Overview Articles Authors Impact. About this Research Topic Submission closed. Decisions about financial issues take many forms across different sectors and products such as: mortgages, gambling, everyday consumer choices, healthcare, insurance, education, retirement, pensions, and professional or semi-professional investing e.

Being ill-equipped to make sound financial decisions has been identified by the Millennium Project a United Nations think tank as a key issue facing humanity because of the potential devastating costs to individuals and whole societies. In this Research Topic, we aim to focus on psychological methods and approaches that can improve the capacity to make financially sound decisions.

Studies have also examined other cognitive, technological and motivational strategies. These include using incentives or social accountability to mitigate the negative impact of cognitive biases or adverse decision environments, and to reduce the magnitude of judgment errors.

Research has also focused on identifying which aspects of the decision making process to modify to alleviate the impact of biased decision making, such as decision readiness, modification of the person, or modification of the environment. While decision making research has spanned a wide range of applications in a variety of fields and environments e.

The objective of this Research Topic is therefore to assemble recent advances in psychological techniques and strategies aimed to improve financial decision making. We specifically welcome research across a diversity of contexts, ranging from personal financial decisions e.

We welcome contributions from a variety of theoretical, conceptual, and methodological approaches within psychology and its allied disciplines. Further, we welcome articles from varied domains of application e. We seek to invite empirical contributions that will inspire further advances in understanding how to improve financial decisions through strategies, techniques, and modifications, as well as novel approaches that may contribute to further insights in this Topic.

Welcome article types include Original Research, Reviews, and Brief Research Reports. Configurators bring many advantages to companies, such as reduced lead time Kristjansdottir et al. To summarize, the manufacturing industries have been utilizing configurators to develop customized products by providing customers with rich information and knowledge about product features, functions, options, and so on, thus better educating customers.

Recognizing the similarities between product and service development, researchers have argued that configurators can be equally applied in other industries, such as the healthcare and financial industries. Consequently, the application of configurators in the financial industry has not been reported.

To win market shares, same as the other types of service companies, the financial industries e. In fact, as early as the s, Pine et al. Some authors have also examined various approaches to offering personalized financial services.

In their empirical case study, Koch and Inanc showed how a Turkish bank offers customized credit cards as an application of mass customization, which is well-known in the manufacturing industry. With an understanding of the influence of customization as a generic methodology, Winter proposed a product-oriented approach to personalize financial services, e.

Their approach is based on an open variant product i. In brief, as with product customization in manufacturing, the financial industries devote themselves to developing and offering personalized services.

Moreover, though different specific approaches were discussed, the authors have demonstrated that there are similarities between product customization and financial service personalization and that financial services can be personalized based on product customization principles.

While considerable efforts have been invested in product and service personalization, the financial sector has yet to fully capitalize on the potential to tailor financial services according to individual needs and preferences. This gap highlights an untapped opportunity to merge technological advancements with financial service offerings, thereby enhancing customer engagement, financial literacy, and decision-making.

To this end, in view of the successful applications of configurators in the manufacturing industries and the similarities between financial service personalization and product customization, in this study, we aim to explore the application of configurators in the financial industry.

More specially, we develop a personalized configurator to offer financial services by improving the financial literacy of individuals and supporting their financial decision-making.

However, while the manufacturing industry has embraced configurators, their potential in the financial sector remains relatively unexplored Beck et al. This personalized financial configurator addresses pension plans for middle-aged people in Demark.

We limit the users of this personalized financial configurator to Denmark because the government pension regulations in Demark are not applicable in other countries. Guided by the pivotal role of financial literacy and the need to address gaps in financial process understanding and decision-making, this study embarks on a focused inquiry.

Our research question is as follow:. How can configurators, known for their role in product customization, be harnessed to enhance financial literacy and offer personalized financial services?

It has underscored the significance of addressing the challenges posed by complex financial systems and the potential repercussions for individuals lacking adequate financial literacy.

The introduction has also highlighted the growing interest in personalized financial services, drawing parallels between the manufacturing and financial sectors in their pursuit of customization to better serve customers.

Moreover, the establishment of configurators as a technological cornerstone for product customization has been discussed, emphasizing their benefits in terms of resource efficiency, reduced errors, and enhanced customer satisfaction and financial literacy.

In essence, this paper sets out to not only fill an existing gap in the literature but also to pave the way for a novel paradigm in the financial sector by marrying technology, financial literacy enhancement, and personalized service provision through the innovative application of configurators.

The rest of the paper is organized as follows. We classify the relevant literature into two streams, including solutions to improve financial literacy and configurator applications, and review it in the next section.

The literature closely related to this study can be classified into two streams, including financial literacy improvement solutions and configurator applications for creating customized products and services. The available studies have concluded that, through a concentrated effort, individuals are able to improve their financial literacy.

However, the available solutions are often generic by providing standard results, instead of personalized ones. Additionally, most of the studies are theoretical or are designed to fit a large sample size of the population Rodrigues et al. For example, van Rooij et al. Such terminology might be useful, while the individuals first need a rudimentary understanding of their own financial life cycle.

Apostolakis et al. Li et al. Hence, traditional finance is prone to problems such as financial exclusion and financial inhibition Zhang et al. Marsden et al. However, the cost and inefficacy of traditional financial education e.

Cole et al. Moreover, providing classroom-based financial education generally yields weaker results, compared with implementing higher-intensity, personalized educational treatments Carpena et al.

In their study, Crawford et al. Similarly, Hoffmann and Otteby investigated if consumers perceive personal finance blogs as a helpful alternative to acquiring financial knowledge.

They assessed personal finance blogs as an online resource, which had the potential to provide just-in-time financial education. Highlighted by their findings, the consumers who are most likely to use personal finance blogs seem to need them the least.

The number of studies on personalized financial decision support is very limited. To the best of our knowledge, Ramjattan et al. In their study, the authors used chatbot educational technology to encapsulate the concepts of just-in-time education, nudge theory, and gamification to provide impactful personalized advice and financial education.

One of their questions addressed is: If the users think a chatbot would improve their financial literacy. Regarding the high percentage of positive answers i. However, the study neglected the concerns around data privacy and also the importance of user-friendliness to the adoption of such a tool as the study shaped around the prototype.

In a literature review, Wube et al. The authors mentioned the importance of analyzing the security and privacy vulnerabilities of chatbots in the financial sector, as well as the importance of customer engagement across multiple channels to provide some personalized offerings.

Some commercial financial IT systems exist, however, with very limited users in certain regions. Consequently, in general, they have a very low level of accessibility. The principle of configuration together with configurators has been extensively applied in the manufacturing industries to develop customized products.

Motivated by the benefits that their applications bring to companies, they are also employed in other industries to address the configuration and development of various tangible or intangible artifacts.

Ariano and Dagnino demonstrated the application of a configurator to create bills of materials of furniture in a furniture manufacturing firm.

