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1. Immediately reassess sector macros & micros and identify sectors that have become short-term unattractive (e.g. auto), those that are now positive (e.g. pharma), and map your clients and portfolio to the new reality.

2. Segment clients as per new sector matrix, and identify clients already troubled in risk sectors and those likely to be affected.

3. Allocate above group to an expanded & high quality work-out team to co-manage the clients with existing RM’s and provide short term business guidance. Don’t necessarily do a drawn-down. In fact provide additional short term capital if needed. Refocus corporate RM teams to account monitoring, rather than new account acquisition for next 30-60 days. I would not release corporate RM headcount at this time.

4. Do all of the above for SME/Commercial accounts at a higher level of aggression. Understand the supply chain impact on your SME/Commercial clients. Get transaction banking going for SME and also corporate clients.

5. Significantly strengthen your risk, especially credit risk teams, and immediately redo the credit scorecards and algorithms.

6. Protect your liability book. Strengthen size of the corporate liabilities unit. Relook at your retail liability products and make them more attractive. Pull wealth customers in as quickly as possible.

7. On the retail side, assume 15%-30% reduction of liability and asset book, and transform operating, business and resulting cost model.

8. Digital, Digital, Digital. Strengthen your banking technology & FinTech platform & offering, and use this opportunity to aggressively move many of your customers and their transactions to digital and acquire new ones. This black swan moment is now a once in a lifetime opportunity in this area.

9. Assume 20% of the branches will need to be temporarily shut-down. Redirect customer to the other open branches. Save on branch operating cost.

10. Based on the above, make careful cost calculations by business unit from a people, process and technology perspective. Get ready to drop 15%-20% of the headcount with generous exit packages. Also compensation alignment for the remaining may be necessary.

Good Luck. And let us know if we can help in anyway.

Regards

Chairman, IBS Intelligence

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Data is widely acknowledged to be one of the business’ most valuable assets. Yet even data can depreciate in value. Like currency itself, it is always changing and evolving with new types appearing. Just as the financial industry has witnessed the rise of alternative and cryptocurrencies, businesses are trading on a recent boom of new forms of structured and unstructured data. Whether it has been digital or voice, every time a new channel is created a new kind of data is born alongside it.

Yet this has consequences for the data that came before, and for the businesses that continue to store it. As technology advances, old data gets harder to read and slower to utilise. Eventually, it becomes obsolete and less care is taken to properly manage it. Once it has fallen off the radar, we call it dark data. When data goes dark, conditions can become very dangerous for an organisation. To overcome this challenge, financial services companies will need a more strategic approach to data management and an increasingly robust use of technology.

The dark age of financial data

From the days of the earliest banks, financial services companies have always used data to improve and streamline the customer experience. We have come a long way from personal customer information written on paper documents, to credit scores, purchase histories and the telematics data used by an increasing number of insurance companies. Yet, this long history of data collection is part of the problem.

As financial services companies evolve, old data loses its strategic and business value – going dark. With today’s limitless cloud storage systems, it is far easier to make use of digital data than it is physical written records. Inevitably, the latter is filed away and eventually lost. Yet dark data never completely goes away.

Financial services companies are particularly vulnerable to the rise of this dark data. Indeed, the industry holds huge backlogs of stale data, 20% of which are made up of old document files. As smart contracts and blockchain transactions grow in popularity, this type of old data is rapidly losing its relevance and value.

The financial services industry’s heavily regulated environment is partly responsible for creating a culture that is cautious to delete anything. The result of this ‘save everything often’ mentality is that old data takes up valuable storage space.

The out of sight, out of mind nature of dark data also means it stops being properly managed, maintained and protected. Over time, this can pose a major security risk to financial services companies and their customers. With data privacy regulations like GDPR now in effect, consumers are more likely to take action against irresponsible financial services firms than any other sector, so dark data represents a ticking time bomb for data security.   

 How good data dies

To fight the dark data problem, businesses must stop it at its source. Ultimately, dark data stems directly from a lax data management strategy. This is not a new phenomenon; indeed, it has long been an aspect of development culture in financial services. Historically, mainframe systems were siloed and when a new application was to be built it would be done in a separate environment. Unsurprisingly, the data these companies hold is now spread across many different databases found in the cloud and on-premises.

