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How today’s forward-thinking banks can turn customer experience into a gamechanger

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Sandro Tarchini, global industry lead, financial services at Valtech

 

The banking sector has never faced more disruption than over the last five years. In particular, the pandemic has exponentially accelerated banking’s digital transformation, completely changing the game for today’s banks.

Traditionally, banks would acquire new customers through a broad set of offerings and physical proximity. But proximity has quickly become less important, particularly for simple or recurrent transactions and interactions. Many customers now expect and prefer the convenience of online banking and mobile banking solutions – significantly reducing their reliance on physical contact points and limiting the opportunities banks have to interact with their customers in a physical branch.

This shift has levelled the playing field, opening the door to a wide range of digital-first competitors such as neo banks. As a result, price has become a key competitive driver, with many banks stuck in a never-ending cycle of trying to outcompete each other on interest rates, commissions, or fees.

But this approach overlooks a key part of the picture. The impact of Covid-19, combined with the recent surge of innovative fintech brands, has increased the value of high-quality digital interactions. It has permanently shifted customer expectations when it comes to the banking experience, offering traditional banks and financial institutions a new way to differentiate themselves.

The growing role of CX

According to Insider Intelligence’s Mobile Banking Competitive Edge Study, 89% of consumers said they use mobile banking, rising to 97% of millennials. These users don’t leave their bank for fees. Instead, they’re most likely to leave because of dissatisfaction around mobile banking capabilities (43%), online banking capabilities (35%) and customer service (33%).

In addition, 75% of respondents to the 2022 World Retail Banking Report said they are attracted to new agile competitors as they offer fast, easy-to-use products and experiences that are readily available while remaining low in cost.

With proximity now a much smaller part of the equation, CX is the one true way that banks can differentiate themselves. Customers still want to be understood, respected, appreciated, and valued – they want the emotional connections that were traditionally built through in-person interactions. The key is learning how to achieve this through digital channels.

With the majority of bank customers preferring digital interactions over physical or phone conversations, the delivery of these interactions is the big differentiator. They must be delivered in a way that’s both transactional and emotional, showcasing to customers that their bank genuinely wants to help them achieve their financial goals.

This is what will open the door to consumer confidence and loyalty. Although the journey towards customer-centricity takes time, banks that invest in good CX have higher rates of recommendation, greater wallet share, and are more likely to up-sell or cross-sell products and services to existing customers.

Ultimately, customers have increasingly high expectations and are demanding more from their banking experiences. The onus is therefore on banks to rethink their business models and focus on providing an overwhelmingly easy, convenient, and distinctive CX. The key to success lies in understanding customer needs, and then fulfilling those needs in a way that no other brand can.

Becoming customer-centric

Financial services customers are generally looking for four things: help in maximising the benefits of existing products, relevant product offers at the right time, personal knowledge of things they care about, and customised product features. Therefore, banks strengthen their customer knowledge so they can serve customers holistically.

The starting point is to establish a CX vision. This will help shape business goals and connect them to key experiences that will distinguish the brand and keep customers loyal. For example, this could include defining how certain features will work, identifying the right training for employees, or structuring CX teams in a certain way.

Once the vision has been defined, banks should then set up an analytics framework to measure their progress. Any effective analytics framework will have highly defined KPIs, data sourcing and reporting – along with market analysts who can generate and interpret insights that will enable real-time customer guidance and help banks track their success.

The final pillar is workforce transformation, which should be addressed from an operational and cultural perspective. Operational in terms of defining ways of working, organisational and process improvements, and access to applications for employees to work more effectively. Cultural in terms of identifying skills gaps and building a culture that encourages employees to adopt new technologies and a customer-centric mindset.

This process will help banks identify any gaps, as well as the opportunities to implement consistent, cross-functional omnichannel experiences. And there are plenty of examples of banks that have successfully transformed their CX. For example, Scotiabank rolled out a global AI platform called C.MEE, which analyses data across all customer touchpoints to deliver personalised and relevant banking experiences. Or there’s Capital One, which significantly increased its CX investment after identifying that 47% of its customers are early adopters of technology and 88% regularly use their smartphone for banking interactions. These insights have helped it innovate in CX and become a recognised leader in customer satisfaction.

As we look ahead, the prevalence of digital banking – along with the expectation for more compelling customer experiences – will only increase. CX must therefore become ingrained within banks’ culture and thought of as a product of its own. It is now a greater differentiator than price or products, putting the onus on banks to deliver superior experiences that meet customers’ evolving needs. Their very existence could depend on it.

