Recent changes in business and regulatory reporting requirements have compelled financial institutions to put in place data management models that enable the management of and response to real-time data requests from diverse sources. And as the industry now starts to explore the growing range of innovative data sources, from sentiment analysis to satellite imagery, to add depth to traditional data resources, there is a significant opportunity to gain new insights through machine learning, correlation and pattern spotting – insights that can improve time to market and drive down costs.
Yet unlocking this new data diversity requires a fundamental change to traditional data management; financial data models must support not only fast and effective on-boarding of new data sources but also efficient data exploration and easy access and distribution of data across the business.
As Martijn Groot VP, Product Management, Asset Control, explains, traditional EDM models are being replaced by a new generation of data services that address the full information lifecycle, from data sourcing to integration and distribution.
New Data Services
From investment assessment to Know Your Customer (KYC), the way in which financial institutions consider decision making is set to change fundamentally over the next year as organisations begin to on-board and explore the new raft of data sources. While the new data model has been driven by regulatory demands, the sheer depth of information now created and collected globally is extraordinary – and is set to take the industry far beyond the traditional catalogue of price and reference data sources.
From web crawling to mine news and spot corporate events to sentiment analysis, satellite and geospatial information, traffic and travel patterns and property listings – the way in which organisations can now analyse investment opportunities, track Politically Exposed Persons, and company news, is being transformed.
No longer will organisations be limited to published financial statements and earning calls; instead investment decisions can be based on a much broader and deeper – but potentially also murkier – set of data. For example, the addition of social media sentiment analysis, combined with satellite information tracking car park usage, can deliver a new level of understanding into a supermarket’s performance. Indeed, with the availability now of transcripts of all earning calls, it is possible to understand who is asking specific questions and how CEOs and CFOs respond – insight which can be tracked and analysed to deliver fast, actionable investment insight. Similarly, with KYC – the ability to rapidly deep dive through multiple diverse data sources provides a chance to address the escalating overhead associated with customer on-boarding and reduce the cost of doing business.
New Mastering Model
The challenge, of course, is to find a way to harness these new data sources; to on-board this new insight into a way that is fast, effective and usable. Where does this leave traditional EDM solutions that have played a vital role in managing traditional data sources? The mastering process must still provide a 360-degree version of the truth that can be used across the organisation, from valuations to risk and financial reporting; the addition of data sources reinforces the need for excellent structured processes that compare sources to find discrepancies and deliver that golden source. But this process must now also deliver excellent integration – with organisations looking for robust Application Programming Interfaces (APIs) to enable the fast stitching together and exploration of these new data sources.
In addition to adding new depth to traditional information, these data sources also change the emphasis of the mastering process. Rather than focusing on error detection in order to achieve consistency and accuracy, these sources enable organisations to undertake pattern discovery, leveraging new techniques, including machine learning, to spot new correlations or reveal unusual activity, within market surveillance for example.
Speed is critical; with the vast number of new data sources available, fast, effective data discovery will be essential to drive down the cost of change and provide organisations with a chance to gain differentiation in time to market. Intelligent data mastering is at the heart of this new model. Combining APIs that enable integration with an easy process for testing and on-boarding these new models in production will be essential – and that will require APIs that support popular data science languages, including R and Python. In addition, the use of NoSQL technology combined with the ability to deploy new models close to the data will be key to supporting the significant associated data processing demand.
This ability to combine robust data mastering processes with excellent integration will build a new data foundation; it will enable an organisation to pull together these diverse data sets, create new insight based on sentiment from social media and performance from satellites and the traditional measures of price history and published financials.
To maximise the value of these data sources, organisations also need to reconsider access and utilisation. Making these new data sets easily accessible, not only to new algorithms and data scientists but also to end users within risk, investment, operations or compliance will mark a significant step change in data exploitation.
Ensuring the data easily integrates with the languages adopted by data scientists is fundamental; but to deliver the immense potential value to end users, data analysis must evolve beyond the traditional technical requirements of SQL queries. Offering end users self-service access via enterprise search, a browser, Excel and easy to understand interaction models rather than via proprietary APIs and custom symbologies, will open up these new data sources to deliver even greater corporate value.
These new data sources are radically different to the traditional data resources – and their potential value to an organisation is untapped. Pattern matching in particular can be oriented not only towards improving operations or reducing risk but also towards improved pricing and new revenue opportunities. Matching of data items will not only take place through common keys but also through spotting the same behaviour in hitherto unrelated data or otherwise finding repeating patterns in time, space and across different data sets.
