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Demolish Barriers to Leverage AI in Financial Services



By Stuart Tarmy, Global Director, Financial Services Industry Solutions at Aerospike


Data has the power to set organisations apart. Leveraging it to enhance real-time applications from customer experience to fraud prevention, instant payments and reducing churn. The more data-driven an organisation is, the better it performs.

But data set sizes are growing at a phenomenal rate and real-time data is growing even faster. The financial services industry is deploying AI to help manage this explosive growth. While this is in essence the right way to progress, organisations need to move forward with knowledge and caution. The road to deploying AI and machine learning has many nuances, and there has been much hype around what AI can and cannot do. It is critical for companies to understand the most productive use cases, how to best leverage AI and advanced AI algorithms such as neural nets, and the underlying technical architecture to make these work in real-time to maximise the customer experience.

A McKinsey study conducted a couple of years ago found that during the pandemic most high-performing companies boosted their investment in AI, with the financial services sector increasing by 28 percent. This was further reinforced last year by research from NVIDIA which showed that 80% of the world’s top financial firms are spending billions on AI to improve services and sharpen their competitive claws.

The message is clear: embrace AI or you will fall behind. Both sets of research, and other studies, indicate that it is the ‘top’ financial services firms that are spending money to deploy AI solutions. What about everyone else? Should we assume that without AI they will fall behind in their growth, their ability to serve customers satisfactorily and perform for shareholders?

Stuart Tarmy

The situation is not that simple, because there are multiple fronts that all companies should address if they want to truly leverage the power of AI.

Improve model development and performance

To ensure AI systems work to their full capacity they need great data scientists with the ability to build sophisticated AI algorithms. They should be able to handle large volumes of data typically measured in terabytes, petabytes, and sometimes even exabytes in some industries, because the more data you have, the better you can train the model and determine the critical data attributes.

In typical financial services use cases, business units and customers are expecting a real-time experience – something in the region of sub-milliseconds or the blink of any eye – and that requires a super-fast engine. This is provided by multi-model real-time data platforms that not only deliver low latency but can also provide predictable performance at any scale.

These platforms serve as a system of record and can handle transactions in their millions regardless of whether they take place on mobile phones, tablets, laptops, at ATMs or in branches. They can help companies to model risk and provide analysis on the market, credit and liquidity exposure across multiple asset classes and customers. Added to that are features for providing identity management, detecting fraud, personalisation and compliance – all essential in financial services. The best-in-class real-time data platforms are multi-model, meaning they can provide multiple capabilities such as NoSQL, graph, time-series and JSON document functionalities.

Introduce large, multiple types of data to improve AI system performance

Look around at some of the world’s most advanced technology users, and we can see that they have adopted neural nets – which work on the concept of neurons talking to each other inside a computer system – and deep learning systems. This gives them the power to analyse millions of data attributes to train a model, sometimes as many as ten million attributes. At PayPal, for example, they have seen improvements in performance of 30 percent by deploying neural nets over more traditional AI/ML systems.

Another key industry trend is incorporating Explainable AI into the system design. This provides explanations about why the model is reaching certain conclusions, and the decision making it did to arrive there. It allows the system to be tweaked and adjustments to be made so that the model works more efficiently. Companies can access fast and reasonable explanations about how their data will be used which is especially useful given data privacy laws such as GDPR and CCPA, as well as the newer AI regulations that have been proposed, such as the EU’s AI Act.

Building and deploying AI for real-time performance

Let’s go back to real-time, multi-model data platforms and look at another way they support financial services companies.

We would expect them to enable fast model testing, but they can also ingest data extremely fast from a variety of sources at the edge. This helps systems of engagement to act in real-time, delivering stellar experiences to customers in line with their performance expectations and quickly serving the needs of employees.  This level of speed and functionality is essential, particularly in consumer lending, payments, credit cards and fraud prevention; for enterprise platforms that are being used for analytics, customer360 and personalisation, and to support systems that protect against cyberattacks.

These highly functional real-time data platforms can sound very expensive, but the newer ones use more modern architectures to minimise costs and reduce total cost of ownership (TCO).  It’s not unusual for these more modern data platforms to reduce TCO by up to 80 percent or more.  They do this by significantly reducing the size of the server footprint needed and achieve best-in-class real-time speeds by techniques such as working natively with the underlying hardware and incorporating sophisticated data parallelization and memory management techniques.

