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WHY FINANCIAL SERVICES COMPANIES ARE PREPARING TO TAKE THE QUANTUM LEAP

Source: Finance Derivative

Authored by Jason Hill, Reply

Financial services companies are no strangers to complex algorithms, but even today’s most sophisticated software can only analyse a fraction of available data. However, quantum computing is about to change all that. Quantum computers will far surpass the limitations of classic computers: performing complex tasks within minutes and completing actions that were once deemed impossible. So what does this mean for financial services?

Use cases in quantum

The potential impact of quantum computing can hardly be overstated. Just as the development of the microprocessor in the 1970s unlocked the power of personal computers to the average end user, and the proliferation of the Internet in the 1990s revolutionised the way the world communicates; quantum computing, with its vastly superior processing power, will have a transformative impact on virtually every industry and individual.

Jason Hill

In financial services, there are a myriad of applications where it can be applied including reinforcing cyber security, targeting investments, profiling risk, optimising portfolios and liquidity management, from context-defining indicators to collateral optimisation.

In the portfolio optimisation case for example, quantum computing could be used to limit a company’s exposure by identifying a portfolio of assets with minimal correlation between them. This is particularly useful when diversifying the portfolio of securities to reduce any risk that might impact return. Furthermore, as the size of an investment portfolio increases, so does the complexity of the computational problem. Quantum computing can quickly solve problems that would take days, months or even years on traditional computers.

Quantum will ultimately help financial institutions prepare for their future and get ahead of their competition by knowing more, more quickly. For example, Reply recently worked with a credit institution to develop a quantum computing algorithm that allowed it to optimise daily collateral costs related to over-the-counter derivatives trading. This took into account non-linearities in the model and involved a dedicated simulation-based optimisation tool to plan for multiple scenarios.

From quantum computing to predictive analytics

One particularly interesting application in quantum computing is predictive analytics which can be used to forecast future events based on past data. Quantum computing can even help users make smart assumptions about data that doesn’t exist. For example, a bank’s cash flow can be projected using the so-called the Monte Carlo method which involves getting a clear, statistical picture based on a high number of simulations. Monte Carlo simulations are a form of predictive analytics and because they require a lot of calculations (with potentially many variables), quantum can process them much faster. This is particularly useful in portfolio management as for example, it allows an analyst to determine the size of the portfolio a client would need at critical times, such as at retirement, to support their desired lifestyle.

Financial companies aren’t at a loss for historical data sources: contracts, transactions, inquiries, and claims. These are the solution to a more certain future. By learning from past knowledge companies can make future estimations with higher accuracy.

Where can we go from here?

The performance ability of quantum computers far outweighs current possibilities. The range of problems that can be addressed thanks to Quantum Computing is broad: it does not stop at combinatorial optimization but, instead, crosses into other areas such as machine learning and quantum security. Quantum neural networks and quantum internet networks are just two of the more interesting ones.

Quantum machine learning (QML), makes the most of the advantages of two current themes: quantum computing and machine learning. Although QML is still in its early stages, it nevertheless offers a whole new world of opportunities, combining the new knowledge provided by machine learning with the accelerated calculation potential and the enhanced accuracy of quantum calculations.

It is not a trade secret to know that today, all major financial services companies have departments focused on Big so they can benefit from the huge amount of data collected over the decades. And with the increase in remote cloud computing power, much more complex prediction models can be employed.

The race is now on for the companies that provide quantum computing solutions to fully realise their potential but once those solutions are in place, they will have a huge advantage over their competitors. It makes sense for them to partner early with companies who have existing use cases in quantum computing. Because the companies that adopt Big Data and Machine Learning processes will build more commercially efficient offerings that will have customers lining up.

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Business

AI in Investment: A Guide for Asset Managers

Source: Finance derivative

Giacomo Barigazzi ,Co-founder, Axyon AI

In today’s dynamic investment landscape, the race to harness new technologies for a competitive advantage is more fierce than ever. For those in the asset management sector, embracing innovation isn’t just a choice—it’s a necessity to stay ahead in the relentless pursuit of investment opportunities.

