• Emerging market banks are encumbered by outdated systems.
• Modern tools, particularly deploying technology, help overcome these obstacles.
• These solutions can empower back-office teams.

Emerging market institutions have a legacy – one shaped by a commitment to stability and risk aversion, but often at the cost of innovation. Compliance and risk management systems that were put in place decades ago remain untouched, not because they are optimal, but because they were the only options available.

The result is tiresome; systems that work just well enough to prevent regulatory scrutiny and change, but not well enough to seize new opportunities. Transaction risk is generally evaluated reactively, based on limited data and regulatory defensability, leaving institutions vulnerable to inefficiencies and missed growth opportunities.

In trade finance and payments, the market doesn’t wait. Fintechs aren’t tied to the status quo, and they’re increasingly winning business by offering faster, smarter, and more modular, customer-first solutions; they manage to handle large volumes of transactions in the face of growing regulatory pressure, particularly in the light of Russian sanctions circumvention and other rapidly evolving regulatory and geopolitical risks. Banks must now ask themselves – will they watch these agile competitors take their business, or will they take the steps needed to unlock growth and reclaim their seat at the global table?

We’ve entered a new era of data-enabled risk management and decision-making. What once took weeks or months of analysis around payment flows, corridor risks, market share, or trade opportunities, can now be processed in an instant. Technology enables real-time insights into risk modelling, enriched by data that helps banks assess both the corridor and the counterparty.

Banks must no longer be defined by outdated geographic stereotypes. Instead, their competitive edge lies in transparent, data-driven risk insights that showcase their true capabilities.  For too long, risk models have been tied to generalised regional assumptions: ‘Your country is high-risk, so your institution must be high-risk too.’ The red tape is drawn, and the door closes. This outdated thinking benefits no one in the network. Why are we limiting our opportunities this way?

Banks operating in misunderstood regions are often labelled as “high risk” because of their geography, not their actual payment flows. These assumptions block global partnerships, even when the institution’s data shows otherwise.

However, Elucidate’s analysis of cross-border transaction flows reveals these assumptions to be false.  Elucidate’s risk modelling of around 14 million transactions – the combination of FI risk, originator and beneficiary risk, corridor risk, and historical coherence – reveals the transaction flows from a selection of banks in the EU countries and the African Union countries. This modelling demonstrates that there is no discernable risk between the transaction activity of the FIs, regardless of their country or origin.  Both data sets show outliers, and those outliers represent the transactions most likely to result in manual investigations and SARs. However, the volume of outliers represents a similar percentage for both regions.

Source: Elucidate

Evidently, a bank’s country is not the ideal way to assess its compliance or financial crime risk; the data tells a much more accurate and nuanced story.  

Legacy systems: What’s holding emerging market banks back

Traditional financial crime risk management workflows often take weeks to complete, delaying critical payment risk assessment decisions, which then lead to errors and opportunities for financial crime to enter our networks. These outdated methods rely on limited data and manual checks prone to inaccuracies and false positives, wasting compliance teams’ resources, straining customer trust, and closing the door to partnership opportunities from other institutions.

Despite being well-meaning, risk ops and compliance teams end up stuck in reactive roles, trying to maintain stability and avoid regulatory penalties, rather than driving growth. Without an adjustment of these legacy processes and improved data visibility, they cannot challenge this approach, enable safer, more lucrative payments,  or offer actionable growth insights to leadership that will bring more opportunities to their institution.

The consequences then become clear: emerging market banks are held hostage by outdated systems, unable to fully serve their customers or realise their potential. However, the right tools can and do rewrite this narrative for institutions that are willing to make the shift.

How modern tools can change the game

Advanced analytics and AI-powered tools let banks demonstrate their true risk posture with enriched, real-time insights, bringing all transaction data into a centralised place through the use of API integrations. This removes critical data siloes that allow financial crime to slip through the net. Instead of relying on assumptions, payment flows are evaluated transparently against defined models and benchmarks, proving security and compliance. 

A key use case is that a bank operating in a historically “high-risk” corridor can show its transactions are compliant and secure, transforming how global partners perceive the bank, and how they assess the commercial opportunities open to them. These tools allow emerging markets banks to build their own risk data profiles, proactively manage risk, and confidently make payment decisions that strengthen their role as reliable partners, thus moving away from “high-risk” perceptions.

From six weeks to six seconds

While this challenge might seem insurmountable, banks do not necessarily need to overhaul entire systems. The future of risk management technology is modular tools that can integrate into existing workflows and tech stacks, allowing institutions to tailor risk management processes. Teams can design models that reflect their bank’s unique realities, improving both efficiency and decision-making.