The benefits of AI in a multi-cloud, on premises hybrid environment

Many financial services firms, while moving much of their infrastructure to the cloud, still have legacy systems and are currently running in a hybrid environment. They require a real-time data platform that can run in this type of hybrid environment.

Multi-model, real-time data platforms can be deployed as software, regardless of whether the user is multi-cloud, on premises, using a single cloud provider or all three. It’s always on, so its performance is consistent throughout the database along with multi-site clustering that allows companies to put clusters in different data centres without sacrificing consistency.

So, if you are looking to embrace AI or neural nets to thrive and dominate in today’s competitive market, you need an engine that is powerful enough to analyse large amounts of data in real-time. Companies across the world are already enjoying savings that run into millions of pounds by reducing their server footprint and improving their real-time transaction throughput. Most importantly, they are gaining marketshare and meeting customer expectations that allow them to remain at the forefront in an increasingly competitive market.


Does the middle market have a financial edge?  



Companies tend to look up the ladder when searching for ways to improve efficiency and business performance. What are larger competitors, or others outside their industry, doing right that they can learn from and implement?

What smart technologies or bright ideas do they have that could create efficiencies for them, too?  

As we enter yet another likely volatile year for business, punctuated by recession, should businesses continue to only look up? And could the approach of a slightly smaller business offer more of a competitive edge? 

Large corporates tend to pioneer innovation in automation by simple virtue of the resources they have. Home to transformation directors and departments, with the ability to implement large overarching software systems, they pave the way for others and are often the first to digitise their source-to-pay cycle at pace.  

While growing businesses understand the merits of full automation, implementing it is often too expensive and it doesn’t bring the rapid realisation of benefits that they need. They need to consider what will bring them the biggest return on investment – and the reality is that those in the middle market don’t necessarily need all the elements of an ‘all-doing’ piece of software. What’s more, without dedicated personnel to project manage a transition, they frequently lack the currency of time to be able to comfortably transform working practices, and take staff with them on the journey, without taking resource from other areas of the business.  

For SMEs, digital transformation has never been quite as seismic a shift. Instead, they tend to take a modular approach, employing digital solutions only for particular areas of their finance department, where they need them. This has never been a particularly strategic move. Rather, for a growing business that values quick results and watches their outgoings with greater scrutiny than their larger counterparts, it’s something that suits them better. A modular approach also comes with very little disruption and can be implemented relatively seamlessly into their existing organisational setups. 

But while growing businesses are opting for a modular approach because it’s the most cost and time effective option for them, the benefits go far beyond that. The beauty of a modular approach is that it is agile. The last three years – with pandemics, an increasingly challenging climate and shifting geopolitical tensions impacting our global economy – have only served to remind us of how suddenly, and drastically, a business landscape can change. The companies that have weathered the storm are those that have reacted and adapted quickly – those that have been capable of changing the way they do things with little impact on day-to-day operations. A modular approach can offer just that.  

Businesses using modular finance technology can integrate small solutions that sync up with the rest of their processes, quickly and seamlessly – and these systems can be integrated into their existing Enterprise Resource Planning (ERP), too. There’s no restriction of a monolithic or aging piece of software either – finance teams can add and update small solutions to their daily operations without the upheaval of having to replace or update large IT infrastructures or wider working practices within the business to accommodate the new software.

Unrestricted by entrenched and hard-to-change systems, the speed with which SMEs are able to react to market changes is miles ahead. A prompt software add-on to manage risk, or create a quick fix in response to a market shift, can be virtually a knee-jerk reaction. SME’s abilities to bend and flex to today’s world efficiently is seeing them reap the benefits of a modular approach. It’s lean, it’s fast and it’s facilitating their growth with a strong competitive edge. And as some of these companies’ growth propels them into the large corporate sphere, they’re choosing to keep a modular approach to finance.  It will certainly be interesting to watch those middle-sized companies which grow to the extent that they find themselves competing in the same space. With no financial remodelling to assume a large ‘all-doing’ piece of software, they’ll be competing against their counterparts with completely different tools in their arsenal.  