Hvam et al. using the configurator. In the construction industry, Piroozfar et al. Similarly, Cao et al. In the service industries, Behunova et al.

Focusing on engineering and manufacturing, Shafiee demonstrated the application of configurators in the chemical industry that manufactures catalysts and chemical plants. Schäffer et al. Hvam described how a configurator was used to design facilities in a large manufacturer of cement plants.

Rasmussen et al. Moreover, in a longitudinal case study by Zhang and Shafiee , the configurators were used to customize catalysts.

Hafidi and Bensebaa proposed an adaptive and intelligent tutoring system based on expert systems configurators not only on the difficulty level of activities but also on the changing learning performance of the individual learner.

Bennat proposes a configurator for investigating high innovation performance in SMEs by comparing different German regions. Nevertheless, their applications in the financial industry to provide personalized financial services by improving individual financial literacy have not been reported.

In this study, we address the development of a personalized financial configurator and its application. By bridging the gap between technology and finance, a personalized financial configurator can address contemporary challenges faced by traditional financial advisory services.

These challenges include information overload, high costs, lack of customization, and limited accessibility. Through its integration of advanced technologies such as AI and data analytics, the configurator can process extensive financial data, providing tailored insights and real-time recommendations that cater to each individual's unique circumstances.

Furthermore, the impact of a personalized financial configurator reaches beyond individual financial well-being. By promoting financial literacy and enabling informed decision-making, this tool contributes to broader societal goals. Individuals empowered with financial knowledge are better equipped to manage their economic futures, reducing reliance on public social services and fostering economic resilience at both individual and community levels Beck et al.

A financial configurator offers personalized financial planning, enhances financial literacy, and tailors investment portfolios based on individual preferences and circumstances. It assesses risk tolerance, aids retirement planning, suggests debt management strategies, and analyzes real-time scenarios for proactive decision-making.

Continuously adapting, it provides accessible, cost-effective, and efficient financial advice, democratizing services and empowering users to make informed decisions aligned with their evolving financial situations.

In developing the personalized financial configurator, we follow the below five major steps, including 1 determining project goals, 2 determining the project scope, 3 identifying system requirements, 4 knowledge acquisition and modeling, and 5 developing the configurator.

While Fig. Most individuals have great difficulty managing their economic portfolios within the increasingly complex commercial financial systems.

The studies have demonstrated the relationship between digital inclusive finance and welfare Li et al. These digital systems are often riddled with complexities, jargon, and rapidly changing dynamics, making it daunting for the average person to navigate.

In addition, most of these available systems are designed for a single purpose, e. Thus, the personalized configurator to be developed should act as a knowledge management system by including a simple and user-friendly interface to allow users to get a fast and easy overview of their financial situations.

Economic innovation operates as a two-sided blade, carving out opportunities while also presenting challenges. The configurator acts as a dynamic repository of financial knowledge, guiding users through complex decisions by synthesizing diverse information sources into a coherent and user-friendly format.

By doing so, it helps bridge the gap between financial literacy and effective decision-making. In terms of better-educating individuals, the personalized financial configurator is expected to improve their understanding of economic situations and further adjust their attitudes toward pension investment.

Regarding investment decisions, much research has examined the link between financial literacy and retirement planning. For instance, Lusardi and Mitchell and van Rooij et al. More specifically, the goal is to educate users about pension plans and corresponding investments and to illustrate the impact of their pension decisions on their economic situations.

Consequently, the configurator needs to 1 provide real-time, higher-quality financial data, 2 reduce the complexity of pension services provided, 3 enhance financial literacy, and 4 generate pension-related outputs based on different input alternatives.

In line with the project goals above, we set the scope of the personalized financial configurator by considering the expected outputs. In particular, the scope is described in terms of general personal information, income information, free assets, diverse expenses, current pension information and regulations set by the government, and financial environments, as shown in Fig.

The specific values of these parameters are necessary to calculate personalized pension plans. In addition, considering the local laws and regulations in the financial industries, we limit the users of the personalized financial configurator to people who reside in Denmark.

However, the results from this paper can be used at a general level when developing financial configurators in other countries. As the financial services in consideration are pension plans, we focus on the requirements and needs of Danish residents who are not retired, middle-aged people, as middle-aged individuals are at a crucial juncture where they need to make significant financial decisions, particularly in the context of pension planning, investments, and debt management.

Focusing on this demographic ensures that the configurator addresses the specific challenges and financial goals of its intended users comprehensively. Moreover, it aligns with local laws and regulations, providing precise and legally sound financial advice tailored to the Danish financial landscape.

These parameters consider demographic factors specific to Danish residents, reflecting income, age, and local economic conditions. This focus on a single jurisdiction simplifies legal and regulatory complexities, minimizing the risk of inadvertent violations across multiple regions, thus avoiding potential legal and financial consequences.

Because the potential users of the personalized financial configurator are Danish residents possessing financial literacy at various levels and diverse educational backgrounds, thus we will identify diverse requirements for the output. To better educate these users, the personalized configurator, consequently, needs to provide output in several different formats, such as an online summary page, and an excel document containing detailed information.

In addition, it needs to offer user-friendly and independent solutions containing different levels of inputs and output. We categorize the input requirements for the configurator based on the project scope above. Regarding general personal information, we identify some important parameters, such as the age of a user, and the number of children.

The identified parameters related to income include net salary and payment from side jobs. The parameters related to free assets are also determined, including stocks owned, other current investments made, inheritance, etc. Current pension regulations, such as retirement age, pension rates, and standard pension plans Footnote 1 , are identified as necessary input requirements, and financial environments, including inflation rates and investment strategies Footnote 2 discussed in Step 4 are determined.

The process of collecting and modeling financial knowledge within our system is a meticulous and crucial step in ensuring the provision of real-time, high-quality financial data. We source financial data from a variety of reputable and up-to-date sources, including financial market APIs, official financial reports, and economic databases.

The selection of these sources is based on their reliability, accuracy, and relevance to the Danish financial landscape. As a financial service provider, Penly delivers digital tools for personal finance planning and archives the rules and regulations for pension calculations.

In this study, we obtain pension-related data and knowledge by analyzing various documents and Excel sheets provided by Penly. In particular, inflation rate, taxation, investment plans, and pension savings are important knowledge for pension calculations. Once the data is collected, we employ a rigorous data preprocessing pipeline.

This includes data cleaning, validation, and structuring to ensure that the information is accurate and consistent.

Data quality is paramount, as any inaccuracies can significantly impact the accuracy of personalized pension plan calculations. Furthermore, we have implemented real-time data feeds from mentioned sources, enabling us to provide users with the most current financial information available.

This real-time aspect is particularly important in the financial domain, where market conditions can change rapidly and we ensure that our configurator offers users access to real-time, high-quality financial data.

This, in turn, empowers users to make informed decisions when planning their pensions, ultimately leading to more secure financial futures. To determine personalized pension plans, it is necessary to obtain various parameter values, such as income, expenses, free assets, and inflation rates, as explained above.

