human sensibilities and expectations. After all, the main goal is to support users and to make their lives easier.
How to use data to protect and power your business
By Dave Parker, Group Head of Data Governance, Arrow Global
Employees need to access data to do their jobs. But as data governance professionals, it’s our job to protect it. Therefore, we must perform a fine balancing act to weigh robust data protection against the productivity of workers who need the data to maintain business-as-usual working processes.
Data grows exponentially, and most organisations will admit that they simply don’t know what data they have, where it is, and the controls that exist around it. This creates 2 challenges:
- Burgeoning amounts of unstructured data makes the business increasingly vulnerable from external attackers or internal data breaches.
- Because data is the key to understanding a customer’s wants and needs, if the business can’t identify its data and unlock its value, it’s at a competitive disadvantage.
As a European investor and alternative asset manager, here at Arrow Global we take care of £50bn of assets and own a data estate exceeding 160TB. How we manage our data is key to our success. We understand the difficulties involved in opening up environments to allow people to work productively, while at the same time locking them down to protect our organisation.
When it comes to analytics, I believe that Arrow is highly proficient because we employ a talented team of data scientists. But even for us, the sheer volume of raw and processed data, that resides in both our structured systems and unstructured data repositories, has the potential to put our business at risk.
We know there’s always more that can be done to strengthen our security posture and ensure regulatory and contractual compliance, while at the same time using our data to drive the business forward.
Data protection isn’t just about compliance
For many organisations, data protection has centred on demonstrating compliance with the GDPR. At Arrow, our efforts have gone one step further to include our contractual exposure.
Being a more mature data organisation, we had previously tried to develop an application in-house to manage our data estate. However, with 160TB across the company in production data alone, we simply couldn’t achieve the scale we needed to handle the sheer volume of data. Of course, the volume is just the start – once you know what data you have, you then need to be able to categorise the data and put it into a structure, so the business can analyse it for a specific use case.
We knew we needed to go to market to find an industrial-strength data discovery product to replace our in-house application. By aligning our choice of product to our overall IT and change strategy, meant that ultimately, we ended up with a far better outcome than we’d anticipated.
Position data as both a risk and an asset
Data touches every part of an organisation, so when it came to building a business case for buying-in a data discovery software platform, we approached it in a way that would speak to different people at the same time. We did this by posing the question:
“What do we want to do with data in a way that is GDPR-compliant, contractually-compliant and enables us to better service our clients?”
These are the black and white tests of data governance – to recognise the importance of securing and protecting data. They’re applied in a way that enables us to commoditise data and use it to drive the business forward, by forcing us to consider how we would use the data – for example, creating value-based pricing for our clients.
In aligning the business case to initiatives that were already priorities within the boardroom, we knew that we’d gain the attention of the senior leadership team and it would be easier to get the buy-in and budget we needed. And in the end, everyone wins – we get what we need to protect the data, and the business gets to distil the data’s value to better meet our customers’ expectations.
Get visibility of data at scale
For us, things got really exciting once we were able to see all of our data at scale. We chose Exonar because it allowed us to discover our data in ways that other products couldn’t. And the interface between the user and Exonar meant that everyone – both technical and non-technical users – could understand the technology and the findings it revealed.
When we saw exactly what data was in the estate, where it was and who had access to it, data security became much easier and the risk of data being compromised was dramatically reduced. We can see exactly where the vulnerabilities are and restructure how our data is stored to strengthen security. Then over time, we can use search, workflow and analysis to optimise the infrastructure and continually identify new areas to improve.
Commercialise the data
From a wider-business perspective, once people can see the data, they can start asking “What if…” to query it and distil its value. But it’s more than just the data itself. It’s not uncommon for data relating to the same thing to exist in unconnected systems across the business. For example, customer interactions and incidents or events.
Exonar is capable of joining the dots in disparate data sets. By stitching these data sets together, we can get a better overall view of our customers and use the outcomes to think of new, different or better ways of serving them through enhancing or adapting our offerings.
Why other financial services businesses should also take a smarter approach to data
- By changing the way you approach data, you can use it to protect and power your business and the people you serve.
- By positioning data as both a risk and an asset, you elevate its position to give it priority in the boardroom. Ultimately, it’s data that helps the business make informed strategic decisions about how to strengthen its competitive advantage.
