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HOW FINANCIAL SERVICES CAN MEET THE EU’s NEW AI REGULATIONS

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Alix Melchy, VP of AI, Jumio

 

The European Commission recently proposed a new regulation framework around the use of AI. The draft legislation seeks to regulate the use of AI proportionate to the level of risk each AI system presents in order to promote ethical and trustworthy use and development of AI in Europe. Moreover, the legislation will ban AI systems that present unacceptable risk and impose strict requirements on those which are considered to be high risk.

Although the UK has left the EU, there are some sectors that are still closely linked to the European banking sector — for example, lending. Therefore, we can expect financial services organisations, even those based in the UK, needing to keep abreast of these regulatory requirements, or else risk severe consequences.

Let’s look at how organisations in the financial services sector can better prepare themselves.

 

AI is no magic wand

AI is regularly positioned as an essential investment to stay ahead of the competition, provide greater customer service to customers, deliver more relevant services and offerings, as well as helping to transform many back-end processes. Its potential use cases have only increased further as we see more bank branches than ever having to close due to the impact of the coronavirus pandemic and consequently more consumers becoming dependent on digital banking services.

However, this raises the serious question as to what would happen if the algorithm used in financial decisions was tinged with bias. Such biases could negatively impact the way millions of consumers and businesses borrow, save and manage their money.

We need to be aware of the limitations of AI and learn to set reasonable expectations with it. To do this, we must take a step back and separate the actual technological capabilities of AI from magic and remind ourselves that AI is a tool, not a solution for everything and must be used responsibly. If businesses are going to start implementing AI, they must specify the exact problem they are trying to solve in order to select the best suited options and come back to this initial goal time and time again throughout the project to ensure it still aligns.

 

Eliminating bias

Another important factor to consider is the data that is going to underpin an AI model. AI systems are built on sets of algorithms that “learn” by reviewing large datasets to identify patterns, on which they are able to make decisions. In essence, they are only as good as the data they feed on.

Financial organisations must ask themselves whether they have enough of that data and, if so, whether it is representative of the population. Algorithms are data hungry and this data needs to be well stratified. It’s absolutely vital that the data represents society fairly so that it doesn’t reproduce historical biases. While it’s possible to buy datasets to speed up the process of building AI models, it is important to ensure that this data meets the required criteria rather than simply being a large data set. This allows employees in the financial services sector to treat customers fairly and, when combined with appropriate modelling and processes, allows them to maintain transparency and accountability in their decision-making processes to avoid legal claims or fines from regulators which can cause deep reputational damage.

 

Getting it right

Another process that businesses must implement in their AI practices is a pilot testing phase to ensure that the algorithm is working as expected and to better understand why an algorithm is making a certain decision. This allows companies to assess feasibility, duration, costs and adverse events to better understand why an algorithm is making a certain decision before it’s put into a real-world scenario.

It’s also important to note that the EU’s guidelines highlight that AI software and hardware systems need to be human-centric and a machine cannot be in full control. Therefore, there should always be human oversight and humans should always have the possibility to override a decision made by a system. Every algorithm has a set of limitations, and so, when designing an AI product or service, financial organisations should consider the type of technical measures needed to ensure human oversight. This is vital when it comes to understanding how AI is working, finding ways to train it and ensuring that it’s working as expected.

 

Establishing ethical AI

As mentioned earlier, a key driver for the EU Commission’s plans to take a risk-based approach to AI is to promote trustworthy AI systems that are lawful (complying with all applicable laws and regulations) and ethical (ensuring adherence to ethical principles and values) in order to avoid causing unintentional harm.

If financial organisations are to reap the benefits of AI, we must first minimise the potential harms of algorithms by thinking about how machine learning can be meaningfully applied. This means we need to have a discussion about AI ethics and the distrust that many people have toward machine learning.