Because pension payments in Denmark are directly connected to income and inflation rates, it is important to estimate the main source of income and the salary for the upcoming years to better calculate personalized pension plans.

We develop a formula for estimating salary, which is a necessary element in the pension calculation model, in Eq. As shown in Eq. The Danish Council of Return Expectations reports three standard investment plans for pension savings and the corresponding investment amounts Council for Return Expectations, The three plans include i a low-risk plan, ii a high-risk plan, and iii a medium-risk plan.

Being consistent with practice, we assume the risks decrease in time. Affected by risks, the annual return rates are different from one year to another. We further model the growth of annual return rates in Eq. In the equation, IRRate denotes the initial average annual return rate, which can be calculated based on annual returns in the past; RRate n is the return rate at year n; Std represents the standard deviation of the annual return rates from the past.

The equation shows how the annual return rate grows in time when the annual return rates follow a normal distribution. Assume a user has an initial investment value, denoted as Investment 0. P is the ratio of the salary paid to the pension investment. Regardless of the pension plans, taxes will be deducted when an individual requests for the pension savings to be paid out.

Thus, it is very important to consider taxes in personalizing pension plans. Taxation in Denmark has three main categories, including labor market contribution tax Arbejdsmarked-bidrag, or AM , state tax which is divided into bottom tax and top tax , and communal tax , as shown in Table 1.

For an annual income higher than All these tax rates are summarized in Table 1. Figure 2 summarizes various configurator elements, including inputs, outputs, system functions, and interactions. In line with the system requirements identified earlier, the inputs include, e.

Based on the inputs, various outputs can be generated, including an overview of incomes, an overview of expenses, an overview of investments and assets, an overview of retirement preferences e.

As shown in Fig. For example, after calculating pension investment values based on the initial inputs, the configurator may ask the user to modify certain inputs e. Moreover, based on a personalized pension plan selected by a user, the databases will be updated. With the updated databases, the configurator, based on new inputs, calculates and generates different types of outputs for the user to make decisions.

The three tiers are the server, client, and data tiers. The client tier serves to get user inputs and display the results, while the server tier carries out data operations and processing. In the client tier, after logging into the personalized financial configurator in his browser by providing an ID and password, a user needs to launch his pension project.

The user will be asked to make necessary modifications if the input data is conflicting, incomplete, or invalid. Upon receiving consistent and valid inputs, the HTTP Hypertext Transfer Protocol server carries out calculations and optimizations and generates diverse outputs.

Each time when a user makes a decision in a personalized pension plan, the databases are updated. The new data will be used in the future to generate personalized pension plan recommendations. The client tier plays a crucial role in ensuring a user-friendly experience and facilitating efficient data exchange between users and the server tier.

User authentication: users access the configurator through their web browsers by providing their unique ID and password. This authentication process ensures that only authorized users can access and utilize the system.

Input validation: the client tier conducts preliminary checks on user inputs to identify potential issues, such as missing or improperly formatted data. Users are prompted to correct any discrepancies before proceeding.

Display of results: once the server tier completes its calculations and optimizations, the client tier is responsible for presenting the results to the user. In the data tier, the databases host all the data.

The data tier serves as the repository for all the data used by the personalized financial configurator. It hosts a comprehensive database that stores essential information, including user profiles, financial parameters, and historical data.

This centralized storage ensures that the configurator has access to the necessary information for calculations and optimizations. Data retrieval: when the server tier requires specific data for calculations, it retrieves this information from the data tier. This retrieval process ensures that the configurator operates with up-to-date and accurate data.

At the core of our architecture lies the server tier. This tier is responsible for handling all data operations and processing tasks. When a user initiates a pension project, the server tier performs several critical functions.

In cases where conflicts, incompleteness, or invalid data are detected, the server tier prompts the user to make the necessary adjustments. Calculation and optimization: upon receiving consistent and valid inputs, the server tier proceeds to execute complex calculations and optimizations.

Each time a user makes a decision within their personalized pension plan, the databases are promptly updated to reflect these changes. This dynamic updating ensures that the configurator operates with the most current and accurate data. By following the above three-tier distributed architecture, we develop the personalized financial configurator based on a well-established configuration system shell, called Tacton, a leading Configure, Price, Quote CPQ SaaS partner for design to sales automation for industrial manufacturers.

The configurator is developed in such a way that the available financial systems, such as banking applications, NemID, national eID a secure two independent authentication factors as a Scandinavia-specific digital signature used to log on to public online banking and many other digital services , and local pension systems can be easily integrated with it.

This is achieved via the Application Program Interface API. For illustrative simplicity, Fig. In Zone 1, different input parameters see Step 3 are added, while in Zone 2, various attributes for each parameter are added.

For example, the parameter: Children has two properties: Name and Number of instances. Name is the parameter name children in this example and the Number of instances is the number of children of a user.

to show or hide the next input fields regarding children based on the number of children inserted by the user. Constraints are defined in Zone 3 to model the relationships among attribute values describing the same or different parameters. This constraint indicates that the total amount of the money received for all children is achieved by summing up the amount for each child.

Some constraints restrict the display of inputs. The current inputs primarily pertain to salary levels and investments simple for users and guide users through the process and provide options that are easy to understand and independent of complex financial jargon.

This integration will enable us to automatically retrieve a significant portion of user-specific information, reducing the need for manual inputs to a minimum.

This enhancement will further streamline the user experience and provide even more tailored financial guidance. Inflation is a dynamic force that profoundly influences the real value of assets and income over time. Within our configurator, users are prompted to input their assumed inflation rate, which serves as a baseline for calculations.

To enhance precision, users have the option to adjust the inflation rate based on an annual basis. This level of flexibility enables users to simulate a multitude of inflation scenarios, reflecting real-world volatility. For instance, users can model conservative scenarios with low inflation rates, or they can explore the potential consequences of high inflation environments.

Moreover, our configurator takes historical inflation data into account to provide users with insights and guidance on selecting an appropriate inflation rate. By leveraging a comprehensive dataset of historical inflation rates, users can make informed decisions based on past trends and economic realities.

Investment choices play a pivotal role in shaping the growth of financial assets and, consequently, the adequacy of retirement plans. We derive this model from historical data and standard deviations, enabling us to simulate the impact of various investment strategies realistically.

Furthermore, our configurator factors in the decreasing risks associated with longer investment horizons, mirroring established financial principles. This dynamic approach to modeling investment returns reflects the complexities of the real financial world, allowing users to make well-informed investment decisions.

Taxes are a critical facet of personalized financial planning, significantly affecting the final outcome of retirement plans. Our system meticulously considers the Danish tax landscape, systematically integrated into calculations to ensure that the personalized financial plans accurately reflect the tax implications of different financial scenarios.

For instance, users can explore how tax obligations evolve as their income and assets grow or as they transition into retirement. The development of the personalized financial configurator is underpinned by a robust commitment to a user-centered approach see Appendix.

