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AI AND HOW IT’S LEADING THE FIGHT AGAINST FRAUD IN THE FINANCIAL SECTOR

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Geoff Clark, Managing Director, Aerospike EMEA

Much like many other sectors financial institutions have accelerated their digital transformation projects since the beginning of the pandemic. Lockdown meant that customers could no longer visit local branches or meet in person with their financial advisor. Financial institutions have no choice but to find alternative ways to serve their customers.

We saw banks quickly adapt and improve their automation tools to interact with their customers online.  Technologies that enable chatbots, credit card brokerage, contactless payment cards, digital verification for onboarding, online insurance applications, mobile apps, recommendation engines, robo-investing and robotic process automation (RPA) were just some of the many solutions deployed. Here in Europe, Ernst and Young (E&Y) reported an increase of 72% increase in the use of FinTech apps since the start of COVID-19.

Geoff Clark

Cybercriminals typically opt for the lowest hanging fruit and as financial institutions clambered to expand their digital services the cybercriminals looked to identify and exploit any weakness in the infrastructure providing the backbone for these technologies. Exploiting the vulnerabilities of financial institutions is not new as they have long been a coveted target for fraudsters. In the main, that’s due to the wealth of sensitive personal and financial information they hold. Throw into the mix pandemic relief funds, increased unemployment benefits, and stimulus payments, and you have the perfect playground for fraudsters.

A recent report found that every dollar lost to fraud costs financial service companies as much as $3.78 — an increase from $3.25 in 2019. But fraud’s impact is much deeper than financial loss. It drains company resources to investigate and prosecute fraud, damages reputations, and puts customer retention at risk. For these reasons alone, it is imperative that the appropriate systems and processes are in place to combat fraud.

 

Analysing Fraud

The majority of financial institutions still rely on dated rule-based systems to mitigate fraud risk. These systems can consist of thousands of predefined rules that store, sort, and manipulate data to find fraud patterns. For example, a rule could say, if there is a credit card transaction in one state and another transaction in a different state within a 30-minute time frame, then this is likely a fraudulent transaction and therefore it declines the transaction.

Rule-based systems are static, hard-coded, and time-consuming to update, and are often one step behind the sophisticated techniques fraudsters use. When fraud occurs, the typical response is to create another rule that prevents another attack, but it’s often too late.

Fraudsters continue to find new ways to commit fraud that rules don’t capture.

The trend we’re seeing from financial institutions is to replace rule-based systems with AI and machine learning-based systems as they’re more effective. These systems are largely self-learning and there is so much more data available and the more information they’re fed the more effective they can be. Rather than using tens of data attributes with rule-based systems, AI and machine learning-based systems can analyse hundreds of data attributes over enormous data sets and longer time frames to automatically detect with higher accuracy unusual behaviours that indicate fraud. For example, Barclays Bank has implemented AI systems to detect and mitigate fraud improving the customer experience in the process through the reduction of false positives and false negatives.

AI and machine learning-based systems are heading toward explainable AI (XAI), an emerging sector in machine learning that addresses how AI systems arrive at their black-box decisions. Financial institutions know the inputs and outputs of these systems, but they lack visibility into how they reached the results.

Building XAI into AI systems enables banks to understand how decisions are made and create better models to improve their systems by removing bias. For example, suppose a fraud system declines a legitimate customer’s credit card transaction. In this situation the financial institution needs to understand why the false positive has occurred so it can further refine its model.

XAI also has data privacy in its favour particularly when it comes to compliance. Under the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA)—and with other data privacy laws coming—financial institutions need to comply with specific mandates. They must be able to explain how they use a customer’s personal information and how they came to decision such as declining a credit card transaction. Overlaying XAI on top of their AI systems, ensures they have far great visibility into how decisions are being made by AI/ML systems.

 

Constructing a Fraud System Architecture

To emulate some of the industry’s more innovative organisations financial institutions must understand and pursue best practices when building their AI-based fraud systems. They should work alongside technology organisations but also work with their line of business managers to understand how fraud is impacting their business, what their greatest weaknesses are, how customer satisfaction can be improved, and how they can incorporate customer fraud/risk metrics into their customer analytics to improve their omnichannel marketing campaigns. Customer data collected and analysed by fraud teams are some of the most robust depositories of customer information making them invaluable to marketers.

