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Fintech: Artificial Intelligence

Fintech: Artificial Intelligence

AI in the context of the financial services sector has the potential to enhance and facilitate complex analytical and decision-making processes; it is for this reason that AI is very much seen as representing a vehicle for the next era of revolutionary change set to transform the financial services sector and society on a global scale.

AI can be relied upon to accomplish time-consuming tasks, improve efficiency of performance and provide previously unattainable insight into patterns, themes and trends that can be extracted from large volumes of data. AI is becoming an invaluable tool that is increasingly adding value to individual endeavours and businesses seeking to derive profit and financial gain from its speed and perception.

AI has already disrupted various markets and is used in subtle ways by millions of people on an everyday basis. At present, there is little legislation governing AI, but this is certainly set to change over the coming months and years as governments and legislators seek to match the pace of development and innovation in AI.

AI: current and future uses

Understanding the use and potential future use of AI is required to understand and prepare for the associated legal and ethical risks. The following list represents a drop in the ocean as to the potential AI has to change and improve everyday tasks and processes:

  • Data mining: the process of using algorithms to identify patterns or infer trends from large volumes of data
  • Internet of things: the integration of AI across all services, platforms, products, environments to create deeper levels of assimilation in turn allowing for greater efficiency and improved quality of life
  • Image processing and tagging: the use of facial recognition or visual scanning to establish identity for security or access purposes, or for the purpose of deriving other types of information, for example health related information
  • Autonomous operation of machinery: the use of automation through AI to improve efficiency by minimising the likelihood of human error and reduce operating costs in industries employing a large volume of people to operate machinery
  • Text and speech analysis: the process of using AI to extract or search for information in text-based data or in a spoken word file in an unparalleled time efficient manner

AI and FinTech

There are also numerous uses for AI in the financial services industry:

  • Security: cyber threats represent an area of increasing vulnerability and concern for the financial sector. More and more transactions occur online or through technology that can be vulnerable to interception and increasingly sophisticated hacking attempts. AI offers a means to enhance security in financial services by learning and responding more accurately and specifically to cyber threats, by analysing large volumes of data and identifying anomalies that might represent an attempt at unauthorised interception, fraudulent behaviour or theft, and by isolating areas of particular susceptibility in the existing security framework through which potential future attacks may be targeted.
  • Automation: although this a function AI performs across every sector and industry it touches, financial services is often an area associated with significant bureaucracy and administrative processes that as such could benefit from automated practices. AI could streamline the way in which financial services companies generate expenditure and expense reports, transform the way in which their services can be accessed and used by their customers and revolutionise the standard business models and operating procedures that have been so heavily relied on for decades. Very much linked to the automation opportunities presented by AI are the opportunities associated with the enhanced utilisation of data. Through AI, the financial services sector will be able to gain a game-changing insight into financial trends, anticipated outcomes and customer preferences, as well as both internal and external business factors influencing revenue and cost margins including productivity levels and areas of strength and weakness within operating practices.
  • Efficiency: inherently linked to increasing automation through AI within financial services are improved levels of efficiency. The use of algorithms, automated processes and technology that can reduce mistakes as well as the time normally taken to complete a task or transaction are examples of the ways in which AI can be fostered to generate new levels of efficiency. On a very practical level, the documentation often involved in both small and more significant financial transactions can be time consuming and subject to human error. AI can be used to authenticate and double check information, as well as ‘learn’ to process information more quickly over time by identifying patterns and recognising what is involved in specific transactions. Businesses will be able to rely on AI to offer faster and more reliant services to customers.

AI has the potential to reshape traditional practices and procedures within the financial services sector, from reducing costs and improving revenue, to tackling complex problems previously reserved for humans. Other applications include automated client interactions, programmed reporting mechanisms, improved risk assessment and tools that allow for smarter and targeted financial services.


Legal Challenges

There are two fundamental legal challenges associated with the development and increasing reliance on AI, namely determining liability in the event that loss or injury arises in association with the use AI and secondly, data protection and privacy issues arising from the collection and application of personal data derived from the use of AI.

