To what extent are you aware of artificial intelligence already being used in the financial sector in your jurisdiction, and do you think regulation will impede or encourage its further use?
Artificial intelligence (AI) is certainly an area of growth in the financial sector in Bermuda. We are seeing start-ups developing AI for things like robo-advisory services in the investment and funds sector as well as cyber-underwriting in the insurance sector.
The regulatory regime and tech-friendly environment in Bermuda encourages AI’s further use and development within the jurisdiction.
The use of AI by Cayman Islands investment funds is becoming more common for example trading techniques in the context of complex quant trading.
We are starting to see the use of artificial intelligence in multiple areas of the financial sector, for example in AI trading techniques in the context of complex quant trading, in fraud detection and risk assessments by credit institutions.
Major banks such as Danske Bank have already launched products which are fully or partly based on artificial intelligence and machine learning technology. A notably example is the automated home and mortgage searching app, Sunday. Furthermore, numerous Danish fintechs are making use of AI.
The current Danish government recognise the potential and value in artificial intelligence ("AI") and encourage businesses' use of AI. Thus, we see no im-plications that national regulators would adopt regulation which would im-pede the use of AI. On the contrary, in our view the direct opposite is more likely.
On EU level, it is worth mentioning that the EU Commission in April 2018 pro-posed a number of initiatives in order to strengthen investments in, and the use of, AI in both the public and the private sector.
Artificial intelligence ("AI") is being used in the financial sector mostly for the purposes of customer services. There are also other types of services based on AI and machine learning, such as in investment counselling. These are the ones most visible to the general public, and back end solutions based on AI are being tested, developed and used.
Finnish law does not impede, nor encourage, further use of AI as such. However, as artificial intelligence requires huge amounts of data, and especially in the financial sector the data may be linked to a certain individual, data protection requirements need to be taken into account.
The most significant legal issue relate to where the data can be generated from, and how to ensure that the data is processed in accordance with data protection laws. Data protection legislation does not impede the use of AI, but sets boundaries to the collection and use of the big data that AI utilises.
Artificial intelligence is more and more used in the Fintech in France. Different services provided by Fintech are concerned by this trend. For instance, the French AI Fintech “DreamQuark” is known for its innovation in the field of AI and particularly deep learning (Deep Learning) applied to financial services. DreamQuark is a platform which allows financial institutions to create all kinds of applications, based on AI, such as customer segmentation, product targeting, underwriting, credit granting, asset management, compliance, anti-money laundering, fraud, collection, satisfaction and customer retention.
As proof of the importance given to this issue by French regulator, the Governor of the Bank of France, François Villeroy de Galhau, announced the creation of a working group with the AMF assessing the effects of the AI on the financial professions. The institution will also publish a study on digital transformation in banking and insurance. We can also mention several Banks and insurance regulators and observers such as the Financial Stability Board or the Bank's Business Observatory, which analyse the potential consequences of AI on their sector.
A recent report on the artificial intelligence of the mathematician and MP Cédric Villani was made public Wednesday, March 28, 2018. As a result, it recommends to free oneself from a legal and fiscal framework too restrictive, which discourages the research, thus braking the competitiveness of France. This report is in accordance with a previous report made by “France Intelligence Artificially” and the French Government who also ordered to build a favourable legal framework.
More and more companies are aware of the advantageous use of artificial intelli-gence and are already partially using the technology like Chatbots for first level customer services or for fraud detection in case of falsified damage declarations to insurers. Another use of AI is robo-advisory. A robo-advice is usually catego-rized as investment advice subject to an authorization requirement in Germany if the customers, on the basis of the details they provide, receive investment sug-gestions relating to specific financial instruments. If the customer, based on the data they provided, receives a suggestion on the structuring of their portfolio which lists different asset classes or industries, given in percentages, without naming any specific financial instruments, the robo-advisor is generally not providing investment advice subject to an authorisation requirement in Germany. However, whether or not an authorisation requirement applies depends very much on the individual case.