Manual reviews and fragmented processes that once took weeks can now be replaced by tools that deliver actionable insights in seconds. AI and machine learning detect anomalies and patterns indicative of financial crime, focusing on bad actors instead of inconveniencing honest ones. Real-time systems assess payment flows, corridor risks, and trade opportunities instantly, giving banks the agility to act when it matters most.

Redefining access as a competitive edge

Modern risk management tools, like Elucidate’s Risk Module Builder and others in the market, don’t just improve payment validation flows, they help institutions carve out and build their own, no-code and robust data workflows – they elevate the role of operations teams. By delivering precise, data-backed insights, these teams become key contributors to strategic growth decisions; they can advocate for their customers to global partners and drive more growth by confidently validating what would before be written off as high-risk transactions. 

Previously dismissed markets and misunderstood payment flows become viable opportunities when analysed through the lens of real-time data.

Elevating operations teams

Modern tools enable operations teams to move beyond back-office roles. With precise, data-backed insights, these teams become strategic drivers of growth and lead to:

• Increased trade volumes, as confidence in payment flows grows;
• Reduced operational risks through real-time, precision-driven assessments; and
• Enhanced global partnerships, with banks proving themselves as reliable actors in global trade.

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By adopting real-time, data-powered risk management tools, banks can transform from being labelled as ‘high risk’ to becoming trusted leaders in global trade. The tools to redefine risk and unlock growth already exist, but they require action.

Clinging to legacy systems and processes may feel safe, but in a market driven by innovation, speed, and precision, inertia is the biggest competitive risk. By investing in fully leveraging their data to build a unified risk data story  (rather than reacting to the limited information provided by siloed, and disparate data sources), banks can position themselves as reliable, proactive partners in global trade.

You are not your country – you are your data. For banks ready to embrace this shift and see themselves as data-armed institutions, the opportunities are endless. 

The post Your bank risk is not your country risk – it’s your data: How emerging market banks can turn access into their competitive edge appeared first on Trade Finance Global.

Modern finance is global.

It’s easier than ever to buy anything from anywhere in the world because there are systems in place that allow money to travel effortlessly across borders.

While endlessly beneficial for businesses and consumers, this interconnectedness also helps illegitimate actors. Financial crime and sanctions circumvention have become more sophisticated, with criminals exploiting global networks to launder money, fund terrorism, and engage in other illicit activities. 

As a result, regulatory bodies worldwide have intensified their efforts to combat these threats, leading to frequent updates and new regulations.

It’s up to the financial institutions on the frontlines to adapt quickly to these changing conditions so they can be well-armed in the fight against financial crime.

Traditional compliance methods—often manual and time-consuming—are no longer sufficient given the volume and complexity of modern-day transactions.

Bank technology is designed to be stable and reliable, not agile

Banks are often heavily criticised for operating on archaic technology systems but these criticisms overlook the fact that banking systems were designed for stability, security, and reliability, not agility. 

They were not built to adapt quickly to fast-changing regulatory demands and shouldn’t try to. The foundational strength of these systems is ensuring secure and reliable operations. Any system upgrade that could cause service disruptions is too risky for many financial institutions to consider.   

But that doesn’t change the pace at which financial crime and regulatory changes occur.

Thankfully, financial institutions don’t need to overhaul their entire core systems to remain compliant. 

The future is modular.

The building blocks of compliant trade finance

A modular approach to financial crime risk assessment involves breaking down the overall risk assessment process into smaller, independent components or modules, with each module targeting a specific area, like customer due diligence, transaction monitoring, or sanctions screening.  

Similar to Lego blocks, these modules can be stacked, connected, and combined into any structure that fits a financial institution’s specific needs. 

For example, an institution may focus on customer-level risk assessments in one region while prioritising transaction-level monitoring in another. 

A system can be configured to align with an institution’s internal policies and regulatory expectations, enhancing compliance and supporting business objectives by allowing institutions to manage risks without stifling legitimate transactions and trade.

This flexibility ensures that resources are allocated efficiently, addressing the most pressing compliance challenges at any given time while ensuring that financial institutions can demonstrate regulated and defensible compliance. 

Harnessing AI to combat sanction circumvention

In the contemporary landscape of financial crime prevention, the integration of Generative AI (Gen AI) into compliance strategies marks a shift in how financial institutions address a range of challenges, including the ever-increasing challenge of sanction circumvention. 

Reflecting on the evolution of sanctions, particularly those targeting Russia, the industry observed a sophisticated maturation from the initial 2014 measures to the comprehensive iterations following February 2022. 