When data becomes dark, it is not because of negligence but the complexity of keeping it organised in deeply fragmented IT environments. Research shows that employees regularly struggle with an overabundance of data sources and tools, as well as a lack of strategy and backup solutions. According to our research, the majority (81%) of organisations think their visibility and control of data is unsatisfactory and even more (83%) believe it is impacting data security. Not only is this fueling the rise of dark data, but it is also hurting the ability of employees to find and utilise valuable data, resulting in missed business opportunities and wasted resources.

A better way to manage data – Creating a data management strategy

As data becomes more siloed and fragmented, it is harder to find, manage and protect. This is how dark data turns into a risk. To stop this happening in the first place, financial services companies must create data management strategies that accommodate both recent and obsolete data. At the same time, they have to resist the temptation of a ‘save it all’ strategy. Instead, they should take advantage of new tools and platforms that can locate, automatically classify and manage data across multiple environments.

Introducing and enforcing data management policies

Data management policies should be put in place and enforced from the bottom to the top. This means everyone knows what the data types and formats are and where they should be saved at all times. But it is equally important that these boundaries are not too restrictive. Data is changing all the time, so standards too will need to adapt. Employees should be allowed some freedom of action as long as they stay within the goal posts.

Using the right technology

Financial services companies should also be willing to adopt data management technologies for increased efficiency and protection. A single, unified data management platform can make use of intelligent automation, helping employees locate the data they need faster. This not only makes data less likely to become dark, it gives the company a strategic edge and the ability to make better business decisions faster.

It is not only old, established players that should fear the rise of dark data. Disruptive payments providers and challengers may be on the cutting edge now, but they are just as subject to time and the depreciation of data. Finding new ways to utilise and safeguard data is at the heart of digital transformation. It is the key to creating opportunities and value for a business. Good policies and a structured, automated approach will not only prevent the rise of dark data in financial services but also help financial services companies truly harness the power of their data.

By Jasmit Sagoo, senior director, Northern Europe, Veritas Technologies

The business of payments – and payments technology – has transformed. In the pre-internet age, banks made money primarily from lending and deposits, supported by batch mainframe systems, with payments a minor sideshow. As electronic payments volumes started to take off in the early dot-com era, banks began to treat payments as a distinct business, driven by fee and transaction revenues. They packaged their offerings as monolithic, silo-ed financial products—and mirrored them with a complex silo-ed technology architecture.

The payment hub was originally conceived as a response to this complexity, to help banks eliminate processing silos and streamline their payments businesses. As we approach nearly twenty years since the first hubs were brought to market, it is a good time to evaluate whether hubs have delivered on that original promise.

Unfortunately, they have not. Many banks that made significant investments in hubs are still running legacy systems, with some institutions even having ended up with different hubs for different payment types, an architectural oxymoron. Many hubs have also proved unable to adapt to the challenges of real-time payments, always-on open banking, and the move to the cloud.

The stakes are high: today, payments generate over $1tn in revenue, with that amount, and transaction volumes, set to double over the next decade. If the traditional hub won’t allow banks to capitalize on this growth, then what will?

Before answering this question, let’s take a look at the trends that are shaping the payments industry, and how these are affecting the basic business model of banking.

Business and competitive environments are now very different from past decades. Competition is depressing fee revenue and rising payment volumes are driving up processing cost, eroding margins. Open banking is allowing challenger banks and non-bank service providers to disintermediate banks from their customers and is placing a premium on innovation and “fintech-like” agility from banks. With complexity in clearing and settlement growing and regulatory pressure mounting, banks are struggling more than ever to bring new payments services to market.

Most importantly, in this era of rapid transformation, both consumer and corporate customers want something different – they want their banking experiences to match the seamless, tailored real-time experiences they are accustomed to across social media, ecommerce and mobile applications. Services above and beyond traditional product offerings are in demand and, with brand loyalty declining, customers are more than happy to switch banks to obtain those experiences.

The combination of competitive pressure, technological change, and shifts in customer demand is forcing banks to change perspective and become much more customer-centric. They are viewing themselves as value-added service providers in a digital customer experience ecosystem, rather than purveyors of financial products. This altered perspective allows the answer to our original question to come into focus—the correct technological response to the transformational demands of business is to move away from monolithic payments applications and hubs glued together by middleware, to digital ecosystems.

