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SHIFTING EXPECTATIONS AND THE RISE OF FLEXIBLE BANKING

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Rajasekar Sukumar, Vice President Europe, Persistent Systems

 

In virtually every aspect of connected life, consumers are demanding personalisation — and banks are under pressure.

While financial services led many sectors in recognising the potential of technology decades ago, rapid advances more recently in areas like retail have put banks under increasing pressure to deliver services that are tailored to the individual.

The general view is that banks are just too slow to transform, but it’s an assumption I readily challenge. Over the last few years, banks of all sizes have developed and launched new digital services and mobile apps at a pace I’ve not see in the financial services sector before.

The perception of slow and steady persists, however, and it’s because banks are missing the focus on personalisation. With consumers so used to the personalised services of brands like Amazon and Netflix, this gap is widening even further — and it’s what’s giving challenger brands their advantage.

Created and developed to offer everything to every consumer, large banks are being challenged to deliver the rapid pace of change that is needed to put personalisation at the heart of their offerings.

Conversely, smaller challenger banks have no legacy strategy or proposition to adapt. They are entering the financial services market with clear and focused propositions, designed to appeal to a niche demographic for maximum differentiation and appeal.

So, what does this mean for the banking landscape of the future?

 

Shifting expectations

Taking a ‘one-size-fits-all’ approach to banking has been relied upon for decades, with the assumption that appeal is maximised if everything is offered to everyone. Yet this standardised approach is not connecting with customers.

As I mentioned, banks aren’t being reluctant to change this situation through digital transformation — it’s just that it’s not easy.

The challenge here is two-fold. Firstly, in how larger banks were built, with a one-size-fits-all architecture to deliver every product or service a bank could ever want to offer to any customer. Adding new systems through integration brings some flexibility, but under the hood this core banking infrastructure is restrictive.

The other issue is that larger banks are the victims of previous success. They have worked hard to appeal to every type of consumer, and they’ve got them on their books. But personalising and segmenting such a broad group is a huge, unwieldy undertaking.

In contrast, newer banks don’t have to shake off legacy perceptions or rework legacy systems. A digital-first approach brings agility and flexibility from the outset, with the ability to rapidly create a banking proposition that is designed for a very particular type of customer.

A great example is UK-based Monument. Launched this year, this digital bank has purposefully hand-picked a focused segment: the mass affluent with between £250,000 and £5 million in liquid assets.

Every Monument message and product has been developed with its niche audience in mind, pushing aside the myriad banking services they could offer to focus only the ones that really resonate and matter to those with high incomes.

 

A digital mosaic architecture

Instead of being shackled with a ‘one-size-fits-all’ infrastructure, challenger banks have the opportunity to develop what we at Persistent Systems call a digital mosaic architecture.

Instead of building in everything from the outset, a digital mosaic provides a flexible structure to add and integrate the right services, applications and data platforms to meet the needs of a particular customer group.

It’s easily composable, and that brings new levels of efficiency, flexibility and agility — and a step change in the personalisation of the customer experience.

With this clear advantage, digital banks can take a truly tailored approach from the start, selecting only the products and services they need, whether that’s debit cards, loans or cross-border payments. With each component acting like a Lego brick, they have the opportunity to select only the best technologies for each product or service they want to offer.

For larger banks, this becomes more complex, as “under the hood” their technology infrastructure lack the flexibility they need to adopt a mosaic architecture quickly. Furthermore, the workflows within this infrastructure were originally created with the bank’s processes in mind, rather than the customer’s priorities, demands and expectations.

With a more composable, mosaic architecture, everything starts with the customer experience — and the technology becomes the enabler, not the blocker, of personalisation.

 

A customer-first approach with the cloud

To even the playing field and gain more competitive advantage, established players in the financial services sector are increasingly looking to the cloud to remove their dependency on complex, legacy IT infrastructure.

I’m seeing previous trust issues with cloud delivery dissipating, as banks recognise the cloud is now both highly trusted and critical to digital transformation projects. Flexibility and security is created in core components such as a credit decisioning system, KYC solutions and anti-money laundering technologies, and banks benefit from the ability to deploy and scale at speed.

The cloud brings the opportunity to break free from a single technology, to compose and integrate a unique and powerful combination of cloud-based services and applications for the optimum customer experience.

Partnering with a trusted systems integrator means this doesn’t have to be an insurmountable challenge either. Use experts to create and implement a best-in-class cloud infrastructure while you focus on what’s really core to the business: running the bank for your customers.

In today’s fast-moving banking landscape, the power and flexibility of a digital mosaic has never been more critical — and the opportunity is now.

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.

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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