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WHY AGILE, SCALABLE DATA MANAGEMENT IS KEY TO DIGITAL BANKING

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By Jason Hand, Global Account Executive – Enterprise Sales, Commvault

 

Back at the start of 2019, before we’d ever heard of COVID-19 (hard to imagine these days, I know), mobile banking was predicted to overtake high street branch visits within two years. But the restrictions placed on daily life to get to grips with the pandemic proved to be a catalyst in speeding up adoption.

Although banks haven’t had to close during the UK lockdowns, they discouraged unnecessary visits — and many people new to online banking discovered that it could provide a quick and easy (and COVID-safe) way to manage their finances. No surprise then, that as summer came to an end, over three-quarters of the UK population were using some form of online banking and one in ten people had switched to a digital-only bank.

When it’s implemented well, online, digital and app-based banking is as easy as shopping with Amazon, booking a cab on Uber or grabbing a takeaway via Deliveroo. With so much potential to create a similar customer experience — and so much to lose if they fail — banks are under pressure to deliver on digital services. But their success (or otherwise) will depend on how well they manage their digital data and, in particular, how willing they are to adopt more agile, scalable, cloud-based solutions to underpin their new services.

 

Adopting New Technology in a Risk-Averse Sector

The UK’s financial services sector is undoubtedly slow when it comes to adopting new technology. Indeed, many UK banks continue to rely on mainframes. This cautiousness stems from the continued rise in cybercrime and the fear of non-compliance with FCA and data protection regulations.

Banks have to tread a thin line. They do want to embrace technology that will help them scale and support customer demand for digital services. But they can only do so with an IT infrastructure that keeps out cybercriminals, hackers and anyone else without explicit authorisation to view the data. So, if their legacy IT systems are secure and protect customer data from cybercriminals, banks do not want to risk implementing new solutions that could leave them exposed — even if those old systems make them less nimble and less responsive to changing customer demands.

 

Open Banking and Shared Financial Data

The increased digitalisation across the sector leaves banks facing a second security and data management challenge. Once, they only had to worry about managing their data and keeping it safe within their closed IT environments. Now Open Banking — a UK government-backed programme — encourages banks to securely share their data with trusted third-party financial services providers via an API (Application Programming Interface).

Typically, these third-party providers offer apps to assist with utility bill management, accounting and auditing, and savings (usually rounding up apps). Once a user grants authorisation, the app directly interfaces with that user’s current account. Customers — whether individuals or SMBs — love them, but for banks, they’ve meant a reassessment of security and data management strategies.

 

What Constitutes Good Data Management?

To begin with, it could mean switching to a single data management solution. Banks historically have deployed several different products to manage their data. Multiple applications add complexity and  need more people to oversee them operationally. This approach will add cost, risk, and ultimately will not align to their digital transformation agendas.

Running multiple data management solutions makes it harder to get a holistic view, understand customer behaviour and predict future trends. It also creates unnecessary security risks. Consolidating data management platforms reduces these risks and costs. At the same time, fewer inter-app data transfer points decrease the number of potential weak-link entry points for hackers and cybercriminals. From a practical point of view, using a single data management solution also enables all relevant data points in a hybrid world to be viewed on a single pane of glass — making it much easier to digest, interpret and deliver data management as a service back to their internal clients.

Automating data management components can improve security and cut costs by reducing human contact. In addition, it enables faster and more accurate data management that can accelerate cloud adoption where data management is key to success.

It’s worth saying at this point that banks have been slow on the uptake of both public and private cloud technology, and are clearly still concerned about security and privacy threats. This is despite the fact that cloud computing — particularly with a zero-trust approach to security — has become a lot safer and carries far less risk.

In the middle of 2019, the Bank of England published a report that estimated the world’s largest global banks conducted just a quarter of their activities in the public cloud or software hosted in the cloud. But change is happening, albeit slowly. Larger banks have started to recognise that cloud computing holds the key to running an agile business  — allowing them to scale their online services and safely store, process and mine vast amounts of digital customer data.

The maturation of the hybrid cloud market may have played a role in increased adoption and allayed many of the sector’s previous doubts. A hybrid cloud infrastructure combines public cloud, private cloud and on-premises architecture, giving users the flexibility to keep some applications and systems (those with particularly sensitive information, for example) within their own four walls while still being able to migrate other systems. It’s an elegant and cost-efficient way to balance security, scalability and compliance.

 

Demand for the Future

With so much change taking place across the UK banking sector, data management has never been more critical. Open Banking, consumer demand for digital banking, and app-based banks like Starling and Monzo are all shaking up the market. But the threats from cybercriminals and the risk of falling foul of FCA regulations are still very much present. And, while navigating all these challenges, banks still face pressure from shareholders and investors to make a profit, retain customers and grow the business.

For these reasons, data management strategy — and linked to that, the pace and effectiveness of cloud computing adoption — are now two of the most significant determining factors in how banks cope today, and how effectively they will operate in the future. As such, 2021 should be the year that most banks and financial organisations embrace and invest in new technology when it comes to data management.

 

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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