- By gaining visibility of data at scale, you can see exactly what data you have and where it is. This gives the business confidence about the actions needed to ensure it is secured in both a regulatory and contractually compliant way, and that people are doing the right thing with data at all times.
- And joining different data sets provides you with a single view of ‘X’ within your data, no matter where it is. Helping to support your wider-business strategy and priorities, it gives you the information you need to secure a business advantage and generate value.
How business leaders can find the right balance between human and bot when investing in AI
By Andrew White is the ANZ Country Manager of business transformation solutions provider, Signavio
The digital world moves quickly. From keeping up with consumer behaviour patterns, to regulation and compliance, the most successful organisations are always on the cutting-edge of technological developments.
However, when it comes to investing in artificial intelligence (AI), a hard and fast strategy does not guarantee a top spot amongst the league of tech greats. Instead, it pays to take a considered approach to balancing reliance on automated processes with a human touch. Why? Because creative and strategic thinkers are the true propellers of innovation; automation is simply the enabler.
The International Monetary Fund (IMF) developed the ‘Routine Task Intensity’ (RTI) index as a measure of which processes are likely to benefit most from automation. According to this metric, jobs requiring analytical, strategic, communicational and technical skills score low on the RTI index, while simple, repetitive tasks scored highly.
The lesson for business leaders here is simple; your digital investments are just as important as your stake in talent. When deciding which processes to automate, start simple, and remember to value the skills and potential of your people.
Keep customer-centricity at your core
Customer-centricity means that every business decision, dollar spent and new hire is centred on one question: how does this benefit my customer? Investments in AI are no different. To be truly successful, they must have a customer-focused outcome.
Where companies get this wrong is by implementing cost-saving measures or ‘copy and paste’ software that fails to improve the customer experience – often having the adverse effect.
Take the virtual chat-bot, for example; if implemented poorly, it can send your customers into a frustrating and seemingly infinite cycle of dead-ends. The modern consumer is far too digitally savvy for this shortcut, and will quickly move onto the next merchant offering a more seamless customer service experience.
To guarantee your investments are delighting rather than infuriating your customers, it helps to take an outside-in perspective of your business processes, aided by Customer Journey Mapping (CJM).
Before you commit to digital investments, CJM can trace and map each customer touchpoint, signalling pain points or conversion rates throughout their journey. These data-driven insights lead you to the areas that would benefit the most from automation, instead of implementing a broad band-aid solution.
Avoid the ‘set and forget’ method
When investing in enterprise-wide AI, the ‘set and forget’ method rarely works. Real transformation requires an ongoing dedication to refining and improving AI-driven processes, as well as adapting them to the evolving needs of your customers. This is the best way to achieve customer loyalty, by proving that your organisation listens to, and understands its users.
A human perspective is invaluable here, paired with process mining – a method that thrives on finding process inefficiencies – to create a consistent feedback loop of improvement.
During periods of uncertainty, customer loyalty is everything, so aim to protect it at all costs.
The power of your people
The rise of automation can be linked to the corporate world’s obsession with speed and efficiency. However, the psychology behind this goes deeper than being the biggest and fastest producer; it’s also about reallocating resources into attracting and retaining the brilliant minds that drive companies into the future.
When communicating digital change, it’s critical to highlight the valuable impact AI has on augmenting jobs; removing the burden of mundane, repetitive tasks and allowing for more strategic skill-sets to shine through. For lower-skilled workers, invest in upskilling or re-education where possible.
Successfully rolling-out digital transformation plans means that every employee across all tiers of your company understands the value of AI. The starting point here is education to achieve buy-in. Change communications must be accessible, constructive and value-focused, supported by key culture influencers who champion automation within teams.
Enterprise-wide buy-in is an important element of refining and improving digital processes, as cross-functional collaboration can offer valuable insights into common pain points or inefficiencies ripe for automation. Supported by process mining, collaboration provides a holistic view of how each investment will impact other processes. There is no point investing in automation that streamlines one process and makes another more people-centric, so be sure to take a balanced approach to your investments.
Remember, AI is not about creating an army of robot workers; it’s about increasing efficiency and productivity so that an organisation, and its people, can work smarter.
