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Banking

DIGITAL TRANSFORMATION: WHAT CAN BANKS LEARN FROM OTHER SECTORS?

By Paul Jones, Head of Technology at SAS UK & Ireland

 

The banking sector sets a benchmark for other industries in many areas. When businesses need to process large volumes of transactions reliably, maintain 24/7 availability, meet complex regulatory requirements, analyse risks or make financial plans, they often aim to follow the same practices and adopt the same technologies that banks have established as a gold standard.

However, there are other areas where banks aren’t necessarily ahead of the field – and where they can learn from the successes and failures of other sectors. Digital transformation is a prime example. According to McKinsey: “Years of research on transformations has shown that the success rate for these efforts is consistently low: less than 30 percent succeed.” And as almost all established banks see digital transformation as a top priority to help them counter disruption from challenger banks and fintech startups, this is a major concern.

 

Technology as the catalyst for transformation

In their struggles to get digital transformation initiatives over the line, banks typically take one of two approaches. The first is to create a separate internal organisation with a remit to develop new digital products and services, unencumbered by the bank’s existing legacy processes and technology. In some cases, banks have even acquired one of their former fintech rivals to take advantage of its digital skills and provide this internal innovation capability.

The second approach is to focus on incremental digitisation by enhancing existing processes with digital technologies. For example, a bank might seek to enhance contact centre operations by embedding intelligent decisioning capabilities that use artificial intelligence and machine learning to help operatives make more personalised offers to customers. This strategy has the advantage of building on the strengths of existing ways of working, instead of starting from scratch. But it may also be more difficult to implement and require significant investment from senior leaders to drive the required cultural change.

It’s difficult to say which of these approaches is best. And in practice, banks will probably require both, depending on the type of transformation they are trying to achieve. But one interesting insight, again from McKinsey, is that whichever approach they follow, organisations whose transformation initiatives are successful tend to deploy or try more technologies than those who fail, particularly in areas such as cloud, mobile, IoT and artificial intelligence. And this links strongly to the fail-fast mantra in introducing digitalisation.

 

The importance of first principles engineering

There’s a connection here. Banks are buying fintechs to take advantage of their digital expertise, and fintechs have earned that expertise through their willingness to adopt and experiment with new technologies. But that experimental approach isn’t something that the fintechs invented on their own. It’s a lesson they learned from the big technology companies.

For example, while Facebook’s famous mantra of “move fast and break things” sounds like a frightening idea in the highly regulated world of the financial sector, it’s basically the same idea that Tesla calls “first principles engineering.” You take a new idea, try to implement it using whatever technologies seem most promising and expect your first attempts to fail. But because you expected some form of failure, you learn from the experience and do better on the next iteration.

Perhaps some of the new technologies you try end up in the final product, and perhaps they don’t. The point is, you make the cost of the experiment and the price of failure as low as possible so that you have space to explore the problem and come up with the right design for your business.

 

Learning from the tech giants

Take Monzo, for example, which is one of the UK’s biggest success stories in the new wave of challenger banks. In its mission to build a banking system from the ground up, Monzo’s engineering team decided to build a loosely coupled microservices architecture, specifically because “large internet companies like Amazon, Netflix and Twitter have shown that single monolithic codebases do not scale to large numbers of users.”

In its willingness to learn from the tech giants, Monzo experimented with different technologies before settling on Kubernetes – the same technology that Google uses to manage containerised workloads at a massive scale. (Incidentally, at SAS, we’ve been through a similar journey in developing our own cloud analytics platform and came to a similar conclusion. We’re now running our new services on Kubernetes too.)

The same principle applies to the adoption of analytics tools for artificial intelligence and machine learning. Even more so than classical statistical modelling, AI inherently requires an experimental, iterative approach where you learn as much from your failures as you do from your successes. In many cases, the wisest path is to try a wide range of different approaches and technologies, including all the latest open source frameworks, to discover what works best. Once you have found the right approach, you can then industrialise it using a production-grade analytics platform such as SAS Viya, and even provide it to your clients as a service.