When looking to build a world-class system, financial services firms should consider the following steps:

  • The fraud system needs to likely consume hundreds of terabytes of data, perhaps even petabytes for the largest firms.
  • Data must be continuously updated in real time from many sources such as internal customer and transaction data from storefronts, web pages, and mobile devices, as well as third-party demographic, behavioural, geo-location, identity management, credit bureau, and other data types.
  • This data will usually need to be prepared, e.g., cleansed, standardised, and normalised, to convert it into a form that AI/ML models can more easily digest and understand.
  • The data needs to move back to the central data platform to be further enriched.
  • At this point those financial institutions can fine-tune the model parameters, test and select the optimal machine learning algorithms, feed them with data to learn the underlying patterns, and validate the model’s accuracy to make good decisions using data that was not part of the training set.

After the above steps are completed and they are satisfied the model can be deployed to act in the microsecond moments that are necessary to fight fraud.

As technology evolves at such a fast pace all organisations must aim to implement a fraud solution that can combat the increasingly sophisticated fraudsters while implementing the following key elements

  1. Large data sets (TeraBytes, PetaBytes) consisting of both internal company data supplemented with third-party data;
  2. Highly optimised and validated AI/ML algorithms that detect fraud and minimise false positives and false negatives;
  3. A real-time data platform capable of running these AI/ML algorithms across enormous data sets in sub-millisecond response times to provide customers with the fast customer experience that they expect.

 

 

 

Business

IS SCARCITY OF TALENT THREATENING THE UK’S FINTECH CROWN?

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To be attributed to Rafa Plantier, Head of UK and Ireland at Tink

 

From the Square Mile to Canary Wharf, London has been the historic centre of global finance, with long-established trading exchanges and trusted financial institutions. In the digital era, it has also ensured that it’s moved with the times to become a thriving hub for fintech.

But the UK financial services sector is now at an inflection point. In the past year, London’s position as a global fintech leader has been under threat. Earlier this year, Amsterdam overtook The City as the largest European share trading hub. The European Banking Authority moved from London to Paris. And Dublin, Paris and Frankfurt are all competing to win a greater share of the European financial marketplace.

The culprits of the shift are the twin challenges of the pandemic and Brexit, combined with the speed of technological transformation in financial services – disrupting the traditional flow of people, capital and ideas. So the pressing question for the industry is: how do we maintain and, more importantly, accelerate momentum to retain London’s fintech crown?

The answer revolves around one key thing — people.

 

Diverse talent drives innovation

Attracting the best talent is crucial if the UK financial services sector is going to continue to thrive and retain its global position as the preeminent financial centre.

In February 2021, the Kalifa Review laid out a strategy and delivery model for the UK to lead the fintech revolution, covering five key areas. These included skills and talent, investment and international attractiveness and competitiveness. But what became clear was that access to the right level of highly skilled talent was one of the biggest challenges for UK fintech, with barriers spanning both domestic skills shortages and the need to access foreign talent seamlessly.

As a native Brazilian in the UK, working for a Swedish-owned fintech, I understand these challenges as well as anyone. I love London, but we must recognise that fintech firms need unique talent and skills, and such a talent base can’t be met by a single city – not even one as resourceful as London. Not only do fintechs require technology and data specialists, but also experienced managers with good knowledge of high-growth companies and financial services.

As someone lucky enough to have worked with startup and scale-up fintechs across the world,  I understand the unique grounding that comes from being a part of a high-growth global company. That’s why I believe it’s vital that we attract people from across the world with commercial experience at ambitious, rapid-growth businesses — so they can bring this experience to bear on the UK financial services sector.

At the same time, many companies face renewed pressure to create new services and products to meet expectations for growth. That is why it’s critical that the UK has access to people with the right technical skills in areas such as software engineering, DevOps, Cybersecurity and data science.

Put simply, having the smartest minds delivering the best products is good for everyone. It drives efficiency, productivity,  growth and, ultimately, prosperity.

 

The UK is open for fintech

The UK should be proud of being a fintech pioneer and the driving force behind legislation that helped usher in the era of open banking. There is now an exciting opportunity to take this even further. Having access to a diverse pool of talent and skills will empower the financial services industry to create innovative products to tackle complex social challenges, such as better B2B payments, financial inclusion and climate change.

The good news is that the UK government clearly recognises the role the industry has to play in driving growth and innovation. The 2021 Autumn Budget reaffirmed commitments to reskill the nation. With £3.8bn budgeted for skills and a formal criteria for the long-awaited Scale Up Visa, the Chancellor announced a set of proposals that will support the breadth of our sector — from startups right through to unicorns and incumbent banks. This will be essential for fintechs like ours to continue to trailblaze and for the UK to differentiate itself on the global stage.