During these stages, technologies were developing, primarily focused on identifying and mitigating risks in static scenarios. However, the scenario has drastically changed with the advent of Gen AI. This technology has not only refined but also advanced the approach towards identifying risks related to sanction circumvention—shifting from reactive to proactive risk management.

Today, financial institutions employ Gen AI to perform intricate analyses of transactional data, enabling them to unearth hidden patterns and relationships indicative of potential compliance breaches. This can happen within existing technology, or as a purpose-built data workflow alongside existing technology. 

For instance, when a transaction is flagged, the subsequent review process is no longer as laborious as before. Previously, analysts might spend hours, if not days, manually searching through data and requesting additional documentation to confirm a transaction’s legitimacy.

Gen AI accelerates this process by automating the creation of detailed profiles for transaction originators and beneficiaries. This is via advanced API and using AI algorithms that integrate diverse data sources, such as Google Maps, to provide a holistic view of a transaction’s context. By doing so, it mitigates the time-intensive aspects of compliance, allowing analysts to focus on higher-level decision-making and strategy formulation.

The practical application of Gen AI in financial settings is illustrated by its capacity to streamline and enhance the accuracy of sanction screening processes. For example, when a payment is halted due to a potential sanction risk, Gen AI can quickly analyse the associated parties and the nature of their past transactions. 

This enables institutions to rapidly ascertain the risk level of proceeding with the transaction, significantly reducing the time spent on each case and minimising the likelihood of inadvertent non-compliance.

Moreover, the integration of Gen AI into compliance frameworks supports financial institutions in maintaining agility amidst tightening margins. By automating routine compliance checks and risk assessments, banks can preserve their operational efficiency while adhering to regulatory requirements—thus safeguarding their reputation and financial standing in the global market.

Case study: Uncovering sanctions circumvention

Many nations, including the USA, have imposed sanctions on Russia following its 2022 invasion of Ukraine. Despite the sanctions, Russia has still been able to acquire many sanctioned goods by leveraging legacy trade networks with its neighbours.

Financial institutions in these regions that help with sanction circumvention—intentionally or inadvertently—risk severe consequences, such as losing access to Western financial systems, facing substantial fines, and damaging international relationships.

To help prevent this, a regional bank in the area sought to proactively identify payment originators and beneficiaries in the markets most associated with Russian sanctions circumvention. 

Using the Entity Resolution, Activity Check, and Investigative Analysis analytical modules from Elucidate, the bank was able to identify the payments, originators, and beneficiaries with the most concentrated risk. 

By isolating the risk, the bank could focus on preventing the highest-risk payments and use existing tools to screen for those names without impacting the experience for its legitimate customer base. With this approach, within the first 60 days, it achieved a 30% reduction in sanction circumvention risk while ensuring that its procedures adhered to independent regulatory standards.

The rapidly evolving regulatory landscape demands innovative solutions for financial crime risk assessment. A modular approach offers a comprehensive answer, providing flexibility, customisation, and regulated defensible compliance. 

As globalisation and financial crime threats continue to grow, financial institutions must leverage advanced technology to stay ahead. By adopting modular systems, they can efficiently manage risks, meet regulatory requirements, and support global economic stability by constructing financial compliance that meets their unique needs. 

This approach ensures compliance and enhances operational efficiency, positioning institutions to thrive in an increasingly complex and global world.

The post Combating financial crime: The benefits of a modular approach appeared first on Trade Finance Global.

Financial institutions and payment companies are not new to the adverse impacts of geopolitical risk. Sanctions and the tools used to enforce them, for example, are but one of the well-established tools used in financial services relating to such risks. 

However, the evolution of sanctions and the increasingly complicated manifestation of those sanctions highlight that geopolitical risks are often hidden within our economies. The rules-based approach and manual investigation-based systems that worked in the past are no longer sufficient for identifying and preventing the manifestation of such risks.

In the ever-evolving global political and economic landscape, the intersection of data science and geopolitical risk management has become critical for cross-border payments. 

The nuanced and indirect nature of geopolitical and sanctions risk – sanctions circumvention is widely viewed as a critical risk at the moment by both regulators and financial institutions – together with customer and regulatory expectations for ever-faster payment execution, creates the potential for a new level of risk. As has been the case for the past 30 years or more, financial institutions will be expected to independently mitigate that risk or be responsible for the consequences.

So geopolitical risk and financial crime risk, including both money laundering and sanctions, are intertwined. This much has been clear to the market for as long as country risk has been assessed. What has changed is the complexity and opacity of payments, combined with a level of velocity which amplifies risk. 