At this time there is no indication for any kind of regulatory impediment to the further use of AI. Furthermore, it is noteworthy that the BaFin has started a study on the use of Big Data and artificial intelligence, the facts and findings of which you can find here:
Providing a legal framework capable of welcoming and encouraging the growth of new technology has been a key focus in the development of the DLT Regulations, which is the reason why Gibraltar does not regulate the technology but instead focuses on regulating those entities who use the technology as part of their business. This flexible yet robust regulatory framework allows the fintech industry in Gibraltar to mature and advance within a regulated environment without the need to constantly update the regulations. Therefore, the development and adoption of AI is highly encouraged by the jurisdiction and its regulators.
Like global financial institutions have prioritised investment in AI to enhance their services, revenues, and performance, Maltese financial institutions have also invested in this innovation. One major use of AI locally is in the banking sector where technology is used to detect fraudulent transactions and clamp down on money laundering. In trading, firms have invested in automatic robo-traders which build risk profiles of investors on the basis of information supplied by such investors, thereby allowing firms to tailor the financial products sold to investors.
The Maltese Government, has in a recent consultation paper, highlighted the prospect of regulating AI solutions under the Innovative Technology Arrangements and Services Act (Chapter 592). The upcoming framework targeting AI will likely replicate the efforts in the DLT sphere, wherein platforms and service providers can opt for voluntary certification and supervision under Maltese law. Besides establishing an effective tailored form of financial regulation, whereby market participants themselves would be able to choose a regime according to their business profile, the consultation paper further mentions the possibility of granting legal personality to AI.
Today, the use of artificial intelligence is prominent in the fintech sector, with over 15% of Israeli fintech companies using artificial intelligence, which percentage we expect to grow. As can be seen in other answers, the legislation environment in Israel is encouraging for the fintech sector and new technology and we therefore we do not believe regulation will be impeding the use of artificial intelligence but rather encourage its use within the permitted framework.
While the use of artificial intelligence in the financial sector still appears to be limited, we can find several players in this sector attempting to utilize it in their business. For example, certain asset managers recently launched mutual funds that use artificial intelligence to make automated investment decisions. Certain banks announced that they'd launch new loan programs utilizing artificial intelligence as an automated loan screening tool in the near future. Certain insurance companies are also attempting to utilize artificial intelligence to handle insurance claims and examine payments of such claims.
In general, the national government of Japan shows a proactive attitude towards the use of artificial intelligence. In the financial sector, the Financial Services Agency supported the testing of a project whereby an IT vendor and financial institutions attempted to have artificial intelligence undertake primary screening of customers' voices and extract potential compliance breaches and customers' complaints based on them. It recently announced the successful completion of the project with the statement that the use of artificial intelligence would be feasible for this kind of screening process.
Mexican financial institutions are not only at the forefront of the implementation of artificial intelligence, but a significant percentage of them are already in a process of digital transformation in order to streamline their processes.
According to GFT Banking Expert Survey 2017, 30% of the Mexican banks have a defined digital transformation strategy, while 50% have a digital transformation strategy being developed. Regarding AI, 23% of the Mexican banks consider this type of technologic as a strategic tool, 40% consider it as an important but only tactical change.
There is no AI regulation per se, however due to the technologic progress, regulation should foster its further use in the near future.
British Virgin Islands
As in most industries, the current scope of artificial intelligence being used in the BVI financial sector is what would be classified as “assisted intelligence” or “narrow AI”. However, there are certainly initiatives underway involving machine learning and other related technologies which expand that scope, and regulation is increasingly supportive of those efforts. A recent amendment to the BVI’s AML Code of Practice, aligning it with the latest developments in digital identity verification, is an excellent example of the direction being taken by the jurisdiction.