 

There are some key areas to consider when it comes to ensuring AI is ethical:

  • Usage consent: Make sure that all the data you are using has been acquired with the proper consent.
  • Diversity and representativity: AI practitioners should consider how diverse their programming teams are and whether or not they undertake relevant anti-bias and discrimination training. This will draw upon perspectives of individuals from different genders, backgrounds and faiths, which will increase the likelihood that decisions made on purchasing and operating AI solutions are inclusive and not biased.
  • Transparency and trust building: Accurate and robust record keeping is important to assure that those impacted by it know how the model works.

In the financial services industry, there are many ways that AI can be leveraged. For example, in the document-centric identity proofing space whereby documents (such as a passport) are matched with a corresponding selfie to connect real-world and digital identities, proving AI is being used in an ethical way is becoming crucial. Gartner predicts that by 2022, more than 95% of RFPs for document-centric identity proofing will contain clear requirements regarding minimising demographic bias, an increase from fewer than 15% today. This shows that there’s a real opportunity to leverage AI solutions to provide the best service, but financial institutions must ensure that they are doing so in an ethical and accurate way by focusing on these key areas discussed. By following this guidance, businesses can ensure that their AI projects start off on the right foot and pave the way for regulatory compliance.

 

Finance

The penny has dropped – the finance sector needs Data Governance-as-a-Service

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By Michael Queenan, Co-Founder and CEO at Nephos Technologies

 

In our data-driven world, the amount of data is growing exponentially and it’s predicted that the amount generated each second in the financial industry will grow 700% this year. Leaders of financial services organisations have realised two things since the start of the pandemic – that data on their customers and services is their greatest asset and that they must embrace technology to make intelligent business decisions to grow successfully and outperform competitors.

Since the financial sector holds arguably the most valuable and sensitive information, organisations must do more than just store this data. They need to ensure its security, integrity, and governance so that it’s useful in improving the brand’s customer experience, innovating products and services or predicting future trends to improve risk management.

Yet without a robust data governance model – a strong set of rules and processes for what data means, and how it is categorised, owned, accessed, stored, and used – data is worthless. Only when an effective data governance model has been established, will data meet regulations and be secure. Data leaders must shift gear in their data processes to avoid hefty compliance penalties and unlock potential value from their data assets.

 

The data governance challenges faced by financial sector organisations

The barriers for achieving ‘good governance’ are many and varied. Ignorance of the benefits of data governance is a major hurdle for developing a governance strategy. Many financial firms have invested – at significant cost – in data governance tools, but struggle to deliver the benefits they are looking for. Many don’t have the right skills and resources to maximise or set the right metrics to measure the business value. Some are compromised by unoptimised gaps in their approach.

With many different elements to master, data governance is complex – from identifying the right tools to managing the challenges presented by encryption, all whilst ensuring that data quality is sustained and data is managed responsibly.  The negative impact of misplaced investment in ineffective data governance strategies can be significant, for the short and long-term.

 

Why data governance matters

With the acceleration of digital adoption in the financial services industry, it has become crucial to deliver seamless, intelligent customer experiences. Data governance is the key to managing data flow, ensuring compliance, and scaling up. Proof that data governance matters is evident in the Master Data Management Market growth prediction, from $16.7 billion in 2022 to $34.5 billion by 2027.

Data governance is a comprehensive methodology for ensuring the quality and security of the company’s data. The various benefits of an effective data governance strategy include minimised risk, coherent policies, metrics and processes, and better implementation of compliance and enhanced data value. However, for financial services, there are significant advantages as a result of the following:

  • Data governance saves the company money by increasing efficiency. Precious time can be saved by having good quality data and a single source of truth, with less duplication of data, and less time needed to correct data errors.
  • Good data governance gives the business confidence in having accurate and trustworthy data, the holy grail for delivering outperforming customer experiences.
  • A data-driven culture can also be introduced to your business through good data governance. With the ability to gather critical customer and market insights that can guide the direction of your business, data governance allows financial institutions to drive innovation and gain competitive advantage.

