Digital development in the financial sector is increasingly gaining speed. At the same time customer behaviour and expectations are changing. Banks used to gain customer insight through personal meetings between the customer and his/her advisor. Nowadays, more and more meetings take place through digital channels. For the European savings and retail banks this development means a change in how insight into customer behaviour is gathered. Customer insight now needs to be gathered by using different dimensions, such as channel and product behaviour, customer preferences, and the change of customer engagement. Offering financial advice through digital channels is an important step to adapt to this development. The savings and retail banks are up to this challenge and are currently developing/implementing new tools and adapting existing tools as well as analysing possibilities to use other (and more) data sources.
As the Discussion Paper refers to MiFID II ESBG would like to make a remark in this regard. ESBG would like to raise awareness of the fact that the implementation of this directive bears the unwanted practical consequence of creating a burden for small investors to receive recommendations. MiFID II contains vast information duties and obligations for advice records which create administrative burdens with regard to the every-day advice of small investors. ESBG expects this to result in a serious challenge for the savings and retail banks.
Last but not least, what is true is that the regulatory environment and development in the area of automated financial advice has not kept pace with the market developments and customer expectations. Thus, technical solutions are at the moment slightly ahead of the legal reality. This can create obstacles, as most existing pieces of law do not consider the provision of automated financial advice. Thus, ESBG observes, in parts, a lack of clarity in what is prudent and what is not. Addressing this issue, however, would be the responsibility of national and European law-makers.
[In the online ESBG response to the ESA Discussion Paper the above remarks will be stated under question No. 24 as additional comments.]
MAIN CHARACTERISTICS OF AUTOMATED FINANCIAL ADVICE TOOLS
1. Do you agree with the assessment of the characteristics of automated financial advice tools presented in this Discussion Paper? If not, please explain why.
First of all, ESBG would like to make a general remark on the definition of automated financial advice. For reasons of simplification, ESBG suggests to just distinguish between consumer-facing tools and advisor-facing tools. Doing so can help to provide a much easier and clearer definition. ESBG supports the characterisation of automated advice tools as consumer-facing-tools in opposition to advisor-facing-tools which shall not be considered as automated advise.
Apart from that, ESBG thinks that the more sophisticated ESA definition of financial advice tools needs to be modified in parts and should be further sharpened in other regards. According to the ESAs, three main characteristics are needed: (1) the consumer uses the automated tool directly without (or very limited) human intervention, (2) an algorithm uses information provided by the consumer to produce an outcome and (3) the output of the tool is, or is perceived by the consumer, as financial advice. On these points ESBG has the following comments:
- A case that can be problematic under the current definition is the criteria of the customer's perception of getting advice. This can include cases where a financial service provider did not intend to provide advice. A practical example where this problem arises is the following: If a customer uses a self-service tool which helps to assess what amount of a consumption loan he/she can afford, this could already be seen as "advice" under the ESA definition. However, from the banking side it was not intended as financial advice but just as a bank service offering. In this context, and to avoid legal grey areas, it would need to be clearly determined when a recommendation/general information turns into "advice". Another example is the outcome of an automated tool which makes clear that the actual recommendation will be given afterwards by a human as the outcome of the automated tool does not specify the products (e. g. it only suggests target portfolios).
- This point is similar to the problem just described above and refers to the distinction between partly automated processes (paragraph 19) and other automated tools which are outside the scope of the ESA Discussion Paper (paragraph 27). ESBG agrees that automated tools which provide only general information to consumers (even if it is on the basis of information consumers have before introduced into that tool) should be excluded from the scope. The outcome in such cases does not contain an educative element but is, for instance, a mere filter of a universe of possible products (without recommending a specific one among them) and it is the customer who decides on a self-assessment basis. Such automated tools cannot be classified as financial advice and should clearly be out of scope of the ESA Discussion Paper. Only automated tools which are providing advice - and not only general recommendations - have the right to market their service as advice tools.
Finally, ESBG would like to point out that automated advice needs to be subject to the same supervisory requirements as advice provided by a human adviser. The same activities have to be subject to the same regulatory standards. Therefore, automated advice should be considered as an "advice" under the relevant applicable legislation (e.g. MiFID II).