SSEK: Several fintech providers utilize artificial intelligence to process submitted data in order to cut costs and increase efficiency and accuracy (e.g., selecting potential borrowers for peer-to-peer lending providers, using chatbots to address frequently asked questions of customers, transaction screening to detect fraudulent transactions, recognition of behavior patterns to generate appropriate recommendations, etc.).
The current regulations do not address artificial intelligence or the use thereof. However, given that some government institutions, including the Ministry of Communication and Informatics, utilize artificial intelligence it is likely that future regulations will encourage the further use of AI.
AI is a central technology for all sectors and industries, and as a result its testing and use is growing worldwide, including in Portugal. Indeed, AI (together with Big Data) is already being used in Portugal by banks and fintech companies, e.g., in customer service, in the analysis and granting of credit and even in regulatory compliance. AI brings several legal and regulatory challenges, from warranty, liability, transparency, among others. Regulation of AI is being thoroughly discussed at the international level, including in the EU, and such discussions also cover the strategic approach to adopt in this field. It is important to make sure that AI regulation does not impede or hinder the development and use of AI, and an approach of regulating without a full understanding of the evolution of this technology shall be avoided. However, some principles or recommendations shall naturally be approved to create legal certainty, which is also a factor that encourages the development of new technologies. Because of the global nature of this technology, any such guidelines should however be as aligned or coherent as possible to avoid market distortions.
Artificial intelligence is in active use as part of so called "robo-advisories" that harness artificial intelligence to provide wealth management advice and structure investment portfolios. These AIs have attracted some regulatory scrutiny, with the Massachusetts Securities Division ruling that a registered investment company cannot fulfil its fiduciary duties in reliance on AI robo-advisors alone; rather, some human intervention is required.
The US has been slow to regulate in the fintech area, and we do not see specific regulation of AI as a priority issue. While the lack of regulation won't act to impede its use in financial services, other jurisdictions may foster use of AI through regulation.
The use of artificial intelligence in the financial sector is well-established. We do not believe UAE legislation impedes the use of artificial intelligence in the UAE. However, such use would need to satisfy UAE security requirements which are in line with international standards.
Banks use artificial intelligence for a variety of reasons, including the automation of processes, interaction with customers, and building intelligent and real-time lending models. For instance, Emirates NBD has launched the chatbot Eva, which helps customers cut through time consuming layers and access the information they want immediately.
The DIFC has, through its innovation testing program, approved the first robo-wealth advisor in the Middle East, Sarwa. The Dubai Electricity and Water Authority has also launched its robot, Rammas, which listens to customers’ concerns and knows their entire history with Dewa.
At the present time there is no widespread use of artificial intelligence technology in the financial sector of Ukraine. In case of extension of this technology we may be confident that the use of such technology will be supported by the National Bank of Ukraine.
Artificial intelligence (AI) is already used in robo advisory as well as in various compliance projects (e.g. AML, on-boarding of clients) and in document reviews. Regulation will not impede its use; rather, the approach to make regulation technology neutral will encourage its use.
The deployment of AI technologies is currently at a nascent stage in the Indian banking sector, its competitive advantage over conventional means has been recognised, in the form of setting up of innovation centers and organising hackathons vis-à-vis partnerships between banks and Fintech companies. State Bank of India, the largest bank in India conducted “Code for Bank” hackathon to build solutions leveraging futuristic technologies such as AI into the banking sector. Even the Finance minister of India, in his budget speech for 2018 – 2019, mandated India’s national policy think tank, the NITI Aayog to establish the National Program on AI. In pursuance of this, the NITI Aayog has partnered with several leading AI technology players to implement AI exploratory proof-of-concept projects in numerous areas. It is also formulation a national strategy for building a vibrant AI ecosystem in India in collaboration and consultation with various experts and stakeholders. NITI Aayog unveiled its discussion paper on national strategy on AI focuses on how India can leverage the transformative technologies to ensure social and inclusive growth.