Banking

Augmented automated underwriting and the evolution of the life insurance market

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By Alby van Wyk, Chief Commercial Officer at Munich Re Automation Solutions

 

It’s almost inevitable. Spend your working life identifying, analysing, quantifying and ascribing monetary value to risk, and you’re likely to have a fairly strong aversion to it. Or more accurately, an aversion to undertaking new endeavours with inadequately understood consequences. The insurance industry is, on any number of levels, the very definition of risk-averse.

And yet, for all the commentary suggesting otherwise, insurance still has an appetite for innovation. If the insurtech sector is any indication, then an interest in and requirement for new solutions is being recognised and slowly addressed.

Declan O’Neill

It may not employ the language of disruption that runs through the wider fintech market, it may be short a few unicorns and unable to boast some of the record-breaking funding rounds, but a quiet tech evolution has been building in insurance nonetheless. Hence the advent of automated underwriting facilitated by more advanced algorithms and data analysis.

Where insurtech does overlap with its more vocal fintech counterparts is in the greater use of artificial intelligence (AI) and machine learning to solve age-old problems around data analysis and interpretation.

It’s about five years or so since AI first became a topic of conversation in insurance. Since then, despite the intensity of the debate, it has often felt like a reality that is always just over the horizon – a destination that kept moving even as more and more efforts were directed towards it.

But recent research suggests that the journeys made so far have not been in vain. We are at a point where embracement of AI is about to step up a gear. The global value of insurance premiums underwritten by AI have reached an estimated $1.3 billion this year, as stated by Juniper Research; but they are expected to top $20 billion in the next five years. As a destination, it is closer and more attainable than ever before.

However, AI is not an island. Its promise of $2.3 billion in global cost savings to be achieved through greater efficiencies and automation of resource-intensive tasks will not be achieved in isolation.

AI remains part of a more complex ecosystem of data gathering and analysis. It can apply new technologies to get the best out of the already established and still-emerging data sources that feature in underwriting offices around the world. It emphatically does not require these existing investments to be ripped out, replaced or downgraded.

It is more helpful therefore to see AI as the differentiating factor in the latest generation of insurance IT: augmented automated underwriting, or AAU for short.

AAU gives underwriters the ability to spot patterns and connections that are, frankly, either invisible to the human eye or which take normal, human-assisted processes unfeasible amounts of time and resource to identify.

Whereas earlier generations of automation were able to pick up the low-hanging fruit of insurance markets – the individuals whose driving history fit into clearly delineated boxes, for example – AAU can take into account all of the rich complexity of the human experience. It can spot the nuances and individualities that populate the life market, for example, and translate those into accurate policies.

That’s good news for both underwriters and their customers. AAU can significantly reduce the need for separate medicals, repeated questions, lengthy decision-making processes, and drastically increase the speed at which a potential insurer can get a quote and cover – while continually improving the way risk is calculated and managed.

It can make sure the decision-making process remains in the hands of underwriters rather than IT departments, enabling them to set and update the rules and parameters as befits their preferred business model. It consequently makes advanced, complex and precise decision-making available to a broader range of underwriting businesses – which is good for those businesses, good for customers and ultimately good for the entire industry.

AAU – augmented automated underwriting – is an example of the realisation of AI’s promise. As such, it’s set to become one of the key talking points and disruptive technologies of the insurance industry. And this time, AAU is both a journey and destination that all progressive insurance organisations need to be considering for their future operations.

 

 

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Banking

ESG in the finance and banking industry – are you ready?

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By Julian Moffett, CTO BFSI, EDB

 

Environmental, Social and Governance (ESG) has soared towards the top of banking, financial services, and insurance (BFSI) and other boardroom interests. Organisations everywhere know they need to take ESG and greenhouse gas emissions (GHGs) seriously not only because it is the right thing to do for the future of the planet or because it can help attract and retain talent, but also, because failing to do so may pose a risk to the economic value of their businesses and encourage probes by governments, watchdogs and non-execs. However, complying with complex reporting and going the extra mile to actually deliver on the goals of the rules is a challenge in many ways, not the least of which is in achieving the required excellence in data management to underpin strong reporting on ESG.

 

What is ESG? 

Julian Moffett

ESG is an umbrella term that covers a broad gamut of activities. Gartner defines ESG as “…a collection of corporate performance evaluation criteria that assess the robustness of a company’s governance mechanisms and its ability to effectively manage its environmental and social impacts.”

The CFA Institute describes the environmental element as focusing on “the conservation of the natural world” and includes measuring “climate change and carbon emissions,” “air and water pollution” and “biodiversity” among many other measures. Social considers “people and relationships” looking at areas including “customer satisfaction,” and “gender and diversity.” Governance covers “standards for running a company” and analyses factors such as “board composition,” “audit committee structure” and “audit committee structure.”