For that reason, the tools which evolved historically to mitigate these risks are no longer fit for purpose. Real-time payment analysis will increasingly become key to identifying and managing geopolitical, financial crime, reputational and regulatory risk. 

A case study on payment risks

As with so many areas of risk today, data science is a critical component to solving this problem in an effective and sustainable way. Recent research conducted by the team at Elucidate highlights the potential application of data science in navigating the complexities of cross-border financial flows, particularly in the context of sanctions.

Elucidate presented our findings at the 2024 Empirical Anti-Money Laundering Conference organised by the Central Bank of the Bahamas, examining the web of cross-border transactions involving jurisdictions of the Commonwealth of Independent States (CIS). 

The paper suggests that “from a risk management perspective the FATF and EU lists are of limited practical value in identifying jurisdictional-level sources of risk. A more empirically-driven approach to cross-border ML/TF risk at the jurisdictional level would contribute to more appropriately targeted focus of limited regulatory and compliance resources, improving overall systemic effectiveness”. 

By harnessing a cross-institutional dataset of transactions between 2018 and 2023, we applied a structured risk model analytical framework that integrates trade flows, GDP, geopositioning analysis, graphic distance and indicators of money laundering risk.

This revealed transactions representing a high probability of association with sanctions circumvention, none of which would have been highlighted by conventional sanctions detection software.

Our findings reveal that despite various CIS jurisdictions’ efforts to enforce compliance with international sanctions, certain cross-border flows the widely reported risk of sanctions circumvention is real and is manifesting in market activities. 

Furthermore, the data relating to these payments are not necessarily correlated to standard high-risk country metrics, such as those published by the Basis Institute and others. This further underscores the limitations of current AML frameworks and the necessity for a more nuanced, data-driven approach.

These findings, which also examined the use of traditional financial crime typologies as a means to backtest and determine exposure to evolving geopolitical and sanctions risks, revealed decidedly mixed results. 

Whilst there were occasions where typologies familiar to transaction monitoring teams – round dollar amounts, offshore customers, etc. – were associated with sanctions circumvention, it was rare that any single typology was uniquely present. More often a combination of typologies existed. 

Complex risks require an updated tech stack

Such complexities would render transaction monitoring tools quite ineffective at highlighting the most acute risks. This highlights the critical need for a detailed analysis of transaction patterns that may or may not appear to diverge from the norm. This also requires a data science-driven approach to uncovering potential financial crimes, as the volume of data and complexity is inaccessible to even the most seasoned investigator.

We urge companies and regulatory bodies alike to recognise the criticality of data-driven insights as a core element in financial security and compliance. This is not the automation of risk management, but rather the augmentation of existing control frameworks with data science to ensure they remain fit for purpose.

By embracing the methodologies exemplified in our research, stakeholders can develop more effective risk management frameworks, tailored to the unique and evolving geopolitical risks and challenges in which they operate.

More work is needed to integrate these new approaches into the payments landscape, but it is essential to ensuring both regulatory compliance and the overall integrity of payments platforms. Real-time solutions and solid risk modelling are essential parts of a robust payments tech stack. 

Shifting the control framework left, with all the benefits that data science, machine learning and generative AI offer, will ensure that we create machine speed compliance capable of matching the increasing velocity of the payments ecosystem.

Not all financial institutions will be able to do this alone, but fortunately, there are tech partners like Elucidate that enable change and evolution to keep pace with even the most fast-changing environments.

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For ages, correspondent banking has played a vital role in the global payments system. Through correspondent banking relationships, banks gain access to a diverse range of financial products across various jurisdictions enabling them to offer cross-border payment solutions and services to their customers. 

Nonetheless, in recent years major banks around the world have been terminating their long-standing correspondent banking relationships. This phenomenon, commonly known as ‘de-risking’, is fundamentally reshaping the global financial services market. 

While predominantly pursued with the intention of mitigating risk exposure for financial institutions amidst growing regulatory pressures, the consequences of de-risking extend beyond the banking sector. Many countries are threatened by the loss of their connectivity to the global financial system. For smaller developing countries, de-risking is not just a banking concern, but a considerable trade issue endangering their basic human needs.

To delve deeper into the key drivers of de-risking and its real impact on global trade and developing markets, Trade Finance Global’s (TFG) Deepesh Patel spoke with Shane Riedel, Founder and CEO at Elucidate.