A digital payments ecosystem consists of a number of independent components that interoperate easily and symbiotically allowing for rapid development of new business services. It is open; designed to support open banking interaction models, and API banking, with every function accessible as a service or microservice. It accommodates services from multiple third-party vendors – and banks. It is cloud-ready; operating in public, private or hybrid cloud models and able to mix and match where services and data run based on a bank’s deployment and data security requirements. It is inherently real-time and 24×7, unlike legacy hubs with real-time workflows grafted onto batch/RTGS scaffolding.  Lastly, it enables banks to own their roadmap – loosening vendor dependencies by eliminating the need to wait for vendor upgrades in order to release innovative new customer services and experiences.

Traditional payment hubs are dead, or dying – but new ecosystem-based payments technology approaches are ready to take over. Long live the next generation of hubs—the digital payments ecosystem!

At UK FinTech Week 2019, Secure Chorus brought to the stage a powerhouse of thought leaders in the field of post-quantum cryptography from UK government, industry and academia. The speakers discussed the quantum threats considered to be the next undefended frontier of cybersecurity and the significance of the problem for the finance industry.

Quantum-related technologies have the potential to massively disrupt the finance industry in algorithmic trading, fraud detection, encryption and transaction security. And yet, with these opportunities also come information security threats, as current encryption methods become simpler to break. Because organisations within the finance industry process and archive sensitive data over long time-frames (up to a decade or more), it is becoming clear that this industry needs to start upgrading all critical infrastructure to be quantum safe.

This was the theme of our recent Thought Leadership Platform addressing the finance industry at the UK FinTech Week 2019. Entitled “Quantum-Safe Finance: Preparing for the Storm”, the event was joined by government, industry and academic experts to discuss quantum threats for the financial sector. Speakers included experts from the UK National Cyber Security Centre (NCSC), ISARA Corporation, Post-Quantum and the Centre for Secure Information Technologies (CSIT).

The massive processing power that will be unlocked by quantum computers will make the public key cryptography we are using today vulnerable. This could bring on-line e-commerce and banking fraud to a systemic breach-type scenario. Blockchain-based technologies that rely on the Elliptic Curve Digital Signature Algorithm (ECDSA) would also not be ‘quantum safe’, exposing the burgeoning cryptocurrency markets to cyber risks.

The vision statement for our Thought Leadership Platform was to raise awareness on the need for greater cooperation between governments, industry and academia to develop successful quantum-safe initiatives.

The market has seen rising investment and excitement surrounding transformational opportunities created by quantum computing. However, the significant threat to our global information infrastructure posed by large-scale quantum computing has greatly overshadowed by it.

Our panel spoke about the design of quantum computers drawing upon very different scientific concepts from those used in today’s conventional or ‘classic’ computers. This could eventually enable them to factor large numbers relatively quickly, which means that they will potentially be able to significantly weaken the public key cryptography that has protected the majority of data to date.

Popular cryptographic schemes based on these hard problems – including RSA and Elliptic Curve Cryptography – will be easily broken by a quantum computer. This will rapidly accelerate the obsolescence of our currently deployed security systems, creating an unprecedented scale of the threat that will require a significant amount of time and resources to mitigate.

Without quantum-safe cryptography and security, all electronic information will become vulnerable to cyber attacks. It will no longer be possible to guarantee the integrity and authenticity of transmitted information. Importantly, encrypted data that is currently safe from cyber attacks can be stored for later decryption once quantum computers become available. From a legal perspective, these scenarios would mean a violation of regulatory requirements for data privacy and security that organisations are required to comply with.

This means there is now a pressing need to develop public key cryptography capable of resisting such quantum attacks. This can be achieved by developing post-quantum algorithms based on different mathematical tools that are resistant to both quantum and conventional cyber attacks.

Standards-setting bodies, including the US-based National Institute of Standards and Technology (NIST) as well as the European Telecommunications Standards Institute (ETSI), are currently in the processes of selecting the strongest cryptographic algorithms in a step towards standardising the relevant algorithms, primitives, and risk management practices as needed to seamlessly preserve our global information security infrastructure.