 

Bridging the governance gap with Data Governance-as-a-Service (DGaaS)

Increasingly organisations are turning to the ‘as-a-Service’ model to bridge the gaps in their data governance capabilities, as well as ensure critical alignment between objectives and results. This dedicated approach aims to minimise the risk of investments and delivers the strategy and proven technologies required to ensure data governance success.

DGaaS can be applied across each major component required to deliver good data governance. First, it uses software tools to scan all data within a typically complex financial services data infrastructure in its data discovery and classification phase. Without this detailed insight, organisations can’t always identify their data assets, any data mishandling and the level of risk generated.

The next part of the process is creation and documentation. This means organisations can drive their governance objectives through to execution, while removing the operational and recruitment overheads, which means they can purely focus on value created from data. In doing so, organisations can convert the raw outputs from the toolsets into meaningful business outputs.

With a holistic approach, DGaaS allows financial services organisations to focus on the transformational potential of data while critically staying compliant.

 

Reaping the benefits

Data is a vital asset to enable financial sector organisations to build the right capabilities to deliver their services and remain competitive. With a robust data governance model, financial firms can assess risk, predict trends, and seize market opportunities based on data-driven insights. Only data-driven processes, built on high quality and effectively governed data, will enable them to build outstanding customer experiences. It’s essential that leaders realise data governance is a fundamental discipline, not a luxury, and establish an effective model to formalise processes and responsibilities before their data lets them down.

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Financial Stability Board Gives Full Support to Wide LEI Use in Global Payments

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Clare Rowley, Head of Business Operations at the Global Legal Entity Identifier Foundation

The strongest recommendation yet by the Financial Stability Board (FSB) that the LEI should be used more widely in payments will catalyze increased global LEI adoption. The most immediate intention is in facilitating cross-border payments. GLEIF explains why this makes it the perfect time for financial institutions to become Validation Agents within the Global LEI System.

The Financial Stability Board (FSB) has put its full weight behind a landmark recommendation that the LEI should be widely adopted across the global payments ecosystem. In July 2022, the FSB published a report encouraging global standards-setting bodies and international organizations with authority in the financial, banking, and payments space to drive forward LEI references in their work. The report also recommends guidance and further outreach on the use of the LEI as a standardized identifier for sanctions lists and as the primary means of identification for legal entity customers or beneficiaries, with specific reference to customer due diligence and wire transfers.

A primary near-term goal of the FSB’s most recent report, published as part of the G20 Roadmap for Enhancing Cross-Border Payments, is to stimulate LEI to use initially in cross-border payment transactions. By helping to make these transactions faster, cheaper, more transparent, and more inclusive, while maintaining their safety and security, the LEI has been deemed by the FSB to support the goals of the G20 roadmap.

As a result, banks and financial institutions will now be compelled to move quickly to incorporate the LEI as an integral component of their cross-border payments infrastructure, since there are huge benefits in doing so. In addition to supporting lower costs and enhanced transaction speed and transparency, the LEI can also facilitate straight-through processing (STP) and sanctions screening, while easing compliance with Know-Your-Customer (KYC) due diligence.

Additionally, the report recommends that standards bodies (e.g., BCBS, CPMI, IOSCO, FATF) and international organizations (IMF, OECD, World Bank) should consider how the LEI may be used as a standardized identifier for sanctions lists or as the primary means of identification of legal entity customers or beneficiaries. This demonstrates the broader ecosystem needed to support cross-border payments evolution – an ecosystem based on a single global identifier for legal entities that can be used to facilitate compliance checks across various resources.

With this in mind, banks and financial institutions who may soon need to ensure their legal entity clients possess an LEI to engage in certain payment transactions, cross-border or other, should feel motivated to leverage the benefits of becoming a Validation Agent within the Global LEI System. The advantages are two-fold: enhanced customer service, through a simpler, faster, and more convenient LEI issuance process for customers; and huge efficiencies in client onboarding and lifecycle management for the bank or financial institution. It really is a win-win scenario.