Especially for active investment management, the use of non-traditional data sources can help compete and differentiate against passive investment strategies; while in compliance and risk management, accessing a broader range of sources can help trigger early warnings on suspect transactions, relationships or price movements.
The potential is incredibly exciting – and first mover advantage cannot be overstated. The key for financial institutions over the next year or so is to move beyond traditional EDM models and embrace the new mastering and distribution services that will enable essential exploitation of data across the business.
Time for financial institutions to Take Back Control of market data costs
By Yann Bloch, Vice President of Product Management at NeoXam
Brexit may well be just around the corner, but it is market data spending that financial institutions are more interested in taking back control of right now. In fact, other than regulatory equivalence post the transition period, it is hard to think of a more prominent issue right now than the rising cost of market data. According to analysis at the end of last year by Burton Taylor, global spend on market data topped $30 billion in 2019. With costs showing very little sign in coming down, at least in the short to medium term, now has to be the time for market participants to better grasp of not only what their costs could be at the end of the month, but also the precise areas of business consuming the most data.
The problem has been, and still is, seeking out those month-on-month cost anomalies. For example, why is it that fixed income and FX derivatives costs have all of a sudden doubled compared to the previous month? The trouble is it is nigh on impossible to get accurate answers to questions like this because the vast majority of investment firms have no fullproof way of analysing how spending evolves over time. In certain cases, financial instructions can experience a 10%+ increase on their monthly market data vendor bills.
It is not hard to see why – as every small incremental cost mounts up fast. First there are the direct costs for one or more sets of data – which leads to billing getting far more complex. Sure, a market data vendor may be adding lots of different add-on services to help clients save money, but at the same time, they will also be adding on more costs. If this was not enough, there are also the indirect costs around data governance and regulatory compliance. New rules, such as the Fundamental Review of the Trading Book (FRTB), means that investment banks will have no choice but to consume a lot more data to be able to run models and back testing.
All this begs the question; how exactly can firms gain more control of their market data spending? A good place to start is trying to reduce waste. This involves firms making sure they do not request new sources of data from their vendors that they are not going to use. If data vendors charge for every single piece of data that the client requests, then the client needs to make sure they are going to act on this information. Then there is the recycling of the data. Say an investment fund needed a new piece of data instantly, and also needed that same piece of data at the end of the day. If the fund manager already has the data, they surely, they do not need to request it again? It is all about being smarter about reusing whatever data the fund manager has received previously. After all, different trading desks are all consuming data and requesting information through the data management team, but it is hard for the trader acting on the data to work out how much the data actually costs. This is why being able to allocate these costs to the different trading desks is key.
When all is said and done, the only way financial institutions can harbour any hopes of overcoming this longstanding data cost problem is by deriving more insights to ensure they a squeezing every last drop of value from their market data. Technological advancements mean that firms can now keep right on top of not just their data direct costs, like complex billing, but also the indirect costs around regulation. With so many other cost pressures across the business right now, it is time financial institutions take advantage of new technologies to finally address the issue of rising market data costs that has, frankly, plagued the industry for too long now.
Cash was our past, contactless is our present, contextual payments are the future
By Jason Jeffreys, founder of FETCH
$6tn in the next five years, this is how much the world will spend through contactless payments, according to analyst firm Juniper Research. For many of us who have discovered and since relied heavily on contactless payments since its introduction in 2007, either through card, phone, or watch, or those of us who have taken a stroll down a covid-era high-street to see shop windows adorned with “card payment only” signs, this is hardly a surprise. Even the Church of England in 2018 equipped 16,000 religious sites with terminals to allow for contactless donations. So what is behind this rise? And what is next?
The switch from cash to contactless is a transformation of payments that is driven by four key factors: speed, security, accessibility, and hygiene. While businesses and customers alike have felt the immense benefits of the cash to contactless transition, the next iteration goes further by digitally transforming the entire transaction process. It’s that potential which pushed me to launch FETCH – technology that allows customers to order and pay from their phone, anywhere. By exploring the benefits already felt by our contactless present, I hope to show you why I’m excited to be part of the contextual payments future.
Aldi is all about low prices and this is achieved with efficiency – that is why their checkout staff are trained to scan as fast as possible, it’s why their barcodes are huge, and it’s why you can’t keep up. It’s all in the name of efficiency and cost saving, and contactless payments make this possible.
While increasing the rate of transactions has a direct impact on money through the till, there is an increase in the perceived speed which does wonders to get customers back through the door. Shoppers may have spent an hour or more in-store but their direct interactions with the shop and staff were quick and timely and that’s the experience they remember and the impression they build of the brand.
