Whitepaper: The use of AI is on the rise in the financial sector. Utilizing machine learning algorithms to make decisions and predictions based on the available data can be highly valuable. AI offers benefits to both financial service providers and its customers by improving service and reducing costs. Examples of AI use cases in the financial sector are: identity verification in client onboarding, transaction data analysis, fraud detection in claims management, anti-money laundering monitoring, price differentiation in car insurance, automated analysis of legal documents, and the processing of loan applications.
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This white paper is the result of a research project by Hogeschool Utrecht, Floryn, Researchable, and De Volksbank in the period November 2021-November 2022. The research project was a KIEM project1 granted by the Taskforce for Applied Research SIA. The goal of the research project was to identify the aspects that play a role in the implementation of the explainability of artificial intelligence (AI) systems in the Dutch financial sector. In this white paper, we present a checklist of the aspects that we derived from this research. The checklist contains checkpoints and related questions that need consideration to make explainability-related choices in different stages of the AI lifecycle. The goal of the checklist is to give designers and developers of AI systems a tool to ensure the AI system will give proper and meaningful explanations to each stakeholder.
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In this policy brief we recommend that in order to face numerous societal challenges such as migration and climate change, regional governments should create a culture of innovation by opening up themselves and stimulate active citizenship by supporting so called Public Sector Innovation (PSI) labs. These labs bring together different types of stakeholders that will explore new solutions for societalchallenges and come up with new policies to tackle them. This method has been developed and tested in a large EU funded research project.
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Dit essay legt het belang van de gelaagdheid in het sociaal werk bloot. Professionals willen weten hoe het werkt, organisaties wat er werkt en bestuurders waartoe het werkt. Omdat hierover tussen de verschillende partijen geen helderheid bestaat, ontstaat een Babylonische spraakverwarring en afrekencultuur. Een essay over de gelaagdheid van kennis in de sociale sector.
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The shortage for ICT personal in the EU is large and expected to increase. The aim of this research is to contribute to a better understanding of the roles and competences needed, so that education curricula can be better aligned to evolving market demand by answering the research question: Which competence gaps do we need to bridge in order to meet the future need for sufficiently qualified personnel in the EU Software sector? In this research, a mixed method approach was executed in twelve European countries, to map the current and future needs for competences in the EU. The analyses shows changes in demand regarding technical skills, e.g. low-code and a stronger focus on soft skills like communication and critical thinking. Besides this, the research showed educational institutes would do well to develop their curricula in a practical way by integration of real live cases and work together with organizations.
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Explainable artificial intelligence (xAI) is seen as a solution to making AI systems less of a “black box”. It is essential to ensure transparency, fairness, and accountability – which are especially paramount in the financial sector. The aim of this study was a preliminary investigation of the perspectives of supervisory authorities and regulated entities regarding the application of xAI in the financial sector. Three use cases (consumer credit, credit risk, and anti-money laundering) were examined using semi-structured interviews at three banks and two supervisory authorities in the Netherlands. We found that for the investigated use cases a disparity exists between supervisory authorities and banks regarding the desired scope of explainability of AI systems. We argue that the financial sector could benefit from clear differentiation between technical AI (model) explainability requirements and explainability requirements of the broader AI system in relation to applicable laws and regulations.
