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HANDLING DIGITAL TRANSFORMATION AMID GLOBAL UNCERTAINTY

Karl Van den Bergh, CMO, Gigamon

 

For most financial services firms, digital transformation (DX) was already a challenging, complex and costly – albeit necessary – journey required to keep up with a rapidly evolving technological landscape. However, these difficulties have been compounded by the current global uncertainty, which has seen the explosion of remote working and distributed infrastructure, as well as rapidly changing IT networks. What’s more, banks and financial services are facing increasing pressure as economic downturn prevails and the threat of the greatest recession in three centuries looms over the UK, with GDP falling by 20% in April.

The pressure the current global situation has placed on IT systems that were never designed for this scenario is intense and, as a result, key digital transformation shifts are taking place. Now, more than half of financial services organisations plan to accelerate the implementation of their next generation of technology strategies, and this is already underway. One third of jobs advertised at UK banks are tech-related – an increase of 46% over the last three years – and the way they recruit is changing. Banks are turning to pros from big-tech companies, proving they acknowledge the need to provide their consumers with seamless tech experiences, similar to those from Apple and Google.

In practice, recent DX shifts have included the rapid scaling of remote access infrastructure, enabling apps to meet heightened demand and adapting to new, expanded security perimeters. IT and security teams have had to adapt rapidly to these new challenges in order to maintain network performance, security and a seamless end-user experience – and they have had to do all of this in a minute time frame with reduced resources.

 

Karl Van den Bergh

Adjusting to the fluid workplace

The most notable shift experienced over the last four months has been towards a remote workforce, as people have been forced to stay home as much as possible. Before this shift occurred, 59% of organisations had more East-West traffic than North-South traffic, which shows the scale of this transition. IT and security teams were able to make the move from LAN to WAN quickly, but often only as a temporary fix. However, now it is looking likely that a fluid workplace will prevail during the return to work phase through to the end of the year and beyond, IT teams must solidify these temporary processes in order to emerge victorious from this economic uncertainty.

The patchwork response many IT teams took in response to the work from home (WFH) shift was magnified within financial services, as big banks typically have a legacy IT problem. In fact, nearly 50% of banks don’t upgrade old IT systems as soon as they should. Repurposing older or existing infrastructure will cause issues such as failures and bottlenecks within the new network architecture. To avoid these detrimental issues that could lead to reduced productivity from employees – which could encourage customers to look elsewhere – financial services firms must ensure they have accurate visibility into the network. Having a clear view of all data in motion will enable IT and network teams to undertake capacity replanning, identify critical traffic and optimise bandwidth usage to ensure the network runs smoothly.

 

Optimising mobile apps

Banking customers increasingly want speed and convenience, and COVID-19 accelerated the shift to online as customers were unable to engage with their banks physically. A recent McKinsey survey found that one in five customers in Britain have tried online banking for the first time during the COVID-19 crisis. New application containers, microservices and virtual machines are being set up to quickly meet this sudden growth in demand. However, this can lead to a mismatch in application capacity and infrastructure capacity, as IT teams may find it hard to keep up with fast-working DevOps and applications teams. In the worst case scenario, as app capacity increases, infrastructure capacity and user experience may lag and bandwidth issues could appear. What’s more, traffic and app usage may not be adequately monitored for security threats, which could be hugely damaging in an industry as critical as financial services.

In order to counter issues that may arise from increased app use, IT teams must ensure they thoroughly monitor and visualise app usage, and take appropriate action in response. Surges in traffic at a particular time of day may cause security tools to become overwhelmed and fail. By visualising where and when these surges occur, IT and security pros can decide whether the traffic needs to be assessed by certain tools, as well as filtering out safe or low-risk traffic to preserve bandwidth for other apps. By optimising apps and security tools in this way, financial services organisations can do more with less and maximise the ROI from their existing investments.

 

Maintaining borderless security

Employees have successfully adjusted to remote working, and many are set to continue this as businesses maintain a fluid workplace going forwards – with the workforce able to work freely between the office and their homes. This means the network has turned literally ‘inside-out’: traffic that was previously inside the firewall is now entering the network from outside. It is no longer enough to rely on a perimeter-based approach to security, as the network is going borderless. With employees now connecting to the corporate network from personal devices and routers, ensuring network security has never been more important as it’s impossible to guarantee these users are following the correct protocol and using patched devices. In fact, 94% of IT pros in the financial services industry say they lack confidence in the ability of employees to safeguard customer data.