Aldi are not alone in realising this and while it is easy to point to the impact that contactless has had on the retail sector, its revolution has slowly crept into hospitality – an industry notoriously late at adopting new technologies.
High-street coffee shops rely on getting as many people as possible through the doors and back out again. They want as little disruption to your day as possible but more importantly, they want to process as many payments per hour as possible. Cash transactions are slow in comparison to a single tap, so for the coffee shops, this means fewer transactions per hour and money lost. For businesses in this sector who rely on periodic rushes, measuring performance per hour is a necessity and maximising revenue over these short windows is so important.
For reasons obvious to anyone who has been to a crowded hospitality venue, stood at a crowded bar or waited for waiting staff during a busy dinner rush, the businesses in this space already running on contextual ordering systems like FETCH have all reported a vastly improved staff and customer experience in hospitality venues. While it may be difficult to spot how these benefits can be felt in retail, this reality is not bound to fiction or the distant future – it’s being pioneered already in retail by Amazon.
In a well documented glimpse into the future of shopping, Amazon’s latest Seattle store removes the transaction element completely. Instead, you put your items in your trolley as you go round the shop, and the sensors and cameras accurately and automatically recognise the items, keeping a track and total, before taking payment automatically and digitally through your Amazon account once you walk the trolley back out of the store. Can you imagine standing in a supermarket queue to pay once you’ve experienced the ease, simplicity and effortlessness of that?
Smartphones have got smarter and they have revolutionised the way we get through the day. From how we discover, connect, and socialise, to how we organise, learn, navigate and search for answers – rarely an hour goes by where we aren’t using our phones for something.
As time moved on they only grew to become more capable, responsible for managing more aspects of our lives, and it was only a matter of time before they were capable of handling secure contactless payments. The leap for people to trust their smartphones with just one additional task was tiny.
When you couple this with debit and credit cards being enabled with contactless technology by default, the rise of wearables, and e-commerce growing massively, the results are clear – people are more trusting of online payments, are more familiar with buying in this way, and have more ways of making contactless purchases, than ever before.
In fact, a Mastercard survey in 2016 indicated that Brits carry less than £5 in cash on average, with 14% of people surveyed carrying no cash at all, and 1 in 10 replacing wallets and purses altogether, opting for a simple card in the pocket instead. Figures which have no doubt grown even starker since 2016.
When we take this into consideration with 99% of 16-24 year olds, 98% of 25-34 year olds, and 95% of 35-54 year olds all being smartphone owners, we begin to see the inevitability of contextual payments as the next iteration and how the response to contextual payments will be positive and welcome; something FETCH clients and the vast majority of their customers can all attest to.
Cashless payments means no cash in the till or on-site; no chance of mistakenly accepting fraudulent notes or coins; no trips to the bank to deposit or withdraw cash for the till; the end of time spent counting money every day, and the end of discrepancies which occur from this.
It limits the levels of theft, switches businesses over to an accurate, secure and efficient system, and gives business owners their time back. It makes tax returns, financial planning and forecasting and more all possible, easier and quicker and in short, it makes businesses stronger.
Contextual payments go further by offering really insightful data of what happens before and after people decide to part with their money; for example, how long they spend browsing before ordering, what they look at, what they’ve missed, when they order next and more. This means you are informed and can redesign and improve the user journey so it works better for you and your customers, all based on accurate, relevant and timely data.
As contactless payments evolve to contextual ordering, it’s important to choose a system that easily integrates with the wider business and your systems so you can continue to access the benefits of contactless. That’s why from day 1 of building FETCH I put so much emphasis on ensuring it integrates with one of the biggest and most popular POS systems in hospitality.
Initial adoption has long been the biggest barrier to widespread, sustained use of new technologies and going cash-free is no exception.
Given that the coronavirus thrives and passes through human contact and shared surfaces, going cash-free and contactless was a small, easy and obvious change to implement for businesses to become covid-secure and safer for customers and staff.
FETCH and other contextual payment systems are being used to go beyond this, to keep staff and visitors safe by limiting human contact beyond just payments. In our case, we have allowed hospitality customers to continue to browse, place their orders and pay, just as before, but without the need for repeated human contact at every single stage.
Given the health imperative and coercion from governments, local authorities and health bodies to switch to contact-free operations, businesses who may have once been years away from this change are laying down the infrastructure today out of necessity and it will be no surprise if contactless becomes a staple long after the coronavirus has left.
