by: Stewart Robbins, Financial Services Senior Industry Consultant at Teradata
How often have you heard messages like “to be the best bank for customers” or “legendary customer service is at the heart of our business strategy”? That’s great, and imperative as the lines blur between Big Tech, Retail, Telco and Banks.
Back in the real world, Banks are well down the CX league tables. For example, the average NPS score for European banks is 15-20 points lower than that for supermarkets*.
Most CX leaders typically face the question, “How do you protect the customer experience when costs are being cut?” I’d argue that the right question is, “What is good customer service worth?”
Without an answer to this question, then CX leaders must make do with whatever budget they can scrape together, and hope they are able to improve the customer experience within it.
Do not despair!
The role of analytics in CX is long-established but specifically addressing the cumulative and incremental value of that experience has often been overlooked – although not by everyone, as you can see from this example from a major Utility:
This relationship between NPV and customer experience (measured here by Net Promoter Score, NPS) allowed the Board to understand the return from moving from second-to-last in the league to first place. Plans and the necessary budgets followed to achieve that goal. And it did work, although history reveals this is a battle that does not stay won!
Interestingly, this picture also suggests that there is not really a great justification for seeking excellence, which makes sense – fabulous electricity is not any different from the other sort! This picture does differ by industry and customer segment.
Of course, this is only a high-level answer which might garner support for a programme but doesn’t really support individual initiatives. Using a measure like NPS, we need to be able to understand the drivers of changes. This analysis needs to cast the widest possible net – important drivers can be surprising.
I worked on a project for a major hospital a few years ago and their biggest CX driver for in-patients was…. not the quality of the surgeon. No one wants to think their surgeon is anything other than good, so unless they are actively awful (which is thankfully rare) then this has no impact. It was also not the caring qualities of the nursing staff or cleanliness of the facilities for similar reasons. No – it was the food.
Many hospitals skimp on food quality and choices for patients or the delivery process to bring it hot and appetising to the bedside – small investments in this area yield disproportionate impacts… even if hospitals are not really looking for repeat visitors!
What do we need to drive insights like this for banks? I would identify six key capabilities:
- Integrated data
- Temporal analytics
- Customer profitability
- Propensity modelling
- Journey analytics
- Board KPIs
Integrated data is the first requirement, and that should be as broadly-based as possible (like meal attributes for that hospital) to discover the unexpected. Agility in connecting to potential data resources and exploring them in temporary lab environments is key.
We also need to undertake temporal analytics – interventions can yield different outcomes depending on the sequence, timeliness and magnitude of the event, as we try to avoid the “it’s a bit late to be sorry” outcome. That leads us to the inevitable task of trying to anticipate negative impacts through use of predictive analytics, which need to be connected to operational processes for execution.
Customer profitability measures are also critical – these need to be forward-looking (NPV) and recognised by the CFO to ensure business cases are acceptable. Intervention-based “what-if” analysis requires a lot of supporting analytics like propensity to buy and churn modelling as inputs.
All these activities should be using the same data – there is no business case for building lots of point solutions if cost control is to be delivered.
Customer Journey analytics are probably already on the shopping list of any CX leader, but this should be reviewed to ensure it can deliver operational change at scale and directly impacts on the experience, not just process failure reduction. I would observe that the loan application process is working correctly when poor risk customers are declined, but that this intended outcome has negative CX impact that might need to be addressed for some customer segments.
Finally, don’t forget to build the measurement and monitoring into core Board KPIs. Aggregate customer NPV is something that can and should be tracked back to experiences customers receive and can come close to the total enterprise value of the Bank.
WHAT BANKS NEED TO KNOW ABOUT OBSERVABILITY
By Abdi Essa, Regional Vice President, UK&I, Dynatrace
More aspects of our everyday lives are taking place online – from how we work, to how we socialise and, crucially, how we bank. To keep pace, financial organisations have stepped up their digital transformation efforts, supported by a shift to dynamic multicloud environments and cloud-native architectures. However, traditional monitoring solutions and manual approaches cannot keep up with these vast, highly complex environments. As a result, many banks are turning to new, observability-based approaches to understand what is happening in their digital ecosystems. These approaches, however, bring new challenges to overcome.
Here are six things banks need to know about observability to ensure they can gain true value, combat the complexities of their modern multicloud environments, and drive digital success in 2021 and beyond.
- Most banks have very limited observability
The scale, complexity, and constant change that characterises hybrid, multicloud environments presents a real challenge to banks’ IT teams. Our research found that, on average, banking digital teams have full observability into just 11 percent of their application and infrastructure environments – not nearly enough to understand what is happening, and why, across the digital ecosystem. Additionally, 87 percent said there are barriers preventing them from monitoring a greater proportion of their applications – including limited time and resources. Without improving observability across the entire cloud environment – by drawing in metrics, logs, and traces from every application – banks’ IT teams are limited in the success they can have driving initiatives to deliver the new banking products and quality user experience customers want.
- You can’t bank on manual approaches
With many banks beginning to rely on more dynamic, distributed multicloud architectures to deliver new services, IT teams are stretched further than ever. More than a third of financial services organisations say their IT environment changes at least once per second, and 65 percent say it changes every minute or less. This rate of change creates a volume, velocity, and variety of data that has gone beyond banks’ IT teams’ ability to handle with traditional approaches – there’s no time to manually script, configure, and instrument observability and set up monitoring capabilities. The need for automation is therefore critical. By harnessing continuous automation assisted by AI in place of manual processes, teams can drastically improve observability to automatically discover, instrument, and baseline every component in their bank’s cloud ecosystem as it changes, in real-time.