We recognize the paramount importance of aligning the configurator with the unique needs, preferences, and expectations of our users. To achieve this, we initiated the design phase by conducting in-depth user research. This involved engaging with potential users 8 domain experts and 21 end-users through surveys, interviews, and usability testing sessions.

These interactions provided invaluable insights into the financial pain points, goals, and expectations of our target audience. It allowed us to uncover specific challenges individuals face in financial planning within the Danish context and identify areas where personalized assistance could be most beneficial.

Furthermore, a user-centered design approach guided the creation of the configurator's interface. We prioritized simplicity and clarity, presenting financial information in an easily digestible format.

User testing sessions were conducted iteratively to gather feedback and refine the interface to enhance usability. Additionally, we integrated features for user feedback and continuous improvement directly within the configurator.

The findings of this study bring to light a pioneering advancement in the realm of personalized financial planning. The personalized financial configurator, as developed and demonstrated, offers a level of tailored financial guidance and real-time planning that is, in many ways, unprecedented.

It marks a significant departure from traditional financial planning tools, which often provide generic advice and lack the adaptability to address the evolving financial situations of individuals.

We acknowledge the importance of considering generational differences when tailoring the personalized financial configurator to a broader user base. To achieve this, we conduct in-depth research profiling distinct generational characteristics, adapt user journeys to align with generational profiles, enhance educational content, establish feedback loops with users from various age groups, and adopt an agile development approach see Appendix.

Firstly, we intend to conduct comprehensive research to profile the distinct financial behaviors, preferences, and knowledge levels associated with different generations. Armed with these insights, the configurator can adapt its user interface and educational content to align with generational profiles, ensuring that the information presented resonates effectively with each age group.

Moreover, the incorporation of feedback mechanisms and user testing with representatives from various generations will allow us to fine-tune the configurator continuously. When using the personalized financial configurator, it is compulsory for a user to provide the basic information e.

Based on the selection results, the configurator displays a new page requesting specific information from the user or summarizing the input information provided by the user.

For example, Fig. If certain information in the summary is wrong, the user can go back to the relevant page and make necessary modifications. If the information in the summary is all correct, the user can click on the Ok button at the top right corner, as shown in Fig.

Graphs and recommendations for personalized pension plans. a An investment potential line graph. b A financial asset changing graph. c A graph showing investment potentials for retirement. Subsequently, the pension calculation model carries out calculation and optimization, and the configurator output the results.

These graphs include an investment potential line graph Graph a , a financial asset changing graph Graph b , and a graph showing investment potentials for retirement Graph c. The recommendations for personalized pension plans are shown in the left panel of the figure.

The different graphs and recommendations give the user an overview of her future economic situation. Such information can better educate the user, which, in turn, enables him to make optimal decisions in a pension plan personalized for him.

Also calculated are the minimum and maximum savings: 2. With the potential saving results, the configurator recommends suitable retirement ages, i.

In another example, based on Graph a, the user may select a high-risk investment plan, instead of a medium-risk one, as shown in the right panel in the figure.

From a theoretical perspective, our findings underscore the importance of a user-centric approach to financial technology development. It empowers individuals to make informed decisions aligned with their evolving financial situations, thus addressing a critical gap in the literature.

A notable theoretical contribution of this research lies in the development of dynamic financial planning models. Traditional financial models often lack adaptability to changing financial environments, which this paper addresses.

This model can guide future research on dynamic financial planning methodologies. The personalized financial configurator offers real-time, personalized recommendations for pension planning, investment, and taxation.

Moreover, users of the configurator experience tangible practical benefits in terms of time and effort savings. It ensures that individuals with varying levels of financial literacy can benefit from the tool.

By bridging the gap between financial complexity and user comprehension, it aligns with the practical goal of expanding financial services to a broader demographic. Users not only receive personalized recommendations but also gain a deeper understanding of the forces shaping their financial plans.

Caused by the variability in financial literacy as well as the complexity and limitations of available commercial financial systems, many individuals have great difficulty understanding their economic life cycles, thus being unable to make wise financial decisions.

To contribute to both literature and practice, in this study, we developed a personalized financial configurator to facilitate users to make optimal pension decisions.

It was developed by capitalizing on the configuration principles widely applied in other industries e. As demonstrated through its applications, the personalized financial configurator can provide rich information about, e.

Such information is presented in different forms, such as Excel files and graphs. With the recommendations and rich financial information, the user can make wise pension decisions, e.

While our personalized financial configurator holds substantial promise, it is important to recognize and address potential limitations and challenges.

One potential limitation lies in data accuracy and reliability, as the configurator relies on user-provided inputs and external financial data sources. To mitigate this, we are actively exploring partnerships with financial institutions and government agencies to enhance data accuracy and timeliness.

Additionally, cybersecurity concerns and data privacy issues are paramount when the system is implemented, and we have to be committed to robust security measures and compliance with relevant regulations. Furthermore, we acknowledge the possibility of generational and demographic biases in our algorithms and decision recommendations, and we are dedicated to refining our models to minimize such biases.

As we continue to develop the configurator, ongoing user testing and feedback collection will be pivotal in identifying and resolving any unforeseen challenges. Though the personalized financial configurator can facilitate users to make some wise financial decisions, they are limited to pension plans, which opens potential avenues for future research.

In particular, further studies need to expand the financial analysis within various areas, such as incomes, housing assets, and investments in the market, to ensure the accuracy of the life cycle analysis.

These areas need to be developed concurrently to ensure their interrelationships are considered thoroughly. Moreover, in this study, we targeted Danish users who are closer to the retirement age.

Hence, improving the configurator by including younger individuals as potential users might be beneficial. Hence, young users can learn the impacts of investment decisions on their economic life cycles earlier. Considering the diverse levels of knowledge and varying goals among different generations, future research may examine how these differences can be addressed and integrated into the improved configurator.

It is equally important to investigate how the various outputs can be better presented so that the users of different generations can easily understand the large volumes of financial information.