Post-coronavirus, contextual ordering offers businesses the chance to let the technology take care of these minor tasks, giving staff the space to instead dedicate their time, talent and energy towards elevating the overall experience. It’s the health imperative that acts as the gateway to this.
What does this transition mean for businesses? With visible consideration and effort put into hygiene, you are making your customers feel safe and cared for; by making transactions quick and painfree, you are giving your customers time to spend on the experience they came out for in the first place. In the process, you have created the ideal conditions for consumers to spend money and given them the confidence to do so.
I’ll end with the picture UK Finance data has painted through multiple annual payments reports: in 2006, 62% of all payments in the UK were made using cash; three years later it dropped to 58%; in 2016 the proportion had fallen to 40%; and just two years after that, cash formed just 28% of all UK payments. With a pre-covid prediction envisaging that by 2028 fewer than 1 in 10 payments will be made by cash, the widespread, covid-induced encouragement, adoption and enforcement of cashless policies in retail and hospitality has surely brought that many years forward.
Contextual ordering is the next inevitable iteration and if you were one of the few who reaped the benefits of going contactless early, you have the chance to be ahead of the curve once more. A welcome future for a multitude of industries is being set around us today.
The Rise of Contactless Payments
By Bilal Soylu, CEO of XcooBee
Today, banks involved in the issuances of credit cards, and companies at the nexus of merchant services, are experiencing a rare event in the industry.
For years, digital payment innovators fought a hard battle to adopt contactless systems and create standards. The effort and push came from companies with much of the effort directed at consumers to adopt their methodology. Whether it is Samsung Pay, Google Pay or Apple Pay they all had to overcome similar hurdles – consumers were reluctant to adopt a technology that did not have a sufficient number of merchants; thus, the progress was slow.
The COVID-19 pandemic rewrote the script in a whirlwind. All of a sudden, consumers began to demand contactless payment experiences in every way imaginable. The supply side push has turned into a demand side pull and the adoption rate is spiking.
This left banks, originators and companies involved in the eco-system with an interesting dilemma – fast decisions have to be made as to which digital technology to invest in and do they bind themselves, for multiple years going forward, to a specific infrastructure.
While previously the belief was that this could be explored over a longer period of time, the current reality is that these decisions are forced on institutions “overnight”. In this light, there are many different aspects to contactless payments and originators, and banks need to make smart bets on which type should be supported.
So, let’s look at all the relevant elements of contactless payments to explore a better model for institutional support.
General Drivers of Contactless Acceptance Growths
Physical safety from virus infection by avoiding touching 3rd party equipment or allowing safe distancing from other people and/or equipment is the main driver today. It has been emphasized by many epidemiologists as a basic requirement for conducting business. Consequently, it will be no surprise that safety is the factor that underlies the rapid adoption of a number of contactless payment technologies by once reluctant consumers.
We expect this to be a primary driver well into 2021. Thus, any technology to be rolled out in the short term should enhance safety in some form or contribute in a way to the improvement of safety.
An early benefit highlighted and emphasized by contactless technology providers was the data-security aspect that surrounds the transaction. Rather than exchanging the actual credit card number, for example, a tokenization is performed to create transaction specific tokens that are then used to complete the transaction. Even when intercepted, these tokens cannot be used outside this transaction and, thus, the approach is considered to be more secure.
Although the data-security value was incessantly marketed to consumers, most had, and still have, a limited understanding of the implementation of the technology. Thus, the appeal to the consumer with this benefit was not successful. However, the increased security elements were a clearer benefit for merchants and issuers. Hence, a steady growth of terminals and accepting merchants was the result.
In general, the tokenization approach to security has been chosen for many types of contactless payment systems, this includes NFC based card chips, digital payments like Apple Pay, Google Pay or Samsung Pay. However, for QR payments the use of tokenization should be verified as there are no current standards that govern its use consistently.
Convenience was the aspect of many contactless payments system that appealed the most to consumers prior to Covid-19. The ability to either very quickly conduct a transaction or very flexibly conduct a transaction drove consumer adoption. For example, being able to load many payment methods onto a mobile device that users carry with them anywhere increased the appeal of use to consumers.
Thus, when evaluating a particular contactless payment technology with a longer-term outlook the convenience aspect should be emphasized. Given the historical basis, consumers are very likely to be attracted by this aspect as the main driver of adoption again. A financial institutions’ post-Covid planning and investment models for contactless technology should consider this to be a major aspect.