Unveiling the catalysts behind de-risking

The ongoing Ukraine-Russia conflict has magnified the global regulatory focus on the financial services sector, particularly in areas of financial crimes, anti-money laundering (AML), and counter-terrorist financing (CTF) regulations. In response, financial institutions have notably cut back their risk appetite.

Although the declining risk appetite and the intensifying AML/CTF scrutiny are often perceived as the main motives behind de-risking, the underlying factors are much more complex. From Riedel’s perspective, de-risking reflects a reaction to the multifaceted commercial realities in today’s financial markets. 

As Riedel pointed out, “De-risking is just a response to the commercial realities of the market. The instances of genuine de-risking due to financial crime or compliance reasons, represent an astonishingly small percentage of the overall exits observed in the market.”

In addition, Riedel clarified that the primary reason behind de-risking lies in commercial decisions that are centred around the costs of regulatory compliance, saying, “In most instances, the reason that banks are consolidating their portfolios is a commercial decision, based on the cost of regulatory compliance.”

Whilst acknowledging the significance of enhancing compliance frameworks, Riedel cautioned against focusing solely on implementing additional compliance measures. Rather, he suggested exploring the systemic factors that hinder banks from effectively evaluating the commercial aspects of their correspondent banking relationships. 

Aiming for more cost-effective partnerships or inclusive distribution of risks and costs across the market, he explained, “We need to look at the systemic reasons why banks can’t make the commercial elements work and how to change that.” 

The economic impact of de-risking

De-risking disproportionately impacts developing economies. Particularly vulnerable are the communities that rely on these services to access financial resources and dollar liquidity from the developing world to sustain their populations. 

As dollar liquidity declines, the challenge obviously demonstrates the real intersection of financial market dynamics and basic societal needs. Underscoring the fragility of such economies and the struggles faced by these nations and their SMEs, Riedel added, “In these markets, fewer opportunities are being created for SMEs who could otherwise have been more involved if the trade finance gap was better bridged or if more opportunities for international trade was available to them.”

Another often overlooked impact of de-risking is its potential to trigger underground transactions. The closure of bank accounts may force organisations and individuals to resort to cash transactions, effectively creating an environment that precludes the goals of AML/CTF regulations. 

Riedel notes, “What we are seeing is the evolution of shadow banking, entities that are less regulated and less transparent. The impact of de-risking has generally been to not only remove or reduce opportunity but also to reduce transparency in the market.” The rise of shadow banking and the inadvertent promotion of untraceable transactions represents a stark paradox in the global efforts to maintain a secure financial ecosystem.

Balancing risk and accessibility

While digitisation has led to significant progress in correspondent banking, particularly in the payments and trade sectors, operational, compliance, and risk management processes remain stagnant.

Riedel highlighted that while the payments and trade sectors have successfully integrated digitisation, risk management still relies heavily on manual processes, such as manual Know Your Customer (KYC) checks, qualitative assessments, and governance procedures. 

He explained, “The moment you get to the operations, compliance and risk side of the house, the processes are the same today as they were 10-15 years ago.” This disparity calls for the adoption of digitisation and automation into the compliance domain, reducing manual processes and achieving a balance between risk assessment and operational efficiency. 

Riedel asserted, “The only way to address this is by bringing digitisation and automation to the commercial side.”

Furthermore, partnerships have the potential to achieve a balance between risk and accessibility. Riedel illustrated this potential with a real-world example of the collaboration between Elucidate and Dow Jones. 

This partnership allows financial institutions to access quantified and objective risk scoring, supporting their compliance strategies. Riedel said, “We can take some of the most cumbersome, qualitative processes and start to put values against them.” 

Similarly, various financial instruments such as Letters of Credit (LCs), can benefit from such a data-driven approach. Riedel pointed out how this approach can transform the traditional LC processes, stating, “We enable banks to pre-qualify those letters of credit by determining the riskiness of the originating bank.” 

This risk-based approach helps banks to accelerate their decision-making process and enhances operational efficiency without compromising due diligence.

The future of correspondent banking

With disruptive market entrants such as digital currencies and the introduction of multi-currency payment platforms fueling competition and sparking innovative solutions, the correspondent banking sector is likely gearing up for a transformational change. 

Moreover, the correspondent banking industry is continuously adopting strategic aggregation models and nesting multiple layers of aggregation to enhance operational efficiency, albeit with added complexity. 

As the market navigates complex layers of payment clearing, and where multiple banks are engaged in a single transaction, the role of data and standardisation cannot be overstated. As Riedel stressed, “The role of data and standardisation becomes even more important to avoid the chaos of numerous rejected payments and ultimately more de-risking.” 

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