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While this Impproved typically doesn't directly identify you, it makijg to a more personalized Imprvoed experience. Notes Credit report transparency pension plans Imprvoed Denmark are low-risk, high-risk, and Improved financial decision making plans Council for Return Expectations, Privacy preference center. Motivated by the benefits that their applications bring to companies, they are also employed in other industries to address the configuration and development of various tangible or intangible artifacts. With this approach, you can break down complex business decisions and elect to pursue projects expected to yield the best outcomes.	Users are prompted to correct any discrepancies before proceeding. In essence, this paper sets out to not only fill an existing gap in the literature but also to pave the way for a novel paradigm in the financial sector by marrying technology, financial literacy enhancement, and personalized service provision through the innovative application of configurators. Have you considered professional financial advice? The selection of these sources is based on their reliability, accuracy, and relevance to the Danish financial landscape. While conventional finance models often assume that individuals act rationally and make decisions based on logic and data, the reality is that emotions, biases, and other psychological factors can play a significant role in financial decision-making.	There is a growing awareness of the importance of successful financial decision making (FDM) to individuals, organizations, and society 13 Ways to Improve Your Financial Decision Making · 1. Maintain a Holistic Financial Plan · 2. Slow Down, Give Yourself Time to Be Rational · 3 5 Ways Managers Can Use Finance to Make Better Decisions · 1. Perform Financial Statement Analysis · 2. Estimate the Financial Impact of Projects	Budget visibility · Workforce productivity · Customer satisfaction · Speed of decision-making · Data sharing and collaboration · Employee trust in data · Simplified The intervention substantially improves subjects' knowledge and conceptual understanding of compound interest (financial literacy), as measured by their You can	You can movieflixhub.xyz › blog › the-psychology-of-financial-decision-mak Strong financial knowledge and decision-making skills help people weigh options and make informed choices for their financial situations, such as deciding how
Alternative Investments Business Analytics Business Credit monitoring service Business and Climate Change CLIMB CORe Design Thinking and Innovation Digital Marketing Strategy Disruptive Strategy Economics for Managers Entrepreneurship Essentials Financial Accounting Global Improvrd Launching Dwcision Ventures Leadership Imrpoved Leadership, Improved financial decision making, and Corporate Accountability Financiak with Finance Management Essentials Negotiation Mastery Organizational Leadership Power and Influence for Positive Impact Strategy Execution Sustainable Business Strategy Sustainable Investing Winning with Digital Platforms. How to scope configuration projects and manage the knowledge they require. The current inputs primarily pertain to salary levels and investments simple for users and guide users through the process and provide options that are easy to understand and independent of complex financial jargon. Close pop up window. However, it is the individuals i.	To achieve this, we initiated the design phase by conducting in-depth user research. In their empirical case study, Koch and Inanc showed how a Turkish bank offers customized credit cards as an application of mass customization, which is well-known in the manufacturing industry. It hosts a comprehensive database that stores essential information, including user profiles, financial parameters, and historical data. Lyngby, Denmark. Basing incentive compensation on profitability metrics, not just volume, further supports both individual and institution success.	There is a growing awareness of the importance of successful financial decision making (FDM) to individuals, organizations, and society 13 Ways to Improve Your Financial Decision Making · 1. Maintain a Holistic Financial Plan · 2. Slow Down, Give Yourself Time to Be Rational · 3 5 Ways Managers Can Use Finance to Make Better Decisions · 1. Perform Financial Statement Analysis · 2. Estimate the Financial Impact of Projects	Financial education aims to improve decisions by helping consumers acquire the basic knowledge and skills they need to understand the choices they face. A large One way to improve your financial decision-making is to have control over your burn rate, optimizing your spending to secure long-term business Budget visibility · Workforce productivity · Customer satisfaction · Speed of decision-making · Data sharing and collaboration · Employee trust in data · Simplified	There is a growing awareness of the importance of successful financial decision making (FDM) to individuals, organizations, and society 13 Ways to Improve Your Financial Decision Making · 1. Maintain a Holistic Financial Plan · 2. Slow Down, Give Yourself Time to Be Rational · 3 5 Ways Managers Can Use Finance to Make Better Decisions · 1. Perform Financial Statement Analysis · 2. Estimate the Financial Impact of Projects
Configurators bring many Loan repayment relief to Improvsd, Instant loan repayment alternatives as decsiion lead time Kristjansdottir et al. To win market shares, decieion as the other types of service companies, the financial industries e. Previously, managers would analyze decsiion financial statements at month end, however, technology has enabled people to adopt modern financial reporting and visualize data at any time. Constraints are defined in Zone 3 to model the relationships among attribute values describing the same or different parameters. CFSB is registered with the Federal Deposit Insurance Corporation FDIC Certificate Encouraging clients to seek outside perspectives can be a valuable strategy for helping them overcome these biases and make better financial decisions.	LET'S CONNECT Contact Us White Papers Developer Docs. In essence, this paper sets out to not only fill an existing gap in the literature but also to pave the way for a novel paradigm in the financial sector by marrying technology, financial literacy enhancement, and personalized service provision through the innovative application of configurators. Hvam described how a configurator was used to design facilities in a large manufacturer of cement plants. Calculation and optimization: upon receiving consistent and valid inputs, the server tier proceeds to execute complex calculations and optimizations. If you feel there are specific areas that need more work, you can go back to any one day of the challenge to find relevant articles and tools to help you.	There is a growing awareness of the importance of successful financial decision making (FDM) to individuals, organizations, and society 13 Ways to Improve Your Financial Decision Making · 1. Maintain a Holistic Financial Plan · 2. Slow Down, Give Yourself Time to Be Rational · 3 5 Ways Managers Can Use Finance to Make Better Decisions · 1. Perform Financial Statement Analysis · 2. Estimate the Financial Impact of Projects	One way to improve your financial decision-making is to have control over your burn rate, optimizing your spending to secure long-term business financial decision making—teaching personal finance and teaching math. ▻ Improve personal finance knowledge: This is often seen as the natural way increase 5 Ways Managers Can Use Finance to Make Better Decisions · 1. Perform Financial Statement Analysis · 2. Estimate the Financial Impact of Projects	Tip 1: Asses Your Financial Reality · Tip 2: Identify Your Goals, and Estimate the Costs · Tip 3: Don't Forget Your Debt – and Your Emergency Fund Financial decision making is an important behavior with societal, interpersonal and individual-level outcomes. Decisions about financial issues take many Improve financial decision making with the right technology so you have accurate data and clear insights to make informed decisions at the right time

Improved financial decision making - Strong financial knowledge and decision-making skills help people weigh options and make informed choices for their financial situations, such as deciding how There is a growing awareness of the importance of successful financial decision making (FDM) to individuals, organizations, and society 13 Ways to Improve Your Financial Decision Making · 1. Maintain a Holistic Financial Plan · 2. Slow Down, Give Yourself Time to Be Rational · 3 5 Ways Managers Can Use Finance to Make Better Decisions · 1. Perform Financial Statement Analysis · 2. Estimate the Financial Impact of Projects

The data changes constantly. If the decision makers wait for the month or year end to analyze the financial reports, they may lose out on capitalizing the opportunities. Now is the best time for organizations to invest in technology — tools that can help them become agile and gain better control over the accounting data.

Instead of looking at traditional figures and data sources, they can go deeper and integrate multiple data sources at one place. Live dashboards update numbers regularly, allowing users to stay one step ahead of any changes.

Dynamic financial reporting is the future of financial and accounting analytics. Ideally, your financial statements solution will work in tandem with your business intelligence software and ERP to facilitate the sourcing and management of data. Phocas Financial Statements, for example, is an add-on to Phocas business intelligence software and integrates with a variety of top ERP systems such as Infor , Epicor , Microsoft, MYOB , Oracle and SAP.