Contactless Payment Categories
When we speak of contactless payment systems, we normally refer to any payment technology that can trigger a payment transaction in the physical space with direct consumer presence, but without direct contact with merchant equipment. Thus, we would exclude online and ecommerce transactions for this purpose.
We will focus on the two mainstream contactless technologies, NFC and QR payments, and review them here. Other contactless payment technologies exist but have not reached widespread adoption so we will only provide brief overview of those.
Near Field Communication (NFC) payments are the earliest form of contactless payments that found acceptance in the markets. Generally, two devices are needed and must be near each other to communicate via radio signals. Both the reader (interrogator) and sender (tag) must be within 4cm (1.5in) for the transaction to be initiated. ExxonMobile’s Speedpass is widely believed to be the first implementation of this touch and go type of pay experience that has come to exemplify NFC based contactless payments.
There are two common sub-categories from that technology today; The single card-based sender (tag) and the mobile-phone-based sender (tag). The mobile phone-based application tends to be more flexible allowing consumers to combine multiple cards into one mobile-wallet that is secured with some form with biometric access.
However, NFC signals are not uniform and different standards are used in the Far East (i.e. Japan) rather than in Europe.
NFC payments found early success in developed western markets where the population already had easy access to banking and bank issued card-based tags. However, in countries where the banking system developed later and card-based payments were not common, NFC payments did not flourish.
Thus, today, the market for NFC is mainly concentrated in Europe, Japan, and US.
The roll out of NFC requires hardware on the merchant and consumer side. The merchant hardware is normally leased, and leasing programs have been steady revenue generators for those companies. Whereas, today, the global contactless Point of Sale (POS) terminals market is poised to grow by $5.54 bn during 2020-2024, progressing at a CAGR of 16% during the forecast period, according to research done by Technavio.
However, with the pandemic, the speed of system activation has been a key criterium for selection of the technology. In this context, delivery of hardware, setting up of POS systems and testing connectivity slows down rollouts and potential revenue.
Similarly, requiring consumers to be equipped with supporting hardware may also introduce a friction element, especially in markets where NFC has gained less momentum.
QR codes are like 3D barcodes. The user scans the QR code via a smartphone and the smartphone, then interprets the barcode and a related website or application may complete the payment process. Like NFC, this can be done very quickly without any contact between smartphone (reader) and the item or display using the QR code.
Normally, QR codes are immutable, meaning that once generated they do not change. However, there are now dynamic smart QR codes, like the ones Xcoobee offers, that can overcome this limitation.
QR codes found strong distribution in markets where banking reach was limited in some form through government or market forces. The QR payment process, in many markets, also exemplifies a jump to direct digital payment, bypassing much of the banking system for purchase transactions. Especially when QR payment systems are connected to mobile wallets the provider of the wallet handles all transaction steps in-system, reducing friction and creating an ease to use and adoption. They have found popularity mainly in China, where AliPay and WeChat pay are gaining dominant market shares.
However, with the advent of COVID and the speed advantages in implementation and cost, other non-traditional markets such as EU and US are seeing dramatic increases in use of QR payments as well.
Activation of QR code payments commonly requires merchants to simply print codes, which can be accomplished with less hardware. The integration into bank systems is handled via merchant or bank app and the consumer simply requires a smartphone.
While bank offerings in this segment tend to be limited, given the simplified requirements, QR implementation can be quick for merchants to roll out.
Other Contactless Options
There are other contactless payment technologies that are currently competing for market attention and can be grouped into a biometric group and a technology group. The biometric group includes such options as voice, facial or palm recognition-based payments while the technology group includes options like Bluetooth and Farfield-type technologies.
None of these have gained sufficient market share or have execution or security advantages that would push them ahead without concerted efforts from large market-players. Similarly, there is no consumer advantage that would drive a consumer demand-based distribution for these technologies.
NFC vs QR
Which one should you choose to support? Each one of these contactless payment methodologies has advantages and disadvantages. NFC can be nominally faster to use for consumers and more lucrative for banks, but QR codes currently reach a wider market since more phones can read them than those that can read NFC tags.
Operational simplicity and speed also favor QR code activation, but if there is already and existing NFC infrastructure this may become a secondary consideration.
Simply speaking, we are living through unprecedented times, consumers are demanding contactless payment and creating a demand side wave in exchange for safety. How each institution answers this call best will depend on circumstances and context.
Overall, it may be advisable to hedge bets and support both methodologies and offer services based on both. Evaluate customer input, and then, adopt and activate the best option for your financial institution.
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