The need for unhindered security is driven home within the finance industry due to the sensitivity of the data it holds and the potential damage that could be caused if a malicious actor found their way into the network, especially as attacks exploiting banking trojans rose sharply during May this year. Therefore, the need for a Zero Trust approach is more prevalent than ever. This network architecture sees the behaviour of everything on the network – regardless of whether it’s inside or outside the perimeter – scrutinised, with access granted based on its behaviour rather than any pre-existing credentials.

The finance industry is set to face a challenging year as the full impact of the COVID-19 crisis becomes apparent, but this doesn’t negate the need for DX. In fact, accelerating digital initiatives has never been more important as financial services firms simply can’t afford to suffer network downtime or security incidents during this challenging time. Optimising existing investments and ensuring IT teams have complete visibility into the network, can help financial services organisations accelerate their digital journey and enable them to emerge victorious from this economic downturn.

 

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Finance

HOW COVID-19 HAS RESHAPED THE PAYMENTS LANDSCAPE

By Mohamed Chaudry, Group Chief Financial Officer of FoodHub

 

The year 2020 may well have sounded the death knell for the saying cash is king. As the pandemic took over our world, consumer behaviour altered considerably as people embraced contactless payment, e-commerce and delivery services for many of the things we once handed over notes to buy.

Finextra reports that research carried out by YouGov for the ATM network Link found that 58% of Brits are using cash a lot less often thanks to the pandemic, with 54% avoiding it altogether and using alternative payment methods.

Some 76% of those questioned by YouGov added that they think the crisis will affect their future use of cash over the next six months.

 

Adapt to survive

Many businesses, particularly those in the food sector, quickly worked out they needed to pivot and adapt if they were to survive. Social distancing measures, lockdowns and the economic downturn hit the hospitality industry hard.

Safe and convenient online payments provide food businesses with a solid foundation from which to operate. The year 2020 saw the rise of payment gateways and the size of the market is likely to escalate in the coming months, giving online merchants more choice over the gateways they choose to work with.

Many of these platforms are embracing the changes in innovative ways, adapting to the altered way of life and creating different ways to facilitate recurring online payments and members’ due models. They can also put in place order ahead services for restaurants and expanded delivery options.

 

‘Seamless’ payments process

As lockdown restrictions continue to drive more people online, the e-commerce industry needs to offer seamless online payments to maximise its soaring popularity. The right payments provider should be able to guarantee security, offer access to fast-growing markets and a plethora of relevant payment methods for each market, all components that provide expansion opportunities and a better consumer experience.

Payment providers allow food businesses to focus on their core business and meet new customer demand while they take over the non-core competency tasks. Platforms such as online food portals need to design their site or app to make it as easy as possible for merchants to onboard and customers to use.

As the use of online payments racks up, online security has never been more important. Increases in one inevitably result in the increase of fraud or cyberattacks. Platforms and businesses must ensure customer data is protected. Payment partners can ensure security is key, their greater size and expertise providing the added edge to small businesses that do not have that capability.

 

Building a loyal customer base

Payment security is what will encourage—and keep—customers who haven’t previously used online food portals. Building a loyal, local customer base can encourage businesses to consider expansion—perhaps opening more venues in their region or county or even nationwide.

Promoting the ways in which a platform can benefit customers and a community—in the midst of a pandemic, for example, many people will be conscious that their local takeaway/restaurants, etc., are suffering and they’ll be anxious to help—is another way to broaden a platform’s appeal. An app that doesn’t charge a service fee or take a commission from its partners is one way to do this.

Covid-19 has accelerated consumers’ whole-scale move to online payments faster than anyone can have imagined, and they want convenient, relevant and secure payment services for markets that have previously been served mainly by cash or card.

The pressure is on for retailers (and especially food retailers who want to survive) to ensure they can meet this demand.

 

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Business

NAVIGATING UNCERTAINTY WITH ACCURATE MACHINE LEARNING

Richard Harmon, Managing Director, Financial Services at Cloudera 

 

2020 will undoubtedly prove to be an unforgettable year. The pandemic has been unforgiving, plunging the UK into a recession, and many industries have faced closure and untold disruption. In the Financial Services sector in particular, 86% of profit warnings in the first seven months of 2020 cited Covid-19. But Covid-19 is not the only thing on the sector’s mind – another sizable challenge looms large on the horizon: Brexit. Individually both are highly disruptive events, together they create a double shock wave with a long tail of unknowns: how long the COVID-19 pandemic will last? What the fallout from Brexit will be? How resilient is the UK economy in the longer term? A key topic for discussion is therefore, how will we adapt to these seismic events and how can technology help?