The bedrock of investment management has always been grounded in exhaustive research and due diligence. However, the rapid evolution of technology mandates a shift in strategy. Now, it’s critical for leaders in this space to not just familiarise themselves with, but to fully integrate advanced technologies such as artificial intelligence (AI) and machine learning (ML) into their processes.

Exploring the Varieties of AI in Asset Management

It’s essential for asset managers to recognise the specific AI technologies available to them, as this understanding can greatly influence their approach to investment strategy. Broadly speaking, AI in asset management can be categorised into generative and predictive models, each with distinct capabilities and applications.

Generative AI, powered by advanced machine learning techniques, is designed to produce new data that mimic real-world information, such as text, images, and more. This technology is especially useful for creating realistic and diverse datasets, enhancing personalisation, and improving the accessibility of financial services. For asset managers, generative AI can play a crucial role in developing innovative solutions and strategies by generating novel insights and scenarios.

On the other hand, Predictive AI focuses on analysing historical data to forecast future trends and patterns. This aspect of AI is invaluable for asset managers aiming to anticipate market movements and adjust their strategies accordingly. The predictive capabilities of AI provide a strategic edge by enabling more informed decision-making and risk assessment.

For asset managers intent on leveraging AI to enhance their operations, distinguishing between these AI types is a fundamental step. By adopting the appropriate AI technologies, they can significantly improve client outcomes, operational efficiencies, and, ultimately, investment performance.

Creating a personalised client experience

Improved performance is not the only advantage AI brings to asset management; it significantly enhances the client experience by enabling the development of personalised services. For clients, generative AI tools like chatbots and virtual assistants establish a continuous support system that provides instant responses to queries, as well as up-to-date insights on market developments and portfolio adjustments.

A heightened level of personalisation throughout the investment journey ensures clients are not just satisfied but also better informed – a dynamic which undoubtedly fosters greater human relationships in the industry.

Strategic considerations for asset managers

As the widespread adoption of AI in the financial services sector continues to materialise, asset managers face a crucial task in nailing down the right WealthTech solution. It’s not just about adoption; it’s about making strategic choices.

Ultimately, companies expect to see a strong ROI after adopting an AI solution. Only by making a well-informed choice will they see the expected tangible impact of AI in asset management. A lack of due diligence in the procurement process risks introducing a solution that is both ineffective and disruptive.

Integration is key. AI solutions should align seamlessly with existing systems to avoid unwanted disruption to day-to-day operations. Therefore, choosing a provider that is ready to provide extensive training to support a smooth assimilation into operations should also be a priority for management.

There is an element of self-assessment required in the decision-making process. By recognising areas in a firm that require enhancement and understanding the specific value offered by each AI solution, leaders will be best positioned to identify a product that will bring significant improvements in targeted areas.

With a sea of options available in 2024, selecting an AI solution demands thoughtful consideration. Managers need to assess how each aligns with their investment strategy and delivers results. Consulting with experts and analysing case studies from similar businesses equips managers with valuable insights for informed decision-making.

AI as an empowerment tool

While AI will be a revolutionary tool in the asset management industry that will drive efficiency and innovation, it is not intended to replace the human touch. The technology should be viewed as a tool that empowers asset managers to focus on high-value work of greater importance to clients.

AI’s transition from a nascent curiosity to an integral business tool underscores a pivotal shift in industry dynamics. Asset managers who are slow to adopt these technologies risk falling behind in a market that’s increasingly influenced by AI’s capabilities. By contrast, those dedicated to swiftly and responsibly adopting this technology will likely be rewarded with an extra edge in performance.