To find out more about the new financial solution, watch this 35 minute video that includes an explanation from an in-house expert, a quick demo showcasing how it works and some feedback from early adopters.

Empowering businesses with intuitive data analytics, driving informed decisions for growth and profitability. We make people feel good about data. Financial statement analysis: what's changing?

Financial statements are scorecards for businesses, allowing the finance team to interpret and analyze financial performance.

We'll do the data wrangling, you do the analyzing. The sheer volume of data that businesses generate can be overwhelming to simply manage, never mind analyze. Break down data silos and improve business planning. The amount of data generated by finance, sales and operations teams is vast and complex, making it difficult for everyone to work together, plan and make data-driven decisions.

The time spent on extracting data from multiple systems, formatting into spreadsheets and then loading into other programs is excruciating, and the time lost doing it, is taking its toll.

Welcome to the world of data silos. What are your company's most important financial ratios? Companies that make data-driven decisions do better. While this is a common-sense opening line, you might be surprised at the number of businesses that only look at surface-level data like total sales.

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Home Resources Blog. Back to blog. Improve financial decision making with technology 3 mins to read. Affecting financial and core operational decisions Accounting data and financial statements provide key inputs to your managers regarding the current and expected financial performance.

Understanding data better Standalone, any financial statement such as a balance sheet, profit and loss statement or cash flow statement may not show us a clear picture. The future lies in dynamic financial reporting Financial statements contain numbers. Written by Phocas Software. Related blog posts.

So, when making a decision, you need to understand that the potential for regret may cause you to make a sub-optimal choice. A common problem in financial planning is that many people primarily want to know: 1 If they can retire early and 2 How much they need to retire.

These are valid questions, but without determining how long you are going to live and how much you need or want to spend during that time, you can not get to a valid response to the questions for which you really want answers.

The NewRetirement Planner enables you to vary expenses over your lifetime and run scenarios with different longevity ages to help you get reliable answers about your future security.

Want to know when you can retire? First, create a detailed future budget! Getting input from people you trust can help expand your perspective and limit bad decisions.

Just hearing differing opinions can quiet noise that might lead you astray. NewRetirement Advisors offers affordable annual plans that include on demand guidance. The advisor will help you devise long term financial strategies and be there whenever you need support.

Set up a free discovery session with a NewRetirement Certified Financial Planner® to learn more. Automating savings, investing, monthly, and bill paying are all great ideas. It takes the human element of noise out of the equation and enforces consistency.

Human beings have an inherent bias toward short-term benefits. However, your financial decisions are important for today, but also your entire future. It is important to always consider what impact a decision will have on your life right now.

Will you have less or more money this month to spend, for example. However, it is equally important to think about how your financial decisions will impact your future. However, if you are doing it weekly, you could be taking a year away from the life you want in retirement.

Here are 7 tips for connecting with your future self in order to make better money decisions today. A good way to overcome your own emotions is to visualize how someone else would approach the financial decision you are trying to make.

Think about how other parties involved benefit or lose from your choices and what their interests are. Consider how a friend or colleague might approach the decision. This is a particularly good tactic if you are being asked to buy a financial product.

To understand how the salesperson might benefit from the decision, put yourself in their shoes. Strive to understand what they get from your choices.

Their motivations might not align with your interests. Not everything can get analyzed with data. When you can not use an algorithm to make a decision, it is useful to have a set of rules to help you know what to do.

How your money is invested ought to be based on some sort of logic and the actions you take when your asset allocation falls out of balance should be predetermined. So, if the stock market falls quickly and your funds lose value, you should already know what you are going to do if that happens.

This can be the role of an Investment Policy Statement IPS. An IPS is meant to define:. While it is possible to write an IPS on your own, it is usually done with a Certified Financial Planner CFP ®.

Strategizing an investment plan is a great and cost effective way to use a fee-only financial advisor. They can help you figure out the right asset allocation and suggest specific investments.

Set up a free discovery session with a NewRetirement Certified Financial Planner®. For people who want clarity about their choices today and their financial security tomorrow, NewRetirement is a financial planning platform that gives people the ability to discover, design and manage personalized paths to a secure future.

Our goal is to make high quality low cost financial guidance available to everyone. The platform can be co-branded or white labeled for partners. Additionally, the company provides API access to companies who wish to embed planning functionality within their own site. Take financial wellness into your own hands and do it yourself retirement planning: easy, comprehensive, reliable.

Behavioral finance can show you how to be happier, wealthier and achieve a better retirement. Explore 16 rules of thumb for a better future. Here are 98 retirement tips and tricks. Explore useful advice for a healthy, wealthy and happily ever after.

Independence Being able to retain independence — make your own decisions and care for yourself — is a factor that older people rate as being extremely important. Independence is a huge contributing factor to healthy self esteem.

And, research suggests Resilience At NewRetirement, we firmly believe that planning for your future can give you the…. Disclaimer: The content, calculators, and tools on NewRetirement.

com are for informational and educational purposes only and are not investment advice. They apply financial concepts in a general manner and include hypotheticals based on information you provide. For retirement planning, you should consider other assets, income, and investments such as equity in a home or savings accounts in addition to your retirement savings in an IRA or qualified plan such as a k.

Among other things, NewRetirement provides you with a way to estimate your future retirement income needs and assess the impact of different scenarios on retirement income.

NewRetirement Planner and PlannerPlus are tools that individuals can use on their own behalf to help think through their future plans, but should not be acted upon as a complete financial plan. We strongly recommend that you seek the advice of a financial services professional who has a fiduciary relationship with you before making any type of investment or significant financial decision.

NewRetirement strives to keep its information and tools accurate and up to date. The information presented is based on objective analysis, but it may not be the same that you find on a particular financial institution, service provider or specific product's site.

All content, tools, financial products, calculations, estimates, forecasts, comparison shopping products and services are presented without warranty. Build a Retirement Plan.

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Improved financial decision making - Strong financial knowledge and decision-making skills help people weigh options and make informed choices for their financial situations, such as deciding how There is a growing awareness of the importance of successful financial decision making (FDM) to individuals, organizations, and society 13 Ways to Improve Your Financial Decision Making · 1. Maintain a Holistic Financial Plan · 2. Slow Down, Give Yourself Time to Be Rational · 3 5 Ways Managers Can Use Finance to Make Better Decisions · 1. Perform Financial Statement Analysis · 2. Estimate the Financial Impact of Projects

Now is the best time for organizations to invest in technology — tools that can help them become agile and gain better control over the accounting data. Instead of looking at traditional figures and data sources, they can go deeper and integrate multiple data sources at one place.

Live dashboards update numbers regularly, allowing users to stay one step ahead of any changes. Dynamic financial reporting is the future of financial and accounting analytics. Ideally, your financial statements solution will work in tandem with your business intelligence software and ERP to facilitate the sourcing and management of data.

Phocas Financial Statements, for example, is an add-on to Phocas business intelligence software and integrates with a variety of top ERP systems such as Infor , Epicor , Microsoft, MYOB , Oracle and SAP.