 

The wider impact of LEI adoption in cross-border payments

While the FSB’s report is intended to promote LEI use in cross-border transactions, both the strength and far-reaching scope of its recommendations are likely to be a catalyst for the LEI to be more broadly implemented across many other payment scenarios too. After all, if banks and financial institutions need to equip customers with an LEI to participate in cross-border transactions, then it’s a logical next step for participants in the payments ecosystem to leverage and optimize those LEIs to drive efficiencies across their other payment operations, and to bring enhanced transparency and trust benefits for customers.

There is already a healthy pipeline of active consultations and commitments by financial regulators aimed at recommending or mandating LEI use more broadly within the global payments space.

  • Last year, the European Commission (EC) officially recognized the value of the LEI as a unique mechanism capable of supporting transparency in AML and countering the financing of terrorism (CFT) efforts. It issued two legislative proposals that call for the LEI to be used in certain customer identification and verification scenarios where available.
  • The EC also launched a separate initiative last year to identify obstacles to the creation of efficient pan-European instant payments solutions. As part of its consultation strategy, the EC issued a survey for the purpose of exploring the potential for the LEI to support the screening of instant payment transactions against sanction and watch lists.
  • The Bank of England (BoE) affirmed its position to support wider uptake of the LEI and will introduce the LEI into ISO 20022 standard for CHAPS payment messages on an ‘optional to send’ basis in February 2023. While the BoE encourages all CHAPS Direct Participants to start using LEIs as early as possible, it will not become mandatory until spring 2024, at which time the BoE will begin mandating LEIs to be used in certain circumstances, with a vision to widen out the requirement to all participants over time. In particular, the BoE will mandate the use of the LEI where the payment involves a transfer of funds between financial institutions. The BoE will also monitor the use of the LEI for all transactions, with a view to assessing whether the mandatory requirement to include LEI data should be extended to all CHAPS payments.
  • In order to further the use of LEI in cross-border transactions and facilitate cross-border trade and investment, the Chinese Cross-border Interbank Payment System (CIPS) designed an innovative product “CIPS Connector”, which provides an integrated “one-step” service for a variety of cross-border RMB transactions between banks and enterprises. Every CIPS Connector user is assigned with an LEI, which is used for activating the tool as well as a mandatory business element in their business transaction.
  • In January 2021, and in a move that was the first of its kind, the Reserve Bank of India issued a mandate for the LEI in all payment transactions totaling ₹ 50 crore and more undertaken by entities for Real-Time Gross Settlement (RTGS) and National Electronic Funds Transfer (NEFT).

 

Why the LEI in payments?

The LEI is considered an important tool in payments as it is designed for identifying unique parties to each transaction. It meets a fundamental requirement in payment processing – precise identification of the payer and payee. No other current identifier in payments offers this. International Bank Account Numbers (IBANs) for example are used for uniquely identifying payer/payee accounts, while Business Identifier Codes (BICs) are used for routing the payments to the relevant divisions/sub-divisions of financial institutions.

Today’s highly digitized payment networks require faster, cheaper, and more secure transactions. When the LEI is added as a data attribute in the payment messages, any originator or beneficiary legal entity can be instantly and automatically identified.

 

Become a Validation Agent

When viewed collectively, these developments show that LEI advocacy has never been stronger in the payments space. This signals that the LEI could be the widely implemented trust tool of choice for payments in the near future. With that in mind, GLEIF urges banks, and financial institutions to consider taking a proactive approach to supporting voluntary customer adoption of the LEI and getting ahead of recommendations or mandates in the payments space.

Becoming a Validation Agent in the Global LEI System is now the obvious choice. In addition to easing the process of LEI implementation further down the line by making LEI issuance more convenient and accessible for customers, becoming a Validation Agent can deliver some significant advantages for financial institutions themselves. By utilizing ‘business-as-usual’ onboarding processes to obtain LEIs for clients, financial institutions can improve customer experience, facilitate digital transformation, and reduce client lifecycle management costs.

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