2. Are there any other relevant characteristics of automated financial advice tools?
3. Are you aware of examples of automated financial advice tools being used in the banking, insurance, and/or securities sectors? Please provide examples, giving details of their operating process.
ESBG expects that the provision of automated financial advice will become a more and more common service and will meet a growing expectation from the customer side. Automated tools which some savings and retail banks have already implemented (however, those might not necessarily fall under the definition of "automated financial advice" in the ESA paper) are fully or semi-automatized solutions on consumer loans, such as online credit applications. An automated tool some savings and retail banks offer helps the consumer to choose products which are fitted to the customer profile.
4. Do you offer/are you considering offering automated financial advice tools as part of your business model? If so, please briefly describe: i) what type of entity you are, e.g., long established, start-up, a product provider, an intermediary; ii) the service you provide (e.g. to what extent do you integrate human interaction in the tool you provide?); iii) the nature of your clients; iv) your business model; v) who developed the automated tool (i.e. an external company or developed internally?); and vi) the size of your activity and/or forecast activity?
ESBG is convinced that automated financial advice will change the customer experience by offering easier access to services at any time. Some European savings and retail banks have already implemented automated financial advice tools. Others are currently developing such tools and exploring the areas of use.
5. Do you consider there are barriers preventing you from offering/developing automated financial advice tools in the banking, insurance and securities sectors? If so, which barriers?
The financial advice business is very competitive. Fintechs can enter the market with relative ease as the entry barriers are low and the technology is easily accessible. For traditional banks, obstacles can be created as they have to observe stricter regulation in some regards for instance on lending procedures. Additionally, due to the Basel regulations, banks need to be compliant with strict risk taking rules which can create obstacles to taking on board new developments.
Regarding automated financial advice, ESBG observes further barriers resulting from a legal environment that has not kept pace with the development of the technology. One concrete example in this regard is the General Data Protection Regulation (GDPR) on which a political agreement was found in December 2015. The GDPR regulates data processing in profiling and the need for human assessment, data transfer to non-EU countries and contains much wider rights for data subjects (customers) to request the deletion of data. ESBG would like to raise awareness of the regulator's challenge to find the right balance between data protection rights and the development of sophisticated tools for automated financial advice.
6. Do you consider the potential benefits to be accurately described? If not, please explain why.
According to the ESA Discussion Paper, the list of potential benefits is based on the prior assumption that automated tools are technologically robust. In this regard, ESBG feels the need to point out that potential benefits can only be as good as the program which underlies the technical tool. In every case, ESBG would like to raise awareness of the fact that the development of solid intelligent tools which provide the consumer with maximum quality advice is a constantly evolving - and improving - process, which requires huge investments, in particular in the first stages of the development. Therefore and, at least, in these first stages, the programming of automated advisors will probably always be based on past events. Thus, the benefit of providing future oriented real-time advice should be relativized in this regard.
Some of the benefits listed in the ESA Discussion Paper are not specifically related to automated financial advice. In this context, ESBG would like the ESAs to clarify that financial advisors, of course, also have access to electronic tools which provide them with up-to-date data, consistent information, logical algorithms and prices of transaction benchmarks.
On the whole, ESBG is worried about the opposing comparison between automated advice and human advice and urges the ESAs to avoid such an open confrontation. It is risky and a wide-reaching simplification to present automated advice as being superior to human advice due to its easier accessibility, consistency and lower costs (that is how it is described in this section). If a comparison cannot be avoided, ESBG suggests to add a balancing element. For instance, mentioning that human advice allows for the consideration of any (emotional) subtleties emerging from the human interaction with the customer. Also, human interaction is [still] superior with regard to reacting to unexpected situations.
In addition, paragraph 31 mentions that automated advice is cheaper than face-to-face advice. This may be true for rather costly fee-based advice, where consumers have to pay for a recommendation irrespective of whether or not they later choose a product. By contrast, in the case of commission-based advice, consumers are not charged directly for the advice. They pay, however, indirectly and once they have actually chosen a product. That consumers pay (indirectly or directly) for this service does not depend on the advice tool they use. ESBG rejects to initiatives that could force small investors to switch to automated advice. This could further be problematic in view as the use of automated financial advice requires a certain level of financial education and digital skills (for more details please see below answer to question 19).