 

Status of the current regulatory environment

There are many bodies proposing rules to formalise ESG monitoring and seeking to ensure corporate compliance. Some example groups, frameworks and bodies:

  • The Task Force on Climate-related Financial Disclosures (TCFD)
  • Streamlined Energy and Carbon Reporting (SECR)
  • The International Regulatory Strategy Group (ISRG)
  • The Sustainability Finance Disclosure Regulation (SFDR)
  • The International Sustainability Standards Board (ISSB)
  • The Sustainability Accounting Standards Board (SASB)
  • Sustainable Development Goals (SDGs), the Global Reporting Initiative (GRI) support efforts such as the US SEC’s Climate and ESG Task Force.

Financial services organisations are very aware that the current regulatory landscape is far from mature (and will continue changing) both in terms of alignment between bodies and also with regard to when the new rules will come into effect. At the of time of writing:

  • The requirement for Scope 2 disclosures (see below for description) for the Sustainable Finance Disclosure Regulation (SFDR) will likely come into effect in 2023
  • A proposed Corporate Sustainability Reporting Directive (CSRD) should be agreed by the European Parliament this year for implementation in 2024 to report on performance in 2023.
  • Meanwhile, the SEC has just released its proposed rules for climate-related disclosures, which,if passed in legislation, may come into effect as early as year end 2022.

 

Reporting Obligations 

Reporting can cover a wide range of areas covering energy consumption, GHG emissions, water consumption and waste management to health and safety, labour rights, diversity and inclusion to ethical conduct, and even areas such as appropriate executive compensation.

While the regulatory reporting obligations are not yet finalised, the expectation is that compliance may prove to be an onerous task. For example, organisations are under pressure to monitor carbon emissions but even so-called Scope 1 emissions (those that come from owned or controlled emissions) can be hard to track. Factor in Scope 2 (indirect emissions such as purchased power) as well as Scope 3 emissions from up and down value chains, and the reporting task at hand is difficult indeed.

To measure, monitor and manage in addition to staying on the right side of rules, organisations need to have excellent data management fundamentals, strong reporting tools and a new class of applications, which also have the agility to adapt to rapidly changing regulatory demands. Data will be used both to support decarbonisation measures but also to identify where there are disclosure gaps. It was telling that when the SEC issued a press release on its Enforcement Task Force, it specifically referred to data:

“The task force will also coordinate the effective use of Division resources, including through the use of sophisticated data analysis to mine and assess information across registrants, to identify potential violations.”

Having reliable data comply with emerging rules isn’t the only essential requirement for organisations. Institutions need such data to understand where they are in their journey to sustainability, so that they can set sensible targets and track progress against them. Organisations will have to cover the data trifecta of availability, management and transparency. Many organisations may be stuck in the early stages of managing ESG, overly relying on manual processes, spreadsheets and email. But their target should be to get to real-time data insights that are easily visualised, understood and shared. As a foundation, BFSIs need to capture, manage and securely share data reflecting consumption and safety to emissions, financials and data from surveys measuring results against ESG targets. Data emanating from ERP and other back-office systems, performance data from third-party associates, media and social network coverage, spatial/geolocation systems and beyond should also be factored in.

 

Actually reducing GHGs

Organisations are using a wide variety of ways to reduce emissions and improve their footprints from using renewable energy sources to making secondary use of energy; for example, in the case of one university, this is done through capturing data centre heat in hydroponics. For IT, making broader use of multitenancy in cloud computing and hosting services is a popular way to reduce emissions. Not only do these large data centres offer an economy of scale, they also tend to be state of the art in their use of renewables and highly efficient hardware and other infrastructure. Gartner, in an article titled The Data Centre Is Almost Dead, says it expects 80 percent of enterprises will close in-house datacenters by 2025. For me, the jury is out on this one but an interesting one to monitor going forward.

 

Conclusion

We are at the start of a very significant inflection point in regulatory and consumer expectations around ESG. BFSIs should be under no illusion that momentum is building rapidly in terms of having to address strict reporting requirements and implement strategies to reduce GHGs.

However, we also see this as a time of positive change. As the leading provider of Postgres, EDB is excited to help organisations further their ESG goals as the journey unfolds. We are closely monitoring the implications of ESG regulations as they will give rise to a new class of applications and drive adoption of green data centres. We see OSS, including Postgres, as playing a key role in this shift as often the movement to private and public cloud helps accelerate application modernisation and enables displacement of outdated incumbent technology (including database) platforms. As the leading provider of Postgres, EDB is excited to help organisations further their ESG goals as the journey unfolds.

 

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