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Business

BALANCING ACT: HOW A MULTICHANNEL APPROACH TO COMMUNICATIONS CAN DRIVE ENGAGEMENT 

Source: Finance Derivative

Tom Rahder, from Esendex, discusses how digitisation, and use of mobile messaging has transformed the banking industry, and where it can go from here. 

Barely a week goes by that we don’t see reports of banks closing more of their branches. 

And while they might come under fire for it at times, these closures reflect the fundamental shift in how we do banking today. 

Covid accelerated the change, of course – but digitisation of financial services had been happening for a long time. The rise of online-only challenger banks, and a growing number of ways to manage our finances online, has meant that the local high street branch has become redundant for many people. Young people in particular may never step foot in one because they have no need to: they can do everything from an app on their phone instead.

Most of us don’t think twice about using self-serve and/or automated digital tools for straightforward transactions, like transferring money between accounts. 

But our research also suggests that nearly 70% of those experiencing financial difficulties would rather manage their own repayment plan rather than have an ‘unpleasant’ conversation, and almost two-fifths would opt for an automated service over speaking to a human. So, far from being ‘second best’, an automated environment can provide the privacy people need to address complex challenges they’d once shied away from.

It goes without saying that any branch closures must be sensitively handled and communicated to ensure that the customers who still rely on them, many of whom may be elderly, disabled or vulnerable, aren’t left behind. 

To their credit, most banks recognise this, and will point people to nearby branches, set up pop-up counters in public places, and remind them that the Post Office is available for everyday banking. They also offer free digital skills training courses to empower customers to manage their finances in a fast, secure and convenient way. 

Unlocking the value of multichannel communications 

The reason why so many customers prefer to self-serve is largely down to the range and quality of communications available today. 

Forward-thinking firms recognise that choosing the right channels is critical if they want to deliver outstanding experiences in a competitive sector. 

A multichannel strategy doesn’t mean introducing as many channels as possible but meeting customers where they are, and continually monitoring the effectiveness of all your communications. It means balancing ease and convenience with security, and understanding how different channels drive actions – whether it be a clear and direct SMS for two-factor authentication, or WhatsApp messaging for dialogue.

The financial services sector, like any other, is impacted by wider consumer trends, so we’ve seen a big uptake of WhatsApp for Business messaging recently. It’s a channel that most people are already active on and feel comfortable with – so they are usually more likely to engage with banks, building societies and other lenders that offer it.

The good thing about WhatsApp is that it allows contact centre teams to manage multiple conversations at once, so people don’t have to endure long waiting times to speak to someone on the phone. It can also bring down the cost-to-serve, and free up staff to support customers who need it, including those who can’t easily access a branch. 

Two-way messaging, available via SMS and chat too, helps customers to feel listened to and deepens their connection with a business. They can discuss their issue and come to a resolution in a way that is most convenient for them, and have a written record for reference.

Looking ahead

As mentioned before, consumer demands are changing all the time – the challenge is keeping up. Fortunately, there is a growing number of APIs that plug your business messaging platform, allowing you to build on your capabilities with services such as RCS Messaging (Rich Communication Services Messaging). This interactive content, which can include videos and audio, is a powerful way to reach people via their SMS inbox.

Sometimes, we’re thrown a curveball – for example, reports that Gen-Z is shunning smartphones in favour of ‘dumbphones’. 

Whether this trend takes off remains to be seen; what’s important is that organisations in all sectors are able to accurately track metrics like open rates and ROI. It also reminds us that the ubiquitous SMS, with its open rate of 98%, remains as relevant today as ever. 

Last but not least, don’t be afraid to ask them exactly what they want too, rather than waiting for them to switch off and go elsewhere. A quick-fire SMS survey is a good way to gauge opinion and track trends over time, so you can invest in the channels that will deliver the most value to both your customers and the business. 

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Business

Digital Identity: Safeguarding FinTech from Fraud 

To be attributed to: Marcel Wendt, CTO and Founder of Digidentity

The digital transformation renaissance is reshaping the finance industry, with the number of neo-bank users already surpassing 39 million, with this predicted to soar to 386 million users by 2028.

