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Getting the most out of AI in finance

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A recent survey published in The Economist estimates that 85 per cent of IT executives in banking have a “clear strategy” for adopting AI in the development of new products and services. Nevertheless, some business leaders continue to exercise caution. To promote the adoption of AI, Alex Luketa, partner at artificial intelligence (AI) data management specialist Xerini, tackles some key concerns regarding the implementation of AI and discusses the measures in place to overcome them.

The Information Commissioner’s Office (ICO) has stipulated that businesses must address the privacy risks associated with generative AI before adopting the technology. Stephen Almond, the ICO’s executive director of regulatory risk said, “We will be checking whether businesses have tackled privacy risks before introducing generative AI — and taking action where there is risk of harm to people through poor use of their data. There can be no excuse for ignoring risks to people’s rights and freedoms before rollout.”

For many in the financial services sector, AI privacy and the possibility of input data being used to train models are key concerns. No one wants their company’s private information to be available to competitors, and keeping clients’ financial data secure is critical. However, there are tools available that can improve the privacy of training data. For example, redaction tools that strip out personal or sensitive information like names and addresses, preventing anything from being sent to the large language model.

Where privacy is a more pressing concern, private models hosted on a finance organisation’s own infrastructure can help solve any issues. Working with a trusted AI partner who can consult on risks and mitigation measures can keep privacy concerns at bay.

Will it break the bank?

AI projects were historically less certain. It wasn’t always possible to guarantee a time frame or know for sure whether a model would work, which increased the risk of high upfront quotes or projects going over budget. Nowadays, there are fewer unknowns and a greater number of tools at a software engineer’s disposal. For example, Xerini developed Xefr, which works alongside existing processes and can be customised for more efficient integration.

AI has moved from the realm of specialist software development to become far more standard, making it a more competitive and affordable marketplace. The number of competing open-source services gives AI software consultants leeway when advising clients on the most cost-effective solution.

Will jobs be lost?

AI has the potential to enhance the effectiveness of many professionals by automating administrative tasks, allowing staff members to increase their overall productivity. For example, finance managers can use AI tools to analyse bank statements, tax documents and invoices, freeing them up to focus on client management and other tasks.

It’s natural for people to be concerned about how AI may impact their employment, so

when discussing the integration of AI, it’s crucial for software consultants and management teams to emphasise improvement rather than substitution. An effective AI implementation partner can help finance firms understand how to maximise their team’s potential with the help of AI tools.

Will it be biased?

The potential for bias removal ultimately hinges on the finance and banking data itself, a challenge amplified in a society with inherent biases. Software engineers can take steps to reduce the impact of biases by introducing guard rails, priming a system for bias reduction, or establishing a traceable answer source backlog. There is still work to be done, and bias in AI models will remain a topic of immense active research for some time yet.

Every business, no matter its size or current situation, can start its AI journey today. You can leverage readily available tools such as ChatGPT, integrate existing data and systems using customisable platforms like Xefr, or even create a custom private model. Partnering with an expert consultancy like Xerini can help you overcome implementation barriers and get the most out of AI.

 

About Author: Alex Luketa is a senior software architect with over 14 years of experience working in the financial sector, designing and building a variety of systems for clients including Morgan Stanley, Goldman Sachs and Credit Suisse. Alex is also experienced in the burgeoning field of artificial intelligence, and has developed many practical AI applications, including an innovative in-car app that uses machine learning to improve road safety.

Finance

How technology can help win the war on financial crime

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By Andrew Doyle, CEO of AML compliance software, NorthRow

 

Financial crime is on the rise and the stats are alarming. In the UK alone, 64 percent of businesses (according to data from the Global Economic Crime Survey) have experienced fraud, corruption or other incidents of financial crime within the last 24 months, while ONS stats show there were 3.7 million incidents of fraud in England and Wales in the year ending December 2022.

So it’s no surprise that financial institutions and other regulated firms are under increasing pressure from regulators (and the ever-evolving legislation they must adhere to) in the battle against dirty money. Regulators are imposing crippling fines for any compliance breaches, not to mention the significant reputational damage that comes with non-compliance.

Historically, financial firms have employed large numbers of staff to combat money laundering, but regulators are now expecting to see digital solutions in place to counter the risk of financial fraud, and with good reason. Technology can be the deciding factor in the war on financial crime and here’s why:

Better risk detection

Technology platforms can analyse historical data to predict potential incidents of money laundering, enabling organisations to take preventive measures, while also identifying unusual patterns or changes in customer risk profiles, which may also indicate suspicious activity.

Advanced analytics can help companies identify complex patterns across large datasets, making it easier to detect networks of fraud. It is also possible to assign risk scores to transactions or entities based on their likelihood of being associated with money laundering. This helps in prioritising high-risk cases for investigation.

Andrew Doyle

Enhanced customer due diligence

Automated software platforms can analyse customer information, public records, and other data sources to perform thorough due diligence on clients, identifying potential risks or suspicious behaviour before they are signed up.