  • Liability: AI technology that is capable of learning and effectively behaving in a manner that it is neither predicted nor programmed to do raises questions concerning that attribution of liability in the event that a loss or injury occurs in connection with the use of AI technology. Traditional liability is determined by establishing fault, by looking at the decision-making process or the actions that led to the loss or injury and assessing this against a standard of reasonableness to determine liability or negligence. This traditional and long held understanding of liability endures when ‘decisions’ by AI machines or technology are traceable back to flawed programming or some other similar human related error. The traditional concept of liability falls when AI begins to ‘make decisions’ that are beyond the extent of human programming and instead autonomous. In these circumstances, it becomes harder to trace and attribute liability. A degree of autonomy or independence in an AI programme represents an elementary challenge to the established process of determining liability and in turn reparation for any loss or injury caused. It raises the question as to where liability would rest in the event that autonomous AI technology causes and contributes to loss or harm experienced by an individual or group.      
  • Data protection and privacy: the Cambridge Analytica scandal highlighted how personal information gathered through AI can be used to influence some of the most important decisions made by society. The amount of personal information we share on online platforms today is of immense value and can be bought and sold to third parties with their own separate agendas. AI can also silently harvest personal data, for example through monitoring online interactions and by tracing wireless devices as they connect to different wireless signals throughout a city. Such observations are often performed without the data subject realising or consenting to their data being gathered. The use of personal data to create targeted advertising, drive a political agenda or identify daily routines in certain locations can represent an infringement of a person’s right to privacy. The future success of AI will in part be dependent on the extent to which reassurances can be given that personal information gathered through this technology will not be used improperly or without the consent of the data subject. Users of AI will require guarantees that their personal information will not be bought and sold as a commodity without their prior consent and knowledge. The General Data Protection Regulations should strengthen data protection legislation already in force in the UK and act as a robust standard against which misuse of personal data will simply not be tolerated.

Current Regulatory Proposals

Following a six-month inquiry into the use and future use of AI, the House of Lords Select Committee called for the creation of an AI Council. The Council would represent a mechanism through which AI regulation may develop in the coming months and years and also serve a variety of other public functions, including advising the public on when important decisions are not being taken by a person. 

The House of Lords recently published a report on this matter, entitled ‘AI in the UK: Ready, Willing and Able?’ calling for AI to be developed for the good of humanity, to be used fairly and never to cause harm. If established, the House of Lords has advocated that the AI Council should become the ‘industry body for AI’ and act as a bridge between the private and public sector to coordinate the rollout and smooth integration of this technology into everyday life and society. The Council would also play an important role in educating and supporting the public in their understanding of AI, specifically supporting people to retrain and work in the AI sector to mitigate the potential wide-spread loss of employment that might accompany the expansion of this technology in certain sectors. Work is also being carried out at an EU level; the European Group on Ethics (EGE) has laid out the EU’s ethical principles and democratic prerequisites for examining the role of AI in the future, values including human dignity, rule of law, accountability and sustainability featured on this list. 

At present, the future regulation of AI is unwritten and yet to be determined. Future legislation administering AI may be highly restrictive, governing what type of AI technology can be developed and pre-determining what types must remain in human control. Alternatively, governments and legislators may allow for innovation to flourish before seeking to establish boundaries for this technology. At least for the time being, AI is still being discovered and understood by policymakers. The growing commercialisation of AI will likely increase the momentum moving toward some form of overarching legislation regulating the use and development of AI. Understanding your role as an AI developer or user in shaping the future legislation governing this technology is important. Before the creation of new legislation, government and policy makers frequently embark on a wide-ranging consultation period seeking views and options from experts as well as the general public. Your voice in this debate will be important and could change the future path for AI in the UK and beyond. 

Contact our Fintech Solicitors London, Today

At Selachii, we have a wealth of knowledge and experience in helping those working in the Fintech industry to understand current trends and anticipated developments in the legislative regime governing AI and other technologies. We provide forward-looking legal advice specific to your business needs and will be on hand to provide pragmatic and holistic solutions to the challenges faced by your business. Our team will help ensure your ongoing compliance as legislation governing the use and development of AI progresses.

Contact a fintech lawyer at Selachii today for expert legal advice on AI in the UK and Europe. Call us on the number below or complete our contact form to arrange a consultation.

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