 

The human element

We’ve established that banks can profit by following the example of the big tech companies when it comes to designing the technical architecture and processes around digital transformation. But technology isn’t everything. Successful digital transformation also has a strong human element.

To see why this is important, let’s look at a counterexample. Another fintech company that has enjoyed rapid growth is Robinhood Markets, whose mobile app has made it easy for a new generation of investors to start trading stocks, ETFs, options and cryptocurrencies. However, in early March 2020, the Robinhood app suffered a series of systemwide outages that prevented users from opening or closing their positions.

The cause of the problems was a technology failure. In a subsequent blog post, the company’s founders noted that their infrastructure couldn’t handle the combination of “highly volatile and historic market conditions; record volume; and record account sign-ups.” But the impact was human. When the app failed, there was no contact centre to act as a backup for booking trades.

 

The risks of failed tech

The result? Many of Robinhood’s small investors were helpless as the markets turned against their positions, or unable to make trades to take advantage of opportunities they spotted during a week when the coronavirus pandemic sparked a mass selloff. While it’s not yet clear how Robinhood will weather the storm, it’s reasonable to expect that there will be compensation claims, potential lawsuits and, worst of all, a catastrophic loss of customer confidence in the business. As one customer quoted in The New York Times put it: “For me, the moment they get [back online]I am going to try to get out and switch out to someone else.”

Without a human element that can take over when technology fails, businesses expose themselves to significant risk. And even if the technology is completely bulletproof, it’s a bad idea for banks to use it to replace human contact entirely. When customers apply for a mortgage or a loan, they’re often going through a high-stress situation, such as moving house or expanding a small business. While the loan approval decision can and should be handled by sophisticated modelling techniques, the customer wants to hear more than just “computer says yes” (or “no”).

The best customer experience comes when the model is able to explain its decision to a customer service agent, who can then act as an intermediary to break the good or bad news to the customer. This is assistive AI in action.

 

Learning from the public sector

This is a lesson that the public sector has been faster to learn than the private sector. Health care organisations, for example, are investing significantly in the use of AI to assist with diagnoses – for example, using image recognition models to identify potential tumours in X-rays and other medical images. But the principle from the beginning has been that AI can only play an advisory role; the final decision is always made by the physician.

At SAS, we’ve seen the success of this approach in other areas of the public sector too. We’ve recently worked with a large government department to embed intelligent decisioning into its contact centre to give staff the insight they need to provide a better service to each caller. We’ve helped translate the same principles over to the private sector, as well. One of our clients is a car insurance company that uses AI to assess whether a damaged vehicle needs to be written off, and the model now explains its decisions to the customer service team so that it can advise policyholders.

 

Banking

TRANSFORMATION IS NON-NEGOTIABLE FOR BANKS LOOKING TO DELIVER VALUE IN A POST-PANDEMIC WORLD

Andrew Warren, Head of Banking & Financial Services, UK&I, Cognizant

 

In addition to responding to changing customer expectations, higher operating costs, new technology, and an evolving regulatory landscape, financial services organisations now also face the uniquely challenging business environment created by COVID-19. The economic consequences that are unfolding rapidly and unpredictably mean that banks must double-down on both their efficiency and customer experience agendas. In light of this, the need to modernise legacy banking platforms will gain sharper focus as banks emerge into the post COVID-19 landscape, driven by the need to focus on value for customers and agility to change and shift operations quickly.

 If banks are to remain strong and stable and make real progress with their efficiency and experience agendas, transformation is non-negotiable – but it can be risky and have high rates of failure. So how can banks pursue their transformation agenda, while addressing the very real risk that modernisation of legacy banking platforms presents?