Finally, ESBG would like to highlight that in practice automated financial advice could not be adapted to all segments of customers. For instance, customers that lack digital skills could not access and use automated financial advice.
7. Are you aware of any additional benefits to consumers? If so, please describe them.
ESBG thinks that the ability to deliver advice at the same time to a number of clients without having to meet them in person is important. Not having to be available for a physical meeting or even a virtual one at a specific time may improve the service for certain groups of customer while not for others.
8. Do you see any differences in the potential benefits arising for consumers in each of the banking, insurance and securities sectors?
9. Have you observed any of these potential benefits? If so, please provide examples and describe the kind of benefit that has accrued.
10. Do you consider the potential benefits to financial institutions to be accurately described? If not, please explain why.
ESBG expects that automated financial advice ultimately will lead to a growth in business as more customers will profit from financial advice and via the digital tool more consumers will be reached. Regarding the costs, ESBG feels the need to underline that even if costs for staff can be reduced by automated financial advice tools other costs would grow. Higher investments would be necessary in other areas such as IT, change management, marketing and compliance. Therefore, ESBG rather expects benefits from the growth of business than from the savings on costs.
ESBG has some doubts as to whether "removing the potential for differences due to human interpretation" (B10) is actually a benefit or whether the opposite is the case. Sometimes human beings have a sense or feeling of a situation that is important and that a machine lacks. For instance, an automated tool relies on the information it is provided with and has no ability to wonder whether the information it is provided with is realistic or requires anything other than standard advice. Thus, it lacks the ability to assess whether for any specific reason a less standardised approach is more appropriate in an individual case or the information provided is not realistic at all.
The Discussion Paper further mentions the benefits of automated tools delivering a consistent customer experience by removing differences in human interpretation (paragraph 42). ESBG is not convinced whether this point is actually a mentionable benefit. It is important to consider the other side of the coin: If too many customers receive the same consistent standardised advice, and the same update on this advice at the same time, both might cause market distortions and can lead to systematic risks. Regarding paragraph 44, as the machines for automated financial advice will continuously learn and change over time, it is also possible that following back a decision taken by the machine may be a rather difficult and complex procedure.
11. Are you aware of any additional benefits to financial institutions? If so, please describe them.
12. Do you see any differences in the potential benefits arising for financial institutions in each of the banking, insurance and securities sectors?
13. Have you observed any of these potential benefits? If so, please provide examples and describe the kind of benefit that has accrued.
14. Do you agree with the description of the potential risks identified? If not, explain why.
ESBG considers the risk described under R6 "Consumers are unaware that the personal data they input in the tool is used in ways they did not envisage when they provided it" as possibly exaggerated. Financial companies providing these services are expected to do both - to inform and to act in the customers' interest as well as to be compliant with external demands, such as data protection. On top of that, the information in the digital tool in any case needs to be easily understandable and in clear and plain language.
Regarding R12, ESBG thinks that the described effect is indeed rather likely. The reason being that the advice given by automated tools would probably produce a feedback loop among each other which would increase the probability of the described systemic impact.
15. Do you consider there to be any risks missing? If so, please explain.
One risk arising, on which ESBG has already touched upon, is the following: According to the definition, it would be possible to design an automated tool creating output that a consumer could reasonably perceive as financial advice but which at the same time would not fall under the scope of the recent definition. Thus, the consumer would reasonably perceive that he/she received advice even though this was not the case. Any rules referring to automated financial advice would have to consider this risk of circumvention for the consumer, so the automated advice provided should be considered as "advice" in the relevant legislation aiming at consumer protection (e.g. MiFID II).
Another risk that should be considered are exceptional cases or so called "black swan events". When markets fall, seemingly uncorrelated events can become highly correlated. ESBG observed that improbable events are becoming more likely to happen lately. Traditional market theories and models are lately being tested. Thus, ESBG sees a risk in basing assumptions only on "normal distributions" or classical models. ESBG calls on the ESAs to take into account the development of the markets since 2008 and the (potential) level of intervention of the European Central Bank, which is leading to unknown scenarios.