With technology, working life and business needs continuing to change day to day, we have another year ahead of us that will see companies running to keep pace with each other – and fast-growing companies’ approach to finance could be the silver bullet that enables them to catch up with, and even take on, big enterprises. It might just give them a competitive edge against large corporates in these turbulent times.

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Consumer demand driving sustainable payments




Jenn Markey, VP Payments & Identity, Entrust


Sustainability is a buzzword that seems to be at the forefront of all industries. Since The Paris Agreement of COP21 back in 2016, organisations must now report on the sustainability of their actions per government requirements. While this has put pressure on organisations to re-evaluate their business plans to incorporate sustainability as a core business component, it has opened up vast opportunities for organisations to gain a competitive edge, while adhering to government regulations and improving sustainability. The payments industry has proved to be no exception.

From physical cash and card payments to digital payments through mobile phones, all forms of payment have an environmental impact in some way, and financial service providers must, therefore, evaluate their actions.

A growing consumer demand

Firstly, it’s important to recognise that the issue is not that payments are unsustainable. It is more related to consumer awareness and increased government oversight and regulation.

In today’s society, most consumers want to be sustainable and because of this, have a heightened awareness of the consequences of their actions. This means that if businesses don’t have an environmentally friendly payment option, they risk dissuading a large proportion of consumers from using their banking or financial services.

Jenn Markey

This even applies to the ways consumers make payments on a day-to-day basis. After the COVID-19 pandemic, we saw a drastic shift in popularity of contactless and digital payment formats for safety and convenience reasons. This trend continues to grow as consumers see the benefits that digital and contactless payments have on shrinking carbon footprints. Of course, incorporating digital payments can work towards this by reducing plastic waste associated with physical cards, as well as their packaging and production energy. And even more known to the consumer in a high-speed society, digital cards are instant – if you get a new card from a digital-first bank, in most cases, you can add it to your e-wallet and use it straight away. Speed paired with sustainability makes the digital card increasingly popular in today’s society.

A preference for physical cards

While it might seem that digital payment options like Apple Pay and Google Pay dominate in terms of popularity, research suggests that physical cards are still here to stay. In our recent consumer study, The Great Payments Disruption, respondents listed credit/debit cards with chips (50%) as their most preferred payment method, but contactless credit/debit cards (48%) were a close second.

With this in mind, it doesn’t have to be one or the other, as banks and financial institutions can improve their sustainability practices for physical cards whilst still abiding to the growing adoption of digital cards. Adopting sustainable practices will help banks and financial institutions adhere to ISO 14001 requirements, an internationally agreed standard that maps out the requirements for an environmental management system. What’s more, expected regulation and oversight following the Paris Agreement further highlights the need for banks and financial institutions to take action on sustainable practices. Such requirements outline ways for the sector to improve environmental actions by being more efficient with resources to reduce waste. Reducing the number of resources being used for printing cash or physical cards, for example, will not only improve company sustainability, but also lower production costs.

A further benefit for banks and financial institutions lies in the ability to make physical cards more sustainable by improving durability to extend their lifetime and, where possible, explore eco-friendly card substrates. Today, most payment cards are not biodegradable and, therefore, need to be disposed of in a manner that can be wasteful. Card manufacturers are working on more environmentally-friendly materials to reduce their carbon footprint in the future. Producing cards with durable graphics technology extends card life, meaning lower demand for new cards, fewer materials needed in the production of cards and card printers, and of course less waste. Additionally, extending the life of physical cards will help with the ongoing supply issues regarding chip shortages.

A more sustainable banking sector

Over the next few years, we can expect to see a continuation of the post-pandemic trend of cashless and e-commerce transactions. This paints a positive picture for sustainable payments as the ongoing adoption of alternative payments means a reduction in carbon emissions. Most importantly, banks and institutions can already incorporate more sustainable practices, such as printing cards in-house, and only when required, for near-immediate distribution to keep up the pace of instant e-wallets, while switching to more sustainable printing materials and practices.

What’s clear is that contrary to belief, the subject of sustainable payments is not a case of simply switching to digital payments and eliminating the physical card altogether. It’s about increasing the sustainability of physical cards to keep financial accessibility for every consumer in mind. This should be the next stop for banks and financial institutions on their journey to a more sustainable sector – one where we look after all of our consumers’ needs in today’s society.

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