Of the various post-quantum cryptographic scheme candidates, lattice-based cryptographic schemes (LBC) have emerged as one of the most promising classes for standardisation. For three reasons: first, due to their efficiency and simplicity; second, due to their good security properties; and third, due to their manifestation into more complex security functions.

In order to make the transition from the security we use in the digital space today to a fully quantum-safe one, we need to fundamentally change the way we build our digital systems. We need technology solutions that bridge the gap between current cryptography and quantum-safe cryptography without causing a complete breakdown of systems because of one algorithm not being able to communicate with the other.

Standards help technologies speak the same language. However, the required standards won’t be ready for several more years. In the meantime, we need a path to quantum-safe security. One method of developing quantum-safe public key cryptography is the deployment of a new set of public key cryptosystems for classic computers that can resist quantum attack. These cryptosystems are called ‘quantum-safe’ or ‘post-quantum cryptography’. The principle behind them is the use of mathematical problems of a complexity beyond quantum computing’s ability to solve them. The key takeaway message from our Thought Leadership Platform was that there is a pressing need to start planning for the transition to quantum-safe systems. This is especially relevant in industries such as finance, due to the complexity of their systems that will require several years to be updated.

By Elisabetta Zaccaria, Chairman Secure Chorus

The world of banking today is like a race car on the grid preparing for the inevitable green light. There is a lot of noise before the ‘go’ signal; from the vehicles revving their engines, pundits in commentary boxes speculating on the race outcome, and spectators cheering on favourites from the grandstands. When the chequered flag drops and the race begins, a plume of dust and smoke is left behind as the vehicles speed off across the track. The winner is yet to be decided… 

In banking, the race is just starting. Amidst the noise, speculation and fanfare, success in this industry will come down to one key thing: open APIs. Those that can harness them correctly will take the top spot on the podium. 

Shifting up a gear 

Modernisation in retail banking is largely being driven by customers, who have come to expect a level of digitalisation consistent with what they experience in other areas of their lives. Simply compare well-known consumer tech innovations such as the Amazon Echo, or Google’s impressive AI-enabled search function, to understand why people expect more from those who handle their money.  

This is not to say banks have neglected innovation. Flashier, more convenient services for customers have been introduced. But in the face of ongoing political, legacy, technological, competitive and regulatory challenges, the ‘from scratch’ development of advanced Google or Amazon-style services remains an uphill struggle.  

Even in light of the recent technological advancements permitted by open banking, the issues outlined above have prevented many banks from properly grasping the opportunities of technology and the disintermediation of data.  

Opening the throttle 

Open banking is accelerating the banking industry into the future, with APIs acting as the fuel to power the innovation ahead. But successful development and implementation of API-based technology is a long-winded and costly task for banks to undertake alone. To combat this, some banks have started acquiring fintech businesses to quickly bolster their own service offerings. However, for maximum benefit, industry-wide collaboration around innovation is needed. 

This will require banks to shift from a historically closed-off, competitive mentality, to recognising the advantages of pooling knowledge and raising standards of industry innovation together. BIAN, the organisation that I am proud to head up, has spent a decade promoting this ideology. Our global organisation brings together some of the biggest, most innovative banks and technology vendors, to build a common IT architecture or ‘how-to guide’ to streamline the inevitable move to modern, high-quality, and customer oriented services. 

A large part of how to create a modern IT architecture for banks involves utilising a library of definitions for popular APIs, to avoid unnecessary duplication of time, money and effort. BIAN’s current banking architecture contains 26 new API definitions, including ones that instruct banks how to build automated customer on-boarding processes. These API definitions comply with the SWIFT ISO20022 open banking standardisation approach, making them universally compatible. 

Miles ahead 

Adopting a common IT framework would allow the banking industry to launch services faster, and better meet customer demands for smarter and more transparent services. As time goes on, more complex API functionalities will be built, allowing banks to not just incorporate more exciting services into their offering (e.g. WhatsApp payment), but also establish novel ways to maximise new and previously untapped revenue streams. Naturally, modern and streamlined services can reduce operational costs by eliminating outdated back and middle-office processes.  

