Interview: Alexon Bell, Quantexa, on empowering sustainable decision-making with data intelligence

Alexon Bell, chief product officer at Quantexa, discusses the integration of decision intelligence and data platforms for sustainable banking, government policy alignment with global ESG standards, financial crime prevention, risk management and customer intelligence in the context of evolving ESG preferences.

As green financing and sustainable investing gain traction, how can decision intelligence tools integrate ESG criteria into banking’s lending and investment decisions?

Considering the growing prominence of green financing and sustainable investing, integrating ESG criteria into banking’s lending and investment decisions is crucial. Decision intelligence tools play a pivotal role in this process.

To effectively integrate ESG criteria, banks need to start with comprehensive data. This involves understanding not only the customer but also their entire supply chain. Decision intelligence allows us to resolve counterparty information from transactional data and enrich it with ESG-related insights.

Within the banking sector, especially in larger institutions, there’s an opportunity to track the supply chain extensively. This means applying various ESG matrices and criteria to evaluate potential issues. Banks can focus on environmental impacts, social responsibility and governance practices. This transparency enables banks to make informed decisions about lending or investment based on ESG considerations.

When it comes to investments, it’s about assessing the ethical behaviour of the companies involved. While some data may not be readily available, relying on Know Your Customer data for directors, shareholders and investors can help build a historical picture of their ethical track record.

As governments aim to align policies with global ESG standards, how can data platforms assist in formulating decisions that uphold the UN Global Compact Principles?

Governments are increasingly committed to aligning their policies with global ESG standards, notably the UN Global Compact Principles. Data platforms can be invaluable in aiding governments in making decisions that uphold these principles.

One critical dimension is assessing how a nation like the UK interacts with the global community. This entails evaluating trade agreements, financing deals and investments to ensure alignment with international ESG standards. Data platforms provide a comprehensive view of these interactions.

Additionally, governments must monitor the activities of businesses operating within their jurisdiction. This is particularly important for large enterprises, as their actions significantly impact them. Governments can use data platforms to scrutinise trading partners, detect supply chain disruptions and evaluate companies’ adherence to ESG standards.

Access to extensive and diverse data sources is essential. This includes transactional flows, financial records from institutions like HMRC, customs data and export-import records. Data platforms serve as a unifying force, allowing government agencies to gain a holistic perspective on how businesses align with ESG principles.

By leveraging these platforms, governments can make informed policy decisions and take regulatory actions to ensure compliance with global ESG standards. However, addressing these complex issues requires collaboration, including public-private partnerships and improved information sharing, to effectively uphold the UN Global Compact Principles.

Given the reputational tied to ESG concerns, how can financial institutions utilise decision intelligence to prevent transactions potentially linked to environmental harm or human rights violations?

Mitigating ESG-related risks, especially those linked to environmental harm or human rights violations is a top priority for financial institutions. Decision intelligence can be a potent tool in preventing transactions that might harm an institution’s reputation.

Quantexa has been using decision intelligence in its client base to address these issues, identifying disruptive and illegal activities in flight, such as terrorism and human trafficking. This same approach can be applied to ESG concerns.

Financial institutions have access to substantial datasets, and decision intelligence platforms can analyse these datasets to identify risks associated with environmental and social impacts. For example, detecting signs of environmental harm or human rights violations within a supply chain is now possible.

By identifying such risks, financial institutions can take immediate action to mitigate them. This may include terminating relationships with clients engaged in unethical practices or disclosing such activities to relevant authorities. These actions align with the Social and Governance aspects of ESG considerations.

Furthermore, environmental concerns are closely tied to geopolitical issues. Decision intelligence can help identify and assess these risks, enabling financial institutions to make informed decisions regarding their investments and lending activities.

It’s important to note that addressing these challenges requires a collective effort. Financial institutions should engage in public-private partnerships and share information to combat financial crime and enhance supply chain transparency effectively. This collaborative approach must align with ESG principles and uphold ethical standards.

In sectors exposed to ESG-related risks, like energy or manufacturing, how can analytics platforms aid businesses in pinpointing, evaluating and mitigating these inherent challenges?

Risk management in ESG-exposed sectors, such as energy and manufacturing, necessitates a strategic approach involving analytics platforms. These platforms can help businesses pinpoint, evaluate and mitigate the inherent challenges associated with ESG risks.

Firstly, there’s a pre-phase where analytics platforms come into play. Before venturing into a market or making lending decisions, businesses must analyse the risks associated with ESG factors. In coordination with decision intelligence, analytics platforms can help identify favourable and adverse aspects. This enables organisations to make informed decisions aligned with their risk tolerance.

For example, businesses often face dilemmas such as whether to lend to an oil and gas company. Under ESG considerations, this might initially seem unfavourable. However, if the company is transitioning to renewables, it presents a different opportunity. Analytics platforms can aid in assessing such scenarios and making ethical decisions.

The evaluation phase involves continuous monitoring. This includes observing internal data and external news sources to detect changes that may impact the business. Factors such as changes in company leadership, supplier issues or supply chain pollution can significantly affect the risk profile. Analytics platforms assist in evaluating these developments and their potential consequences.

Organisations must take the corresponding course of action when deviations occur from their ESG goals. This dynamic and ongoing process requires constant monitoring to align with evolving ESG standards and mitigate risks effectively.

As consumer demand sways towards sustainable and ethical choices, how can industries harness data analytics to discern and address the evolving ESG preferences of their clientele?

As consumer demand increasingly leans toward sustainable and ethical choices, industries can leverage data analytics to adapt to the evolving ESG preferences of their clientele.

The key lies in transparency and providing consumers with the information they need to make informed choices. Many aggregators offer ESG tables, but there is often a lack of consensus among them. Therefore, there’s a need for a common framework for assessment. This is where data analytics can play a significant role.

Consumer-driven change begins with understanding the supply chain. Leading companies are already communicating their ethical commitments, but the issue of greenwashing exists. Therefore, consumers need tools and information to hold companies accountable. Data analytics can help verify these claims and detect discrepancies, giving consumers a clearer picture of a company’s ESG performance.

Data analytics can highlight critical aspects such as wage gaps, workforce diversity and supply chain practices. By making this data available to consumers, they can make choices that align with their values. Companies that are genuinely ethical and transparent will likely attract more customers, while those lagging in ESG commitments may face reputational challenges.

Moreover, the democratisation of consumer spending can drive corporate behaviour change. Consumers can make purchasing decisions that align with their ethical values when they have access to transparent data. Companies that fail to meet these expectations risk losing market share, creating a powerful incentive for them to improve their ESG practices.

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