 

Communicating value across the business

 Banking transformation may have traditionally been the domain of the IT function, but the impact on current and future value means it should be on the agenda of a much wider set of senior executives. This includes the CIO and COO but should also be as far reaching as the Chief Risk Officer, Chief Financial Officer, Chief Digital Officer, and Chief Experience Officer.

When we talk about value in the context of transformation it can mean multiple things. In monetary terms, transformation can reduce the total cost of a bank’s IT infrastructure, with legacy equipment 55 per cent more costly than cloud data. More importantly however, transformation often results in moving from highly manual orientated processes to more efficient, automated – and therefore accurate – processes. In turn this can lead to more informed and tailored products and services, internal process efficiencies, enhanced cybersecurity, advanced analytics, and reduced risk, especially around fraud and malicious activity. These all add significant value to customers, as well as operational and regulatory imperatives.

Furthermore, viewing transformation through a value lens should tie it to a range of specific financial and accounting metrics that ultimately measure success. That includes both those that reflect the protection and extension of current value, as well as measuring the extent to which transformation will support the capture of future value. Financial services organisations have a huge opportunity to create greater value for customers from innovation in products and services. Changing market dynamics are creating a basis upon which banks and others in the industry can evolve their offerings and organisations.

In much the same way as we have already seen in retail, for example with Amazon and AliBaba, and media platforms, such as Facebook and Netflix, customers are adjusting to a new way of banking that is changing expectations. To keep up, banks need to increasingly provide easy-to-use digital-first services across their products, as well as introduce new tools to help customers manage their money in the 21st century. And there is no doubt that the fall-out from COVID-19 will likely further drive the degree and extent of digital adoption.

Traditionally, financial institutions take many different approaches to transformation, such as developing sleek new customer experiences to compete or developing new platforms and partnering with fintechs. But achieving success for more mature banks is more challenging given the obstacles presented by their legacy platforms. Comprising complex, customised systems, these are expensive to run and very costly to change.

 

The inevitability of change

To truly transform operations and experience, many banks are now having to face up to the reality that they cannot move forward without banking platform transformation. That means they must – in one way or another – replace their historic systems with more modern, cost-effective, and flexible platforms. That is going to be essential to stand up the capabilities required to enable digital products and deliver the truly revolutionary experiences that customers demand.

Recognising this, many banks are now considering their options. Some have already started down the challenging path and hit bumps in the road. A very small number have successfully executed their ambition to create a platform for the future. All banks contemplating transformation should take lessons from both the successes and the mistakes. These will be critical to inform their plans.

 

What are the next steps?

There are a number of essential transformation steps to consider that will help realise value from investment as rapidly as possible, provide an appropriate level of delivery confidence and manage exposure to the operational risk normally associated with such changes. These include:

1. Business strategy must inform every step of transformation – ensure that the approach to platform transformation is tightly aligned to the wider business strategy.

 

2. Design a strategy-aligned roadmap for delivery – a transformation roadmap should clearly set out the logical order in which business outcomes will be delivered. Here again, that needs to align with the value that the organisation is seeking to achieve, with incremental progress determined by business priorities. This involves making appropriate use of modern delivery methods, such as agile, and making sure that everything that is done satisfies and is frequently assessed against the relevant value criteria.

 

3. Assess technology selection against business value – organisations often undertake detailed and exhaustive market, functional and technical assessments when reviewing new products and suppliers. This often means either the technical assessment dominates proceedings and / or new technology platforms are selected without a clear line of sight to the value required. Poor product selection is a risk as a result, as well as a lack of understanding of how products should be deployed to inform the sequence of delivery required by the transformation roadmap.

 

4. Assess your readiness for change – unsurprisingly, given the sheer scale and velocity of change that business leaders must deal with, resistance to change is often a key reason given for the failure of banking transformation projects. However, it is crucial that the ability of the organisation to deliver and adopt the operational, technical, and cultural changes required to support transformation is comprehensively assessed and done early.