RegTech automates the process of verifying customer identities and conducting enhanced due diligence on individuals and on companies, ensuring compliance with Know Your Customer (KYC) and Know Your Business (KYB) regulations, both vital components of anti-money laundering efforts.

More accurate identity verification

Biometric verification is a powerful tool in enhancing anti-money laundering and fraud detection. It involves using unique physical or behavioural characteristics of an individual to verify their identity. Traits like fingerprints, facial features, iris patterns, and voiceprints are unique to each individual and are nearly impossible to replicate or forge. This makes them highly reliable for verifying that clients are who they say they are.

Biometric verification can also reduce the number of false positives in fraud detection by providing a highly accurate means of confirming the identity of a customer. This leads to more reliable results and lessens the need for manual intervention.

Continuous and real-time monitoring

Real-time alerts allow for immediate action when suspicious activity is detected. This can prevent or minimise potential financial losses and damage to a company’s reputation. By identifying and acting upon suspicious activities in real-time, financial institutions can reduce the risk of financial losses associated with incidents of economic crime.

Continuous monitoring with real-time alerts can also help refine the accuracy of anti-money laundering systems over time. This reduces the number of false alerts and decreases the need for manual intervention.

To the future

According to data from Capgemini, 68 percent of UK institutions are already looking into real-time anti money laundering monitoring systems to stay ahead of potential threats while 86 percent, says Refinitiv, agree that innovative digital technologies have helped them identify financial crime.

So the data tells us that companies are already heading in the right direction when it comes to fighting fraud, but as the landscape of financial crime continues to evolve, financial firms must ensure they do the same.

By leveraging the right technology, businesses can ensure they not only meet regulatory requirements and safeguard their operations, but also protect their reputations and crucially, maintain that all important customer trust.

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Finance

In 2024, payments will evolve to broaden accessibility

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Attributed to Roy Aston, COO at Paysafe.

 

As we look to 2024 and beyond, businesses will need to adapt experiences to changing consumer needs and demands, working with payments providers to increase accessibility, offer broader choice, and more.

We break down some the forces driving evolution in payments over the coming years.

Payments need to be available to everyone, everywhere

Regardless of their location or situation, consumers do not want to wait when it comes to payments. The proliferation of smart devices has given users access to everything, all at once, and this is also expected when making transactions.

In 2024, banks and financial institutions will continue to push ahead with this journey to offer smooth, secure payments to everyone, everywhere, delivering services at the lowest possible barrier to entry. This also means ensuring consumers, even those that are unbanked or underbanked, have access to remittances and cross-border payments.

The first step in achieving this goal will be to improve reliability, security and availability, which may see traditional payment methods like debit and credit cards – still the most popular payment methods – become less dominant, while alternative payment methods (APM) like eCash and digital wallets will grow.

This is because, with the right payment provider, merchants can ensure these APMs are available anywhere in the world – eCash, for example, does not require a bank account to use. In addition, digital wallets and online cash can offer swift, secure transactions, helping users overcome security issues by not requiring them to enter their financial details.

Financial companies will embrace collaboration in 2024

While businesses can address consumer payment concerns using APMs, they must also look to bolster their own defences as the threat landscape changes. Increasingly advanced technology, like AI models, are now accessible to far more people, including threat actors.

To combat this escalating threat, it’ll be no surprise to see more financial companies collaborate in 2024 as they seek to improve cyber risk mitigation. This makes perfect sense – and would be a positive step for the industry – though it is easier said than done.

Businesses must share data legally, while aimed toward a positive purpose, rather than for pure profit. For example, if a financial organisation gains intelligence on a cyber group, they could share this with other companies to protect against bad money movement.

Ideally, collaboration could help improve anti-fraud, anti-money laundering, and cyber security measures, and more broadly reduce risk for businesses and consumers alike. But first, thinking around data governance may need to change.

Existing trends will evolve

While exciting new trends will emerge in 2024, we’ll also see the evolution of some that have yet to reach their full potential.

Embedded payments, for example, will continue to develop, with more businesses bringing together financial products with features like loyalty schemes to offer more added value to consumers.

Decentralised finance, too, should continue to build momentum in 2024. While decentralised finance, and specifically NFTs, have faced challenges this past year, it will be no surprise to see companies get to grips with changing regulatory requirements and continue to build in this area.

Open banking could also see a big 2024, with more APIs becoming available, and companies starting to develop new solutions to enhance customer experience and reduce friction in the payment ecosystem.

And while evolution rather than revolution is a necessity in technology, it’s always exciting to look ahead to the big trends that could shape the future – perhaps not in the year ahead, but beyond.

The future is quantum

Quantum computing is a trend that is as exciting as it is potentially frightening. Able to perform computations that are exponentially faster than ever before, quantum computing represents a new frontier and it will be thrilling to see how it is used in the years ahead.

Combined with AI, for example, quantum computing could optimise processes at a speed and scale never seen before – with serious benefits passed onto consumers.

In the nearer term, however, ensuring payments are available and accessible for everyone must remain the focus in 2024.

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