16. Do you see any differences in the potential risks arising for consumers in each of the banking, insurance and securities sectors?
17. Have you observed any of these risks causing detriment to consumers? If so, in what way?
18. Do you agree with the description of the potential risks identified? If not, explain why.
ESBG asks the ESAs to review their risk assessment R15 in view of the soon to be adopted General Data Protection regulation (GDPR). It might be inconsistent to list human assessment - which consumers still widely expect to be available at a certain point in many processes - as a risk that could lead to disregarding the role that automated financial advice should play. For instance, the new GDPR, says that in case of decisions that are solely based on automated processing the data controller shall implement suitable measures to safeguard the data subject's rights and freedoms and legitimate interest, at least the right to obtain human intervention on the part of the controller, to express his or her point of view and to contest the decision - Article 20, paragraph 1 and 1b. It could be contradictory to list an action as a risk which is in some cases required by law - and therefore unchangeable by the ESAs.
19. Do you consider there to be any risks missing? If so, please explain.
ESBG thinks that it is crucial to consider risks arising from the consumer's individual digital skill set and level of financial education. Said risks can materialise when customers lack basic financial education or IT skills. The use of automated tools requires a certain level of know-how as no human advisor is guiding the user through a questionnaire. Recent studies and surveys show that not all consumers have the necessary set of competencies and skills to use automated advice tools properly. For instance, a Policy Paper of the UK government of 2014 states (referring to other sources) that 21% of Britain's population lack the basic digital skills and capabilities required to realise the benefits of the internet. In addition, a 2012 Eurobarometer survey showed that 52% of consumers tended to opt for the first product they see when obtaining a current bank account or a credit card. It is important to acknowledge that a lack in financial education and digital skills can create obstacles for consumers to get access to and effectively use automated financial advice to their benefit. Moreover, a memo from the Swedish Financial Supervisory Authority (FSA) as of 2015 states that results from a research study during 2014 clearly indicate that many adults in Sweden lack numeracy and financial understanding. According to the Swedish FSA, the knowledge deficiency is assessed as comparable to other countries.
20. Do you see any differences in the potential risks arising for financial institutions in each of the banking, insurance and securities sectors?
21. Have you observed any of these risks causing detriment to financial institutions? If so, in what way?
POSSIBLE EVOLUTION OF THE MARKET
22. Would you agree with the assessment of the potential evolution of automated advice? Please provide your reasoning.
Regarding the point mentioned under 91 and 92, ESBG would like to particularly stress the importance of these points which very well reflect the obstacles observed in practice.
23. How do you think that the market for automation in financial advice will evolve in the near future in the banking, insurance and investment sectors? Please also provide details of any relevant data or information to support your views, where available.
24. Are there any other comments you would like to convey on the topic of automation in financial advice?
[See above the introductory remarks.]
About ESBG (European Savings and Retail Banking Group)
ESBG brings together savings and retail banks of the European Union and European Economic Area that believe in a common identity for European policies. ESBG members support the development of a single market for Europe that adheres to the principle of subsidiarity, whereby the European Union only acts when individual Member States cannot sufficiently do so. They believe that pluralism and diversity in the European banking sector safeguard the market against shocks that arise from time to time, whether caused by internal or external forces. Members seek to defend the European social and economic model that combines economic growth with high living standards and good working conditions. To these ends, ESBG members come together to agree on and promote common positions on relevant matters of a regulatory or supervisory nature.
ESBG members represent one of the largest European retail banking networks, comprising of approximately one-third of the retail banking market in Europe, with total assets of €6,702 billion, non-bank deposits of €3,485 billion and non-bank loans of €3,719 billion (31 December 2014).
European Savings and Retail Banking Group – aisbl
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Published by ESBG. March 2016.
 In finance a black-swan event refers to an extreme and highly unexpected happening, like the financial crisis. Mr. Nassim Nicholas Taleb popularised the term in his best-selling book: The Black Swan: The Impact of the Highly Improbable (New York: Random House and Penguin. 2007).