Looking ahead, the next phase of API development will focus on ‘micro-services’ – that is, API first banking capabilities which run independently from core banking systems. Microservices will provision banks to facilitate a “pick-and-mix” approach to their offerings, allowing them to be more aligned to their customer base. In time, such a model could renew the core banking system and change the banking IT function forever. 

First place 

The introduction of a common IT framework will be of massive benefit to the banking industry, helping major players to address customers’ demands for modern banking solutions in a more effective manner. As the introduction of higher standards for global banking services grows, the industry will eventually move away from competing on service offerings to competing on brand value. Like we have seen in the retail industry, the winners in banking will be those that provide the right mix of innovative offerings as well as premium customer service.  

By Hans Tesselaar, Executive Director at BIAN 

We have come a long way from the first commercial use of Oculus Rift VR headset 0f 2013. Yet, most people associate the technology of Augmented Reality (AR) and Virtual Reality (VR) with the realm of gaming. However, many industries including marketing, healthcare, real-estate are accepting the immense potential of VR to improve their business. A report by Goldman Sachs group estimates the virtual and augmented reality to become an $80 billion market by 2025.

Even financial institutions like the banks are well aware of this conundrum, and many firms are aggressively experimenting with the new coming technology to enhance customer experience (CX). From basic apps that use customer location to help locate ATM branches nearby to promoting banking solutions in an engaging 3D environment. Some financial institutions are using it as a marketing tool, others are using AR to offer customer-centric apps that display real-time cost and other information associated with properties which are up for sale, offer a mortgage calculator and more.

According to a study, ‘AR/VR can transform financial data into a visual, engaging experience and can eventually bring the face-to-face experience into a customer’s home’. The possibility of hybrid branches is also in the pipeline where physical branches use AR technology to offer self-service like chatbots, or robots to provide information. If required, customers can also connect to an actual bank-representative via video conferences.

All things said and done, the idea of banking in virtual reality is still half-baked and the road to reach that reality is daunting and surrounded by skepticism about the possibilities of virtual banking. Nonetheless, there are a few corners in the financial sector where VR and AR have already made an impact:

Immersive Experience through Data Visualization

The financial industry has a lot riding on analyzing large amounts of data on a day to day basis. Data visualization helps financial traders and advisors to get a visual breakdown of the copious amount of data and make informed decisions about wealth management. Using the modern technology of VR and AR, data visualization is quicker and easier than ever before.

Remember we spoke about Oculus Rift earlier? Fidelity labs used the technology behind the Oculus Rift to create an immersive 3D environment to analyze data accurately. They created a virtual world where people can talk to financial advisors in virtual reality to learn about the progress of their stock portfolios. Their VR assistant, Cora, will display the stock chart on a wall of her virtual office just like presenting graph on a virtual projector.

Virtual Trading Workshops

Some financial institutions are using VR to create virtual trading workshops. In April 2017, FlexTrade Systems announced the launch of ‘FlexAR’ – a virtual reality trading application that uses Microsoft HoloLens to offer an extraordinary way of visualizing and presenting trading. It uses components from the real world and allows traders to see and interact with the markets and identify the holistic patterns in the trading environment.

Virtual Reality Shopping Experience

Taking customer and shopping experience to the next level, in 2017, MasterCard and Swarovski launched a VR shopping app that allows consumers to browse and purchase items from Atelier Swarovski home décor line and immerse into a complete virtual shopping experience. They can use Masterpass, MasterCard’s digital payment service to make payments.

Security

With biometrics as part of the AR experience, financial services can offer more secure and substantial protection against cybercrime. A number of banking applications already offer fingerprint authentication for many smartphones. With AR, iris identification and voice recognition, are being introduced as well. In 2018, Axis Bank became India’s first bank to introduce Iris Scan Authentication feature for Aadhaar-based transactions at its micro-ATM tablets.

Possibilities of Virtual Branches

As more and more financial service providers are incrementally moving towards digitized banking, the idea of a virtual bank doesn’t seem too far-fetched. Imagine never having to take a break during working hours and wait in a line at the bank. Now imagine, getting the personalized banking service at the comfort of your home, when it’s convenient for you while enjoying a cup of coffee. That’s what virtual branches have to offer. To aid customer demand for contact anytime, financial institutions are already offering services like Chatbots and are developing solutions to provide banking solutions exclusively in a VR environment. This would be a win-win for both- customers will get their service anytime, anywhere and banks will be able to reduce costs as they will not need to invest in physical locations.