Are you a fighter or a freezer? The 4 “F’s” of Surviving Danger.
By Dr.Roger Firestien, Author of Create In a Flash.
The fight, flight, freeze survival response – or FFF for short – is designed to mobilize our brain and body to fight an enemy, run from a tidal wave or freeze to hide from a predator.
FFF is how humans react when they encounter a dangerous situation. It is a primal response that happens instinctively even before we are able to think about the situation we are confronting.
The FFF alarm causes our brain to focus on negative memories, probably to scan them to avoid repeating dangerous situations and negative outcomes. We get tunnel vision as our pupils dilate to increase our focus and long-range vision, but as a result we lose our peripheral vision.
Humans use the FFF response and so do organizations.
When organizations encounter dangerous situations, like, say, trying to survive a global pandemic, they can respond by either fighting the situation, fleeing from the situation, or freezing and waiting for the situation to pass.
I would like to propose a fourth strategy for organizations to deal with a danger like the pandemic. It is the fourth “F.” The farm response. More on that later.
What kind of organization is yours?
The fighter organizations were the ones that fought the idea of a global pandemic or pushed back against the research that reported how serious the virus was. Think of the meat processing plants that didn’t provide proper protective gear or the religious organizations that refused to take a break from large services.
The results were catastrophic for the organizations and deadly to the employees and worshippers.
It is pretty easy to identify the fleeing organizations. You don’t see them anymore. Unfortunately, this is the organization that just doesn’t have the resources or the energy to fight. You will recognize them by the “For Rent” signs in the windows of the buildings they used to occupy.
The organizations that freeze are a little more difficult to identify. They are still around but are frozen by fear. They are the organizations that, although they are in a position to move forward, are too frightened to take a risk or even look at the periphery of their business. Their tunnel vision blinds them to opportunity. The freezers hide and wait for the danger to pass. They are the ones who miss out on possibilities.
For example, if you are in the business of supplying concessions to sporting events, airports and national parks, your business is in deep trouble now. So, what are some ways to keep people buying food and drinks with so many venues closed?
Many national parks are now open and visitors need to eat. How can you sell food while supporting social distancing? Answer: Sell picnic meals to your patrons. And, sell a blanket that commemorates the park that diners can spread out and have lunch while social distancing with their families. Then, they’ll keep the blanket that reminds them of their visit to the park.
Sound like a good idea? It sure does. You can keep your park concession business, allow people to social distance and add to your product line with that commemorative blanket. Did the company implement the idea? Unfortunately, they did not. They froze and missed the opportunity.
However, businesses are finding ways to optimize their organization and capture opportunities. They are the farmers. The farmer organizations study the situation, just like farmers study the weather and the land. They look at the resources available to them and get to work.
Farmer organizations pivot and get creative.
Distillers, who before the pandemic, were making vodka, whiskey, gin and other spirits quickly changed their operation from distilling booze to distilling sanitizer.
Telemedicine, which had limited acceptance before the pandemic, almost immediately became the accepted way to deliver care. Now, the doctor comes to you.
Fitness trainers are conducting their sessions via Zoom or in person outside on sidewalks in front of their gyms so they can social distance.
My favorite ranch, SK Herefords, sells their beef at local farmer’s markets in the Western New York area. This spring when the large packing houses shut down and grocery stores were limiting the amount of beef customers were able to buy, my farmer friends were there at the markets with locally produced farm-raised beef. Sales soared and demand skyrocketed.
Why? The farmers were ready. They used their resources and were not afraid to optimize them in a rapidly changing and volatile environment. Farmers live with constantly changing weather conditions and market prices and are accustomed to rapid change.
To operate with constant change, all of us, like farmers, need to be constantly creative. Phil Keppler, my philosopher farmer friend from SK Herefords says, “Creativity helps you to not look at things as a problem. It’s trying to find the solution – and that’s the exciting thing about it. Things aren’t problems anymore. It’s just difficult situations and you’re trying to find a solution to that situation.”
A good mindset for what our world is experiencing now… it’s a difficult situation and we are creating solutions daily.
Fight, flight, freeze or farm. What kind of organization is yours? And, what can you learn from “the farmers?”
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