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The future of the business sector for students in higher education is uncertain. The reasons for this are technological developments, the effects of globalisation and the shifting of business models (Brynjolfsson & McAfee, 2014; Helbing, 2014). The consequences of digitalisation and robotisation are large for professions in the financial-economic sector, such as accountancy and finance, business economy, and marketing (Frey & Osborne, 2013; Deloitte, 2016). As a result, certain jobs will disappear, but on the other hand new types of jobs will arise. It is expected that people in employment will have to have a strong adaptive ability to handle fast changes. There is an increasing expectation that they need to be mobile between employers and that they should be able to deal with a variety of new tasks, roles and positions (Dochy, Berghmans, Koenen, & Segers, 2015). Professionals need to have a sense of great flexibility in order to be able to anticipate these changes based on their own power and ambition. In addition to this adaptive ability, good interpersonal skills are essential due to the need for working in multidisciplinary teams on complex issues (Onstenk, 2017). The Social and Economic Council of the Netherlands (Sociaal-Economische Raad, 2017) presumes that the level of basic skills required to participate in an increasingly complex society is continuously growing, and they advise upcoming professionals to train their resistance, flexibility and the ability to continuously develop in order to maintain sustainable employability. In this way professionals regularly need to be able to reinvent themselves during periods of change (Van Water & Weggeman, 2017; Frie, Potting, Sjoer, & Van der Heijden, submitted for publication). This chapter will describe how the Department of Business, Finance & Marketing (BFM) of The Hague University of Applied Sciences (THUAS) has found an answer to the challenges of a Department-wide educational innovation. First it is outlined what this innovation involves and how it will be designed. The net paragraph clarifies the overlap in the competency profiles of the five programmes of BFM. Then the next steps of this educational innovation process are described. Finally, insights will be discussed as to the role of the lecturers and the business sector, as valuable partners, within this educational reform.
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Generatiewisseling binnen de agrarische wereld is een complexe proces. Voor de toekomst van de sector is het daarentegen noodzakelijk. Deze sector is van groot belang voor ons voedselsysteem en de leefbaarheid van stad en ommeland. De complexiteit zit in de duur van het bedrijfsovername proces en het aantal betrokkenen met verschillende belangen en inzichten. In deze bundel richten we ons op bedrijfsoverdragers, bedrijfsovernemers, partners, niet overnemende familie, adviseurs. De verhalen komen uit de praktijk, waarbij de bedrijfsovernames in verschillende fases zitten. Naast een inleiding beschrijven we ook de lessen die we geleerd hebben door in gesprek te zijn met de praktijk.
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The increased adoption of electric vehicles worldwide is largely caused by the uptake of private electric cars. In parallel other segments such as busses, city logistics and taxis, are increasingly becoming electrified. Amsterdam is an interesting case, as the municipality and the taxi sector have signed a voluntary agreement to realise a full electric taxi fleet by 2025. This paper investigates the results of a survey that was distributed amongst 3000 taxi drivers to examine perceptions and attitudes on the municipal charging incentives as well as taxi ride characteristics.
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The economic recession has hit especially hard the residential building sector in the EU region, e.g., the number of the housing completions has decreased -49% and the total residential output has been squeezed down by -24% between 2007 and 2014 (Euroconstruct, 2015). In turn, the aim of our paper is to suggest a set of radical, novel programmes for developing the national residential building sectors within EU member countries up to 2025. We have applied the framework of strategic niche management (SNM) to the diagnoses of the current portfolios of the innovation, R&D programs in our two member country contexts. In the case of the Northern Finland, the prime example is Hiukkavaara, the largest district to be built in the City of Oulu. Homes will be constructed for 20,000 new residents. Hiukkavaara is a model for climate- conscious design in the northern hemisphere. Energy and materials are conserved, nature is valued and human beings adapt to their environment. One sub-programme involves Future Buildings and Renewable Energy Project. In the case of the Netherlands, the prime example is Energiesprong (Energy Leap), i.e., the innovation programme commissioned by the Dutch Ministry of the Interior. The aim is to make buildings energy-neutral and boost large-scale initiatives. The sub-programmes are targeting homes owned by housing associations, privately owned homes, office buildings, shops and care institutions. This programme is about ensuring new supply by encouraging companies to package a variety of technical sub-solutions, full services and financing options as well as about asking clients to put out tenders and ask for quotes in novel ways, with the government making changes to the rules and the regulations. Experiences on which the Dutch case in this paper focuses are sub-programmes for residential buildings, which include de Stroomversnelling, LALOG and Ons Huis Verdient Het. Based on the emerging Finnish and Dutch evidence, we are suggesting key elements to be incorporated into future national residential programmes within EU member countries on: (1) radical direction with balanced stakeholder groups, trustworthy advocates, contextual goal-setting and barriers management, (2) radical networking with entrepreneurial roles and causal links, novel expertise, transparent choices and digital platforms and (3) radical learning processes to arrive at better informed markets on user preferences, co-innovating, new rules and regulations, higher performance/price ratios, higher quality, new roles and responsibilities assignments.
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