The impact of COVID-19 paired with and the demands that financial services organisations face from all directions, make change an inevitable necessity for the most. The approach to delivering a successful banking transformation, underpinned by a modernised platform, will vary dramatically from bank to bank. However, above all, businesses need to ensure that value drives every aspect of change explicitly linking transformation strategy and investment with the realisation of value.

 

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Banking

CLOUD ALLOWS BANKS TO BASK IN CHANGE

by: Elliott Limb, Chief Customer Officer at Mambu

 

As a new era of banking takes off, the cloud is enabling players to adapt fast at low cost and with minimum risk, while rolling out products that customers actually want, writes Elliott Limb

For all the talk of today’s banking landscape being the most competitive ever, you’d think the customer would be spoilt for choice. Sure, there are more banks and prices are low, but the reality is that it is still pretty hard to tell one from another when it comes to real value-added services.

Every retail bank, for example, offers some form of online and mobile banking; and most private banks have adopted automation and robo advice of some kind to help bring costs down and make its service more relevant to customers.

The upshot of this homogeneity is that rather than working to provide a unique service, banks seek to stand out from the pack through marketing – offering free travel insurance for premium customers; zero-fee balance transfers; no interest on overdrafts; low-cost or flexible loans. These offers aren’t about providing a better banking service. They are small treats in an industry that has raced to the bottom on price.

But this old-school approach is now being challenged. Technology across other industries has already forced change, putting choice for the customer front and centre. The big platform companies like Amazon or Google were among the first to use Big Data and algorithms to analyse behaviour and thus predict what the customer wants – often before the customer knows it themselves.

As other industries apply predictive technologies, it has had two effects: customers have come to expect a highly personalised and relevant service that enhances their lives; and the big platform companies are beginning to encroach on some banking activities such as loans and payments. The capital reserves held by Apple today would put it among the top ten banks outside China.

Taken together, these changes are dragging banking into a new era of differentiation and choice, where customers will expect to get what they want when they want it at a price they’re willing to pay.

What every successful player will have in common is agility – the ability to quickly adapt and change not just products and services but business strategy to reflect movements within its own market space. And to be clear: this agility isn’t just about the technology that is used – it’s a business model.

The agile model doesn’t wed the bank to a set of tools; it marries the bank to choice, thereby maximising the chances of it becoming and remaining the best. This agility can only come from cloud operations.

 

Enter the cloud

Cloud allows banks to innovate fast. Digital technology in the cloud lets them quickly reconfigure products and services to take into account new regulations or temporary circumstances – the fall-out of Covid-19 and the need to waive overdraft fees or provide payment holidays, for example. Where legacy systems demand banks carefully plan and time changes, which can take many months, banks working with the cloud can carry them out on the hoof, often within hours. This makes them more competitive, incurs lower costs and lowers risk.

Working with the cloud also allows banks to align costs to revenues because billing is on a pay-as-you-use basis. Use can be scaled up or down according to demand, so expensive technology doesn’t lie idle on-premise ever. Locked-in costs are minimised. This means that you could launch a great new customer-centric bank today and scale up to become a $1bn unicorn fast.

Finally, cloud technology helps cut risk. By providing flexibility, banks can adapt their products and services as the market evolves. They aren’t locked into medium and long-term strategies. They can be nimble.

Furthermore, cloud providers invest heavily in their technology, updating and upgrading it constantly and ensuring its resilience and security in a way that individual banks simply couldn’t afford. So banks working with cloud providers will have access to the best, most secure, resilient, up-to-date technology.

Make no mistake. Competition going forward will be tough and customers will expect the best or they will go elsewhere. Margins are already low, thanks to the above mentioned fight to the bottom on price.

However, banks using cloud technology will be ready to compete on a level unseen as yet and offer customers services that they want and need, at price points they can afford. They are able to differentiate on agility and adapt quickly as their market dictates and they are able to manage risk. As a result, customers will have real choices for the first time – choices that will add value to their banking experience and even their lives.

 

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