To find out more about the new financial solution, watch this 35 minute video that includes an explanation from an in-house expert, a quick demo showcasing how it works and some feedback from early adopters.

Empowering businesses with intuitive data analytics, driving informed decisions for growth and profitability. We make people feel good about data. Financial statement analysis: what's changing?

Financial statements are scorecards for businesses, allowing the finance team to interpret and analyze financial performance. We'll do the data wrangling, you do the analyzing. The sheer volume of data that businesses generate can be overwhelming to simply manage, never mind analyze.

Break down data silos and improve business planning. The amount of data generated by finance, sales and operations teams is vast and complex, making it difficult for everyone to work together, plan and make data-driven decisions.

The time spent on extracting data from multiple systems, formatting into spreadsheets and then loading into other programs is excruciating, and the time lost doing it, is taking its toll.

Welcome to the world of data silos. What are your company's most important financial ratios? Companies that make data-driven decisions do better.

While this is a common-sense opening line, you might be surprised at the number of businesses that only look at surface-level data like total sales.

By clicking "Accept all", you agree to the storing of cookies on your device to enhance site navigation, analyze site usage and assist in our marketing efforts. When you visit any website, it may store or retrieve information in your browser, mostly in the form of cookies.

This information might be about you, your preferences or your device and the primary purpose is to ensure the website functions as you expect it to. While this information typically doesn't directly identify you, it contributes to a more personalized browsing experience.

Because we respect your right to privacy, we provide the option to control certain types of cookies. Click on the different category headings below to learn more and modify our default settings according to your preferences. However, blocking some types of cookies might impact your experience of the website and the services we are able to offer.

More information. Home Resources Blog. Back to blog. Improve financial decision making with technology 3 mins to read. Affecting financial and core operational decisions Accounting data and financial statements provide key inputs to your managers regarding the current and expected financial performance.

Understanding data better Standalone, any financial statement such as a balance sheet, profit and loss statement or cash flow statement may not show us a clear picture.

The future lies in dynamic financial reporting Financial statements contain numbers. Written by Phocas Software. Related blog posts. Read more. Break down data silos and improve business planning The amount of data generated by finance, sales and operations teams is vast and complex, making it difficult for everyone to work together, plan and make data-driven decisions.

This includes data cleaning, validation, and structuring to ensure that the information is accurate and consistent.

Data quality is paramount, as any inaccuracies can significantly impact the accuracy of personalized pension plan calculations. Furthermore, we have implemented real-time data feeds from mentioned sources, enabling us to provide users with the most current financial information available.

This real-time aspect is particularly important in the financial domain, where market conditions can change rapidly and we ensure that our configurator offers users access to real-time, high-quality financial data.

This, in turn, empowers users to make informed decisions when planning their pensions, ultimately leading to more secure financial futures. To determine personalized pension plans, it is necessary to obtain various parameter values, such as income, expenses, free assets, and inflation rates, as explained above.

Because pension payments in Denmark are directly connected to income and inflation rates, it is important to estimate the main source of income and the salary for the upcoming years to better calculate personalized pension plans. We develop a formula for estimating salary, which is a necessary element in the pension calculation model, in Eq.

As shown in Eq. The Danish Council of Return Expectations reports three standard investment plans for pension savings and the corresponding investment amounts Council for Return Expectations, The three plans include i a low-risk plan, ii a high-risk plan, and iii a medium-risk plan.

Being consistent with practice, we assume the risks decrease in time. Affected by risks, the annual return rates are different from one year to another. We further model the growth of annual return rates in Eq.

In the equation, IRRate denotes the initial average annual return rate, which can be calculated based on annual returns in the past; RRate n is the return rate at year n; Std represents the standard deviation of the annual return rates from the past.

The equation shows how the annual return rate grows in time when the annual return rates follow a normal distribution. Assume a user has an initial investment value, denoted as Investment 0. P is the ratio of the salary paid to the pension investment. Regardless of the pension plans, taxes will be deducted when an individual requests for the pension savings to be paid out.

Thus, it is very important to consider taxes in personalizing pension plans. Taxation in Denmark has three main categories, including labor market contribution tax Arbejdsmarked-bidrag, or AM , state tax which is divided into bottom tax and top tax , and communal tax , as shown in Table 1.

For an annual income higher than All these tax rates are summarized in Table 1. Figure 2 summarizes various configurator elements, including inputs, outputs, system functions, and interactions.

In line with the system requirements identified earlier, the inputs include, e. Based on the inputs, various outputs can be generated, including an overview of incomes, an overview of expenses, an overview of investments and assets, an overview of retirement preferences e.

As shown in Fig. For example, after calculating pension investment values based on the initial inputs, the configurator may ask the user to modify certain inputs e. Moreover, based on a personalized pension plan selected by a user, the databases will be updated. With the updated databases, the configurator, based on new inputs, calculates and generates different types of outputs for the user to make decisions.

The three tiers are the server, client, and data tiers. The client tier serves to get user inputs and display the results, while the server tier carries out data operations and processing. In the client tier, after logging into the personalized financial configurator in his browser by providing an ID and password, a user needs to launch his pension project.

The user will be asked to make necessary modifications if the input data is conflicting, incomplete, or invalid. Upon receiving consistent and valid inputs, the HTTP Hypertext Transfer Protocol server carries out calculations and optimizations and generates diverse outputs.

Each time when a user makes a decision in a personalized pension plan, the databases are updated. The new data will be used in the future to generate personalized pension plan recommendations. The client tier plays a crucial role in ensuring a user-friendly experience and facilitating efficient data exchange between users and the server tier.

User authentication: users access the configurator through their web browsers by providing their unique ID and password. This authentication process ensures that only authorized users can access and utilize the system. Input validation: the client tier conducts preliminary checks on user inputs to identify potential issues, such as missing or improperly formatted data.

Users are prompted to correct any discrepancies before proceeding. Display of results: once the server tier completes its calculations and optimizations, the client tier is responsible for presenting the results to the user.

In the data tier, the databases host all the data. The data tier serves as the repository for all the data used by the personalized financial configurator.

It hosts a comprehensive database that stores essential information, including user profiles, financial parameters, and historical data. This centralized storage ensures that the configurator has access to the necessary information for calculations and optimizations.

Data retrieval: when the server tier requires specific data for calculations, it retrieves this information from the data tier. This retrieval process ensures that the configurator operates with up-to-date and accurate data.

At the core of our architecture lies the server tier. This tier is responsible for handling all data operations and processing tasks. When a user initiates a pension project, the server tier performs several critical functions.

In cases where conflicts, incompleteness, or invalid data are detected, the server tier prompts the user to make the necessary adjustments.

Calculation and optimization: upon receiving consistent and valid inputs, the server tier proceeds to execute complex calculations and optimizations. Each time a user makes a decision within their personalized pension plan, the databases are promptly updated to reflect these changes.