Neo-banks heavily rely on digital platforms, making them susceptible to cyberattacks and data breaches. If a neobank’s security measures are breached, whether from phishing scams, malware, less stringent verification processes or third-party integration, consumers’ sensitive financial information could be compromised.

Rigorous digital identity solutions and safeguarding measures can not only reduce the risks of fraud but also establish a stronger level of consumer trust.

Marcel Wendt

Old Scams, New Techniques  

With the rise of more ambitious cons, and malicious bad actors looking to target consumers with phishing scams and malware, the call for better security has never been more prevalent. 

Systems must be developed to help protect consumers. This will not only mitigate the threat from bad actors but also help elevate the trust people have in the company’s ability to protect them. 

Ultimately, users are at the endpoint and there is a responsibility for them to be aware, vigilant and educated to detect risks, but the financial sector needs to be armed with the right tools to protect identities in the first place.   

Fraud now accounts for over 40% of all criminal offences in England and Wales. This figure shows the sheer scale that fraud has in the UK. The reasons for this are varied, but one key solace is that it becomes easier to protect your identity online if you have the right technological know-how.  

It’s therefore more important than ever before to have the strongest identity verification processes in place, to ensure people are who they say they are. Identity verification plays a vital role in safeguarding the integrity of the financial system, protecting customers, and ensuring compliance with regulatory requirements.

Passwords and PINs are quickly becoming outdated with multifactor authentication becoming the most secure form of verification, adding an extra layer of security to the verification process. Strong Consumer Authentication (SCA) should be the only method being used to keep consumers and their data secure.

Biometric verification is also increasingly being adopted due to its accuracy and difficulty to mimic. Some financial institutions analyse user behaviour patterns including transaction history as well, to help verify identity. Deviations from normal behaviour can trigger further verification steps or alerts for potential fraud.

Building a Safer Future for FinTech  

In the UK, there have been provisions to ban cold calls on all financial products and introduce a legislative commitment for the tech sector to protect their customers. This is a step in the right direction, as phishing scams are the most common type of scam in the UK. 

To support this directive, businesses within the financial industry should also consider implementing digital identity protections.

There needs to be a strong emphasis on both the authentication and verification processes within companies, to show that people are not only proving who they are but also systems put in place that are secure enough to consistently confirm that people are authorised to access the information they are requesting.

The evolving technology around Digital Identity Wallets is helping streamline this process for all parties involved, by having a one-stop-shop for identification, verification and authentication all in the same place, this creates a unified process of who the person is and what they can access.  

Security Elevations  

Incorporating features such as biometric verification and multi-factor authentication, alongside capabilities to digitally sign contracts, letters, and agreements with electronic signatures will elevate the security measures companies can deliver. This ensures that transactions like wire transfers, online payments and purchases are authorised by the customers through identity verification. These advanced verification and authentication methods add layers of security, making it more challenging for malicious actors to impersonate legitimate users and conduct fraudulent transactions. 

Yes, the rise of AI brings higher risks of fraud in bad hands, however, the use of AI to verify identity remains part of the solution. 

Within the UK, companies can reach Strong Customer Authentication (SCA), by introducing Multi-Factor Authentication (MFA) and biometrics through a trusted provider such as Digidentity. 

While Two-Factor Authentication mandates two features, MFA can involve more than two, typically incorporating a combination of factors from various categories to enhance security by providing an additional layer of protection.

Technology is evolving but the speed of prioritising and progressing security can’t slow down. The responsibility for protection falls both on the company’s safeguarding and also the consumer’s vigilance. Both parties can’t guarantee foolproof systems. Innovation must be at the company’s foremind and the potential risks at the back of the consumer’s minds, this will create a partnership that will enable evolving safeguarding measures to keep pace in the explosively fast pace of risk mitigation.

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