In an increasingly competitive global landscape, and to sustain momentum, we must keep talent avenues open to attract the best of the best in the industry. As one of the fastest-growing areas of the UK economy, the benefits of nurturing UK fintech to drive productivity, growth and lead the UK’s post-pandemic recovery, cannot be overstated. 2021 has seen a surge of activity in the industry and I am eager to see what London’s fintech sector can achieve in 2022.

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THE EVOLVING TECHNOLOGY NEEDS OF THE FINANCE DEPARTMENT

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THE EVOLVING TECHNOLOGY NEEDS OF THE FINANCE DEPARTMENT

Jennifer Sims, Senior Consultant at Xledger

 

The world of finance software is evolving quickly, but with many new software contenders entering the market it can be a mindfield for organisations. Many finance teams are already using multiple accounting apps and software packages for bookkeeping, payroll and invoicing to service individual needs. Whilst it may work fine for now, this segregated approach isn’t sustainable for long-term growth. The world is swiftly moving to agile, automated ways of working. As a result, there is a growing need to choose suppliers that can fulfil multiple functionalities within the one platform.

Financial software is evolving at such a pace that it can be difficult to keep up. Changing up a finance solution is a big step and ease of migration can be a substantial factor in determining which solution provider to go with. But how do you choose a solution that will grow with your business and still offer something innovative in five or ten years down the line? The fear is always that non-techie organisations will end up falling behind, but in such a highly concentrated industry, how do you decide which solution would work best for you?

 

Cloud-first: the term that makes all the difference 

You could find a ‘cloud-based’ service with an application that comes with automated audit trails to make it easier to meet compliance and record-keeping obligations, for example. But for a solution to offer all of the many future benefits promised by the cloud, it needs to have been built specifically for a cloud environemt from the outset – ie. not an on-premise built system that has been later adapted. Cloud-first services (true cloud) were always intended to leverage economies of scale, cope with live updates, be accessible from anywhere with an internet connection, and to scale rapidly, to name just a few of the many benefits.

When we talk about innovation in financial technology, we’re not just talking about software that makes it easier for the financial controller to create reports. If eliminating reliance on Excel spreadsheets is the only tangible benefit you have to really shout about, you are missing out on the real deal. With ‘true’ cloud finance software the sky is the limit.

Finance and accounting technology needs to directly meet the needs of the finance function and support the wider business needs.  When looking at accounting software platforms you’d be hard pressed to find one that doesn’t now promise ‘cloud-based’ enterprise resource planning (ERP) capabilities. The cloud is nothing new, but it’s the way that a solution harnesses this environment that makes a real difference. And here is where there is a need to read between the lines.

 

Automate more with true cloud 

Historically, repetitive and manual tasks are typical of the finance role – from invoice postings to expense claims handling – these can overwhelm the finance team. Research by Xledger[1] has found that an enormous 91% of CFOs and finance decision makers are carrying out at least one of these repetitive tasks as part of their job. What’s more, senior finance leads are averaging a whopping 25 hours per week carrying out repetitive and manual tasks, compared with 15 hours for other finance decision makers.

A modern, true cloud finance system can enable your business to automate repetitive tasks and provide one source of truth so that teams can make informed business decisions that will help to scale a business. Bank reconciliation, dashboard creation and reporting are just some of the tasks that can be handled automatically.These capabilities are aiding overtasked finance teams and saving hundreds or thousands of hours a year.

Whilst different companies are at different stages in their digital transformation what is clear is keeping up with the latest technology is fundamental to the future success of an organisation.

Xledger is a true cloud finance solution. The basics include invoicing, robust general ledger accounting, detailed slice and dice reporting, purchase orders, billing, VAT reporting, and cash and bank payments. It also adds process and structure to the enterprise with procurement and inventory, budgeting and forecasting, and project accounting. Users are always on the latest version of the software and with regulation more stringent than ever today, Xledger is ISO 27001 accredited.

Choosing the right provider for your financial ERP solution comes down to whether it has the fundamentals right. When hosting all of your vital data in the providers’ own servers, it should evidence a highly tested security process that comes with backup services as standard.

As our demand for technology capabilities grows and as ERP models progress, innovation will become the structure for growth – and there is no end to the possibilities.

 

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