There are a number of fintech suppliers who are using artificial intelligence actively in enhancing existing financial processes. One such is Eigen Technologies, which is using natural language processing to pull specific data fields out of large amounts of legacy documents in order to help financial institutions to get digital control of the data that they hold in other formats, in a fraction of the time that it would take humans to carry out the same task. There are other examples of regtechs that are using machine learning to extract and package up regulatory information, such as Cube Global and RequirementOne.
Other companies are using AI to spot behavioural patterns and anomalies in those patterns – one of AI’s strong suits. These include:
- payments authentication solution Cybertonica;
- email security firm Tessian; and
- Nasaq Buy-Side Compliance (formerly Sybenetix), which is used by asset managers and hedge funds to spot anomalies and suspicious activity in traders’ trading patterns.
Others use machine-learning to spot patterns in order to make predictions. These include:
- cashflow prediction engines Fluidly and Fractal Labs; and
- insurance pricing and risk engine Cytora.
There is limited regulation in this area at the moment, the main regulation being those parts of GDPR that touch upon the sorts of data processing that are often involved in machine-learning. These will include, in particular, obligations in relation to profiling and automated decision making (see the answer to question 5 above). A House of Lords Select Committee has been established for the purpose of considering the economic, ethical and social implications of advances in AI, and this has focused to some extent on the concepts of ethical uses of broad data sets, accountability, and the mandated sharing of data (similar to open banking) in order to prevent “data monopolies”. It remains to be seen to what extent this thinking will translate into legislation. However, our view is that if any future regulation is technically realistic and flexible, whilst encouraging transparency and accountability, it will be of benefit to consumer trust in its use in the long term, which will in turn lead to widespread adoption.
Dutch banks are experimenting with AI technology, ranging from tools that may assist bank employees, to technology that directly interacts with customers. One Dutch bank for example is experimenting with chat robots understanding what clients want and what problems clients encounter. Through chat robots, the customer service will be contactable 24/7. It is predicted that 30% of the employment in the banking sector will be performed by robots, the chat robots will contribute to this development. The robots should be taught to make complex connections. For example, when a client asks if he has enough money on his bank account to go out for dinner that evening, the chat robot should be able to predict future costs that will be collected from his bank account, such as rent, mortgage and other fixed charges.
The AFM has declared it aims to facilitate the development of AI technology while mitigating the related risks (e.g. privacy infringements and cyber crime) at the same time. The main concern is that institutions will abuse the data they collect about how consumers make decisions. The decision making process of consumers is not always based on rational grounds; this fact could be misused and exploited via marketing techniques. A risk is called “evil nudging”: drawing consumers in a certain direction and make them buy goods they do not really need or want, while they are not aware they’re being tempted to behave like that.
For now, the AFM only investigates the existence of these risks. If the supervisor detects a breach in how companies use data for unwanted marketing techniques, the AFM will take action within the scope of the current legislation. As far as we know, new legislation is not yet in the making.
The artificial intelligence (AI) is observed to be constantly used in the following financial sectors:
(a) Banking services - e.g. many banks use AI technologies to develop chatbots to provide traditional customer services;
(b) Personal wealth management - e.g. AI technologies are used in making portfolio investment suggestions or decisions for the customers based on their respective risk preference;
(c) Insurance services - e.g. insurance firms have begun to use AI technologies to assess the repurchase rate of customers;
(d) Consumer finance - e.g. in auto finance sector, AI technologies may help finance companies to make risk assessment and provide credit products of highest match degree to consumers,
(e) Supply chain finance - e.g. AI technologies are used to create a bridge between the fund demanders and fund suppliers in the most efficient way; and
(f) Third-party services to financial institutions - e.g. third-party service providers use AI technologies to provide professional services to traditional financial institutions in their model designing, customer identity recognition, risk control and anti-fraud based on data analysis.
The Chinese government will encourage the novation of the usage of AI in the financial industry to improve efficiency and reduce the repetitive work and costs. Nevertheless, there will be inevitably some push and pause of the further application of AI technologies based on how the financial markets develop and react.