 

Predicting the unpredictable

When it comes to planning, Machine Learning (ML) models have become an integral part of how most financial institutions operate, because of its ability to improve the financial performance for both businesses, and their consumers, through data. United Overseas Bank is a key example of a business that has used ML to make it’s customers’ banking experience simpler, safer and more reliable. Through analysing the thousands of files that are uploaded to the platform everyday, the ML models have a more comprehensive view of customer and transaction data to optimize their business processes, design distinctive customer experiences, and to improve detection of financial crimes.

However, in these circumstances of heightened uncertainty, the accuracy of ML models come into question. This is because the majority of ML models that are in use today have been built using large volumes and long histories of extremely granular data. With the world being as unpredictable as it is right now, it will take some time for ML models to catch up and adjust to this year’s events. The most recent example of such complications and abnormalities, at a global scale, was the impact on risk and forecasting models during the 2008 financial crisis. Re-adjusting these models is by no means a simple task and there are a number of questions to be taken into consideration when trying to navigate this uncertainty.

 

Adjusting to the ‘new normal’

The first step is to determine whether the disruption we are facing right now can be defined as a ‘Structural Change’ or a once in a blue moon ‘Tail Risk Event’. A structural change would represent a situation where the COVID-19 pandemic has had a seismic impact on how the world as a whole, and financial institutions in particular, operates. This would result in the world settling into a ‘new normal’, one that is fundamentally different from the pre-COVID-19 world. This shift would require institutions to develop entirely new ML models that rely on sufficient data to capture this new and evolving environment. On the other hand, if the COVID-19 pandemic is perceived to be a one-off ‘tail risk’ event, then as the world recovers and businesses, financial markets and the global economy return to some sort of normality, they should operate in a similar way to the pre-COVID-19 days. The challenge for ML models in this situation is to avoid becoming influenced and biased by a rare, and hopefully, once-in-a-lifetime event.

 

Readjust and reinvest

There’s no one size fits all solution for businesses, however there are some key steps financial institutions can take to them navigate today’s current climate:

  • Modify existing models: This is where all data science teams should start. Modifying models can range from using the latest data elements while creating scenario-based projections adjusted for various levels of model bias. There are a range of alternative ML-based approaches that can be used to revamp existing models.  One of the more innovative approaches to the lack of rich relevant data is a meta-learning approach. From a deep learning perspective, meta-learning is particularly exciting and adoptable for three reasons: the ability to learn from a handful of examples, learning or adapting to novel tasks quickly, and the capability to build more generalizable systems. These are also some of the reasons why meta-learning is successful in applications that require data-efficient approaches; for example, robots are tasked with learning new skills in the real world, and are often faced with new environments.
  • Stress testing: This is a fundamental step as it helps businesses gain a clearer understanding of their vulnerabilities before it’s too late. This isn’t just the job for one team, cross collaboration from finance leaders to Chief Risk Officers is required to set up multiple, dynamic stress testing scenarios. The learnings from these tests should then be implemented and then retested, to ensure businesses are in the best position possible.
  • Industrialisation of ML: If businesses haven’t already done so, now is the perfect time to invest in a platform that supports the entire ML lifecycle, from building and validating processes, to managing and monitoring all of their models across the entire enterprise. Nowadays, enterprises are faced with increasing amounts of data on their customers, entering the organisation from a range of different sources, from the customer service team to social media platforms. For ML models to work at their best, they need to take every stream of data into account, while being able to understand what the different data is saying, and quickly. This can only be achieved with a unified enterprise data cloud platform.
  • Prescriptive Analytics: This approach is complementary to ML and uses simulations for more accurate decision-making for different scenarios, brought on by shocks or market changes. One common approach is Agent-Based Modeling (ABM), a bottom-up simulation for modelling of complex and adaptive systems. ABMs help businesses project thousands of future scenarios without having to depend upon the limitations of historical data.

 

Businesses have had to cope with a lot this year and those that have survived have faced a steep learning curve. When faced with such a crisis, they need to look inwards, towards the technology they have invested in, review whether it’s working in the new circumstances, and whether crucial tools such as ML models are being deployed in the best way possible. Financial institutions shouldn’t look at the issue as a one-off, but instead as a chance to implement longer-term strategies that enable them to prepare and tackle the next crisis head on. Businesses that invest the time now to re-evaluate their ML models are the ones that will set themselves up for success, now and into the future.

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