- Cloud native adoption is obfuscating observability
To remain agile and keep up with the rapid pace of digital transformation, banks are increasingly turning to cloud-native architectures. Our research found 81 percent of them are using cloud-native technologies and platforms such as Kubernetes, microservices and containers. However, the complexity of managing these ecosystems has made it even harder for banks’ IT teams to maintain observability across their environments. Nearly three-quarters of banking CIOs say the rise of Kubernetes has resulted in too many moving parts for IT to manage, and that a radically different approach to IT and cloud operations management is needed. Such an approach should be based on a solution that is purpose-built to auto-discover and scale with cloud-native architectures.
- Data silos result in tunnel vision
To boost observability, many banks have simply thrown more tools at the problem. Our research found that most organisations use an average of 11 monitoring solutions across the technology stack. However, more isn’t always better, and multiple sources of monitoring data can result in fragmented insights. This fragmentation makes it harder to understand the full context of the impact that digital service performance has on user experience and unravel the nearly infinite web of interdependencies between banks’ applications, clouds, and infrastructure. Instead, financial organisations should seek a single platform with a unified data model to unlock a single source of truth. This will be integral to ensuring that all digital teams are on the same page, speaking the same language, and collaborating effectively across silos to achieve business goals.
- Observability alone is not enough
Simply having observability doesn’t help banks achieve tangible benefits or reach their business goals. To get true value, the data processed must be actionable in real-time. As such, observability is most effective when paired with AI and automation. This observability enables teams to instantly eliminate false positives, prioritise problems based on the impact it will have on the wider organisation, and understand the root cause of any problems or anomalies so they can resolve them quickly. The alternative is to manually trawl through dashboards and data to find insights, which is incredibly time-consuming and makes it almost impossible to act in real-time. Our research found that 94 percent of CIOs think AI-assistance will be critical to IT’s ability to cope with increasing workloads and deliver maximum value to the organisation. AI is clearly no longer just a ‘nice to have,’ but a business imperative.
- Observability isn’t just for the back end
Far from just having observability of their multicloud environments, banking IT teams also need to be able to see how the code they push into production impacts the end-user experience, and how that in turn affects outcomes for the business. This is a major goal for many CIOs, with 58 percent citing the ability to be more proactive and continuously optimise user experience as a benefit they hoped to achieve from increased use of automation in cloud and IT operations. By harnessing automatic and intelligent observability, banks’ digital teams can unlock code-level insights and precise answers to their questions about user experience and behaviour, so they can continuously optimise their banking services.
Observability is key for modern financial organisations looking to accelerate their digital transformation. By understanding these six key things about observability, IT teams will be better placed to master dynamic, multicloud ecosystems, and drive better digital banking services for the business and its customers.
NEARLY HALF OF BUSINESSES NEED MORE ASSURANCE ON DATA SECURITY TO ADOPT OPEN BANKING
- Financial services businesses in the UK and Netherlands call for better education, training and increased guidance on data security issues to propel adoption
- Study of 800 senior professionals from banks, lenders, personal finance management tools (PFMs) and retailers, in the UK and Netherlands
42% of financial services businesses want better support and guidance on data security in relation to open banking, according to the latest research by open banking provider YTS.
The survey of financial professionals including banks, lenders and retailers, revealed businesses want better education and training, alongside increased guidance, to help reduce fears around the security risks of open banking adoption. Respondents also stated that they wanted this support to come primarily from regulators.
This ranked higher than taking a ‘wait and see’ approach by allowing more time for open banking technology to develop (39%), which has often been cited as a way to assuage data security concerns, but as YTS’ data demonstrates, won’t solve the issues businesses are facing.
Lack of customer and business willingness to accept risks around data security were the second and third most cited factors threatening the progress of widespread open banking adoption, on 27% and 25% respectively. Over a third of respondents (35%) also believe that an ‘unfriendly’ regulatory environment is threatening the progress of widespread open banking adoption.
YTS is calling for the entire open banking and financial services industry to do more to empower businesses to adopt open banking technology, creating a more nurturing environment for the technology to thrive. This can primarily be achieved by introducing better education and accessible, transparent support for businesses looking to adopt the technology. This must be the spearhead of an industry-wide effort to banish myths and create more solid foundations for growth.
Roderick Simons, Chief Technology Officer at Yolt Technology Services comments:
“To fully maximise open banking’s potential, we must all do more to educate businesses and consumers about its security foundation . Open banking means their financial data is more protected than ever, with the individual in charge of whether their data is shared or not and secure APIs preventing risks from unwanted third-party access. We want to work with regulators, financial services institutions, and businesses themselves to lead the way in educating, training, and supporting businesses to overcome misperceptions of open banking. Doing so will unleash the power of open banking and create huge opportunities for both consumers and businesses.
“Once there is widespread adoption and trust in open banking technology, stakeholders across the open banking ecosystem can then turn their attentions to creating an open finance framework that gives consumers the ability to access their entire financial footprint in one place.”
WHAT BANKS NEED TO KNOW ABOUT OBSERVABILITY
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