Finance lenders anticipate considerable gains in terms of efficiency with the rise of AI technology.

In 2017, Deutsche Bank’s CEO stated that robots would replace nearly half of his workforce in the coming years. At a similar time, the former Citigroup CEO predicted that approximately 30% of global finance jobs could disappear due to AI and robotics within five years. 

While these claims may not have become completely true, industry experts believe AI represents one of the biggest opportunities for the finance industry, to drive efficiency enhance automation, and deliver a considerably better customer experience. According to Bernd Leukert, the chief technology, data and innovation officer at Deutsche Bank, AI tech now lies at the core of their strategy. 

AI is well placed to tackle the challenges of legacy technology that many banks face and utilise the value of the data available. Other financial leaders highlight that while some feel the regulated conditions of financial services will hinder the uptake of AI, others believe it can help meet regulatory requirements, particularly those linked to financial crime. 

Mike Abbot, senior head of Accenture global banking practice, who has discussed with many lenders about their AI strategies, explains that banks are beginning their journeys, but the capacity of tech is growing at an accelerated pace every year. This means there are significant potential gains for those who decide to commit first. Abbot says that risk, compliance and enterprise are where the most impact is. Businesses are using AI today as a customer acquisition tool since banks can provide services in a more personalised way, customising solutions based on profiles built via AI.

Other businesses have emphasised how AI can assess multiple changes to laws and regulations, exploring enforcement and determining what is appropriate for an organisation. Consultancy group Capco has created a tool that identifies about 75% of the records a human would and is in the early stages of deploying the system or using regulatory change processes.

In other cases, Deutsche software engineers are applying AI to produce code more efficiently, increasing productivity for the overall business. The German finance lender is also testing AI to manage IT and HR queries, hoping to apply the technology to some client interactions. 

In investment banking, Deutsche is using AI to manage credit risk models and incorporate a broader range of non-financial-related factors, especially climate-focused measures. John Hinshaw, the COO at HSBC, explains that the bank is applying AI as an anti-money laundering solution in partnership with Google, which is now available to the financial market. 

HSBC and other financial leaders are optimistic about applying AI and the potential for greater gains with a new workforce prepared to embrace the opportunities available with AI. Finance leaders highlight that embracing AI shouldn’t be viewed as eliminating jobs but doing more with the same number of people and creating a more fun environment to work in.

ESG has become a top priority for many companies, but with mounting concerns surrounding greenwashing, how businesses accurately measure their global impact is critical. ESG data represents a valuable resource and could help increase access to funding, especially for smaller organisations.

In recent years, the requirement for higher levels of transparency on ESG impact from businesses has increased. With progression worldwide, like the 2020 EU Taxonomy and Corporate Sustainability Reporting Directive (CSRD) regulation, these concerns have become top priorities for investors and financial businesses. ESG data has evolved into a vital way for companies to quantify their global impact. Regulation surrounding the development of ESG data, including the EU taxonomy, has supported companies, but there is an evident disparity between the businesses capable of producing accurate ESG data when required.

While SMEs make up approximately 90% of businesses worldwide, with minimal to no regulatory pressure to deliver ESG data, a considerable data gap is evident between smaller and larger companies. While there are ways for SMEs to determine their data indicators, the range of methodologies and the lack of primary data can generate skewed results or potentially highly inaccurate results. These anomalies create various challenges when it comes to finding finance. As ESG concerns have increased, investors are gaining further interest in the climate and social impacts of their plans, and many have started using ESG impact as a technique to determine how a business is managing its risk. 

The investor demand for sustainable options is growing significantly. Sustainable bonds, whether it be green bonds or other transition bonds, have sparked investment in environmentally or socially beneficial projects or businesses. Data is vital to determining if a project is applicable for this type of investment and assessing whether a project has met the standards after issuance. So, SMEs that lack accurate data, will find it challenging to access these credit options available within the sustainability field. 

Accessing high-quality and accurate ESG data will improve SMEs’ financing opportunities. Staying in touch with ESG will help businesses keep a competitive edge in the future.

Although SMEs remain exempt from the EU’s Taxonomy Regulation, this will likely change as governing bodies continue pushing for more sustainable business practices. The environmental and social amendments to the Companies Act in the UK are another sign that we can expect further changes to economies worldwide. SMEs that can have their ESG impact to hand will have the competitive edge, pre-empting regulations that may impact their operation and ensure speedy compliance.

What can companies do more/better?

So, what is the key to improving ESG data availability for SMEs? One way is through harnessing a range of alternative sources of data. By using corporate ESG data collected through annual reports, media, and legal records, SMEs have the potential to build a rounded and accurate ESG profile.

The problem is that this data is often disparate and challenging to collect and analyse efficiently. This is where technology comes in, allowing SMEs and financial institutions to automate how ESG data can be assessed using less obvious sources, such as the media and court cases, to build an ESG profile for companies, no matter the size, type of operations and quantity of official ESG data published. 

As ESG concerns continue to grow in importance across the global economy, SMES must stay one step ahead. Harnessing the power of technology can level the playing field for SMEs, providing access to finance for underserved businesses and ensuring compliance in an increasingly complicated world of regulation.