Living in today’s high-tech world, we all know that technology is something that has been and will keep on evolving. With each day passing, reality adjacent technologies like VR and AR are becoming mainstream, and already impacting the way financial institutions operate, manage data, interact with customers and more.

There is no doubt that the financial industry will need to integrate this new science into banking operations. Not only will this help them attract and retain customers, enrich the customer’s user experience (UX) but also help in operational cost reduction. Failing to do so, their customers are most likely to move toward non-financial institutions that offer ease of use and flexible services that they demand.

By Vikram Bhagvan, Associate Vice President, Business Operation, Maveric Systems Limited

In June, Visa started rejecting one in 10 financial transactions across the U.K. and Europe – a problem lasting 10 hours and affecting 1.7 million cardholders. Even in an IT environment designed to support 24,000 transactions per second, a hardware failure crashed the system. The incident was a wake-up call for an industry reluctant to suspend services for scheduled, expensive repairs. Could predictive maintenance have prevented the crisis?

Predictive maintenance draws on machine learning, neural networking, and artificial intelligence. Commonly used in marketing, learning technologies improve with use: every time you search Google, its accuracy improves.

Yet while AI can predict preference, it is still learning how to factor in context. Nirvana for marketers will be when technology shows my car purchase is followed by a caffeine urge, with my coffee advertised accordingly. It’s the search for the unforeseeable yet real relationship that can only be found with a deep data dive. We’re not there yet, but we’re on the way.

Maintenance that informs itself

The same neural networking technologies are being applied to hardware and networks. There is countless data in a data centre. Just as marketers want to utilise all the information available, so do data centre managers. The promise in machine learning is the ability to examine the full range of performance data in real-time to detect patterns indicative of “faults-in-the-making”, uncovering relationships no human engineer would return, like cars and caffeine.

This application of AI algorithms to data centre maintenance underpins our ParkView advanced monitoring system, which contextualises patterns to “understand” infrastructure behaviours. This means instant fault identification and fewer false alarms. Future predictive systems will prevent the types of issues Visa experienced.

The next stage: predictive maintenance taps IoT

In the Tom Cruise sci-fi movie, Minority Report, police use “psychic technology” to prevent crimes before they happen. The twist comes when the crime-solver is accused of the future murder of a man he hasn’t yet met.

There is a parallel with data centres. Human error causes an estimated 75 percent of downtime. That’s why data centres are less populated. The perimeter has security staff, but the interiors are becoming vast and lonely server expanses, where the electric hum is rarely broken by the sound of footsteps. The downside is the lack of human detection of things like temperature changes and dripping water.

That’s where the IoT and the Industry 4.0 playbook developed in heavy industry comes in, in which remote monitoring enables smart and predictive maintenance. A good example here is fixing a data centre air-conditioning system based on its predicted performance in relation to it’s surrounding environment. This concept can be applied across the entirety of a data centre and its cooling, power, networking, compute, storage, and other equipment. Emerging dynamic and largely automated predictive maintenance management will transform the data centres we know today into self-monitoring, self-healing technology hubs, enabling reliability as we move computers to the edge to support the IoT applications of tomorrow.

Evidence indicates a move from a reactive/corrective stance, still dominant in many data centres, to more preventative maintenance delivering average savings of up to 18%. The next leap towards predictive maintenance drops spending about 12% further. In fact, Google used such strategies to drive a 15% drop in overall energy overhead.

Combating downtime with predictive technology

Enterprises must integrate predictive maintenance. Downtime kills reputations, profits, and customer relationships. Most organisations like Visa can recover from unplanned outages, but reducing unscheduled maintenance is always preferable.

IT leaders must make hardware and facilities as downtime-proof as possible. This means using machine learning and AI to return a pound of ROI on every ounce of prevention possible. Banks are investing in AI for a range of purposes, from contract scanning to fighting fraud. It’s essential that the new technology is used to fix problems in advance.

By Evan Kenty, Managing Director EMEA, Park Place Technologies