This dynamic updating ensures that the configurator operates with the most current and accurate data. By following the above three-tier distributed architecture, we develop the personalized financial configurator based on a well-established configuration system shell, called Tacton, a leading Configure, Price, Quote CPQ SaaS partner for design to sales automation for industrial manufacturers.

The configurator is developed in such a way that the available financial systems, such as banking applications, NemID, national eID a secure two independent authentication factors as a Scandinavia-specific digital signature used to log on to public online banking and many other digital services , and local pension systems can be easily integrated with it.

This is achieved via the Application Program Interface API. For illustrative simplicity, Fig. In Zone 1, different input parameters see Step 3 are added, while in Zone 2, various attributes for each parameter are added.

For example, the parameter: Children has two properties: Name and Number of instances. Name is the parameter name children in this example and the Number of instances is the number of children of a user. to show or hide the next input fields regarding children based on the number of children inserted by the user.

Constraints are defined in Zone 3 to model the relationships among attribute values describing the same or different parameters.

This constraint indicates that the total amount of the money received for all children is achieved by summing up the amount for each child. Some constraints restrict the display of inputs. The current inputs primarily pertain to salary levels and investments simple for users and guide users through the process and provide options that are easy to understand and independent of complex financial jargon.

This integration will enable us to automatically retrieve a significant portion of user-specific information, reducing the need for manual inputs to a minimum.

This enhancement will further streamline the user experience and provide even more tailored financial guidance. Inflation is a dynamic force that profoundly influences the real value of assets and income over time. Within our configurator, users are prompted to input their assumed inflation rate, which serves as a baseline for calculations.

To enhance precision, users have the option to adjust the inflation rate based on an annual basis. This level of flexibility enables users to simulate a multitude of inflation scenarios, reflecting real-world volatility.

For instance, users can model conservative scenarios with low inflation rates, or they can explore the potential consequences of high inflation environments. Moreover, our configurator takes historical inflation data into account to provide users with insights and guidance on selecting an appropriate inflation rate.

By leveraging a comprehensive dataset of historical inflation rates, users can make informed decisions based on past trends and economic realities. Investment choices play a pivotal role in shaping the growth of financial assets and, consequently, the adequacy of retirement plans.

We derive this model from historical data and standard deviations, enabling us to simulate the impact of various investment strategies realistically. Furthermore, our configurator factors in the decreasing risks associated with longer investment horizons, mirroring established financial principles.

This dynamic approach to modeling investment returns reflects the complexities of the real financial world, allowing users to make well-informed investment decisions. Taxes are a critical facet of personalized financial planning, significantly affecting the final outcome of retirement plans.

Our system meticulously considers the Danish tax landscape, systematically integrated into calculations to ensure that the personalized financial plans accurately reflect the tax implications of different financial scenarios.

For instance, users can explore how tax obligations evolve as their income and assets grow or as they transition into retirement. The development of the personalized financial configurator is underpinned by a robust commitment to a user-centered approach see Appendix.

We recognize the paramount importance of aligning the configurator with the unique needs, preferences, and expectations of our users. To achieve this, we initiated the design phase by conducting in-depth user research.

This involved engaging with potential users 8 domain experts and 21 end-users through surveys, interviews, and usability testing sessions. These interactions provided invaluable insights into the financial pain points, goals, and expectations of our target audience.

It allowed us to uncover specific challenges individuals face in financial planning within the Danish context and identify areas where personalized assistance could be most beneficial. Furthermore, a user-centered design approach guided the creation of the configurator's interface. We prioritized simplicity and clarity, presenting financial information in an easily digestible format.

User testing sessions were conducted iteratively to gather feedback and refine the interface to enhance usability. Additionally, we integrated features for user feedback and continuous improvement directly within the configurator.

The findings of this study bring to light a pioneering advancement in the realm of personalized financial planning. The personalized financial configurator, as developed and demonstrated, offers a level of tailored financial guidance and real-time planning that is, in many ways, unprecedented.

It marks a significant departure from traditional financial planning tools, which often provide generic advice and lack the adaptability to address the evolving financial situations of individuals.

We acknowledge the importance of considering generational differences when tailoring the personalized financial configurator to a broader user base.

To achieve this, we conduct in-depth research profiling distinct generational characteristics, adapt user journeys to align with generational profiles, enhance educational content, establish feedback loops with users from various age groups, and adopt an agile development approach see Appendix.

Firstly, we intend to conduct comprehensive research to profile the distinct financial behaviors, preferences, and knowledge levels associated with different generations. Armed with these insights, the configurator can adapt its user interface and educational content to align with generational profiles, ensuring that the information presented resonates effectively with each age group.

Moreover, the incorporation of feedback mechanisms and user testing with representatives from various generations will allow us to fine-tune the configurator continuously. When using the personalized financial configurator, it is compulsory for a user to provide the basic information e.

Based on the selection results, the configurator displays a new page requesting specific information from the user or summarizing the input information provided by the user. For example, Fig. If certain information in the summary is wrong, the user can go back to the relevant page and make necessary modifications.

If the information in the summary is all correct, the user can click on the Ok button at the top right corner, as shown in Fig.

Graphs and recommendations for personalized pension plans. a An investment potential line graph. b A financial asset changing graph. c A graph showing investment potentials for retirement. Subsequently, the pension calculation model carries out calculation and optimization, and the configurator output the results.

These graphs include an investment potential line graph Graph a , a financial asset changing graph Graph b , and a graph showing investment potentials for retirement Graph c. The recommendations for personalized pension plans are shown in the left panel of the figure. The different graphs and recommendations give the user an overview of her future economic situation.

Such information can better educate the user, which, in turn, enables him to make optimal decisions in a pension plan personalized for him. Also calculated are the minimum and maximum savings: 2.

With the potential saving results, the configurator recommends suitable retirement ages, i. In another example, based on Graph a, the user may select a high-risk investment plan, instead of a medium-risk one, as shown in the right panel in the figure.

From a theoretical perspective, our findings underscore the importance of a user-centric approach to financial technology development. It empowers individuals to make informed decisions aligned with their evolving financial situations, thus addressing a critical gap in the literature.

A notable theoretical contribution of this research lies in the development of dynamic financial planning models. Traditional financial models often lack adaptability to changing financial environments, which this paper addresses.

This model can guide future research on dynamic financial planning methodologies. The personalized financial configurator offers real-time, personalized recommendations for pension planning, investment, and taxation. Moreover, users of the configurator experience tangible practical benefits in terms of time and effort savings.

It ensures that individuals with varying levels of financial literacy can benefit from the tool. By bridging the gap between financial complexity and user comprehension, it aligns with the practical goal of expanding financial services to a broader demographic.

Users not only receive personalized recommendations but also gain a deeper understanding of the forces shaping their financial plans.

Caused by the variability in financial literacy as well as the complexity and limitations of available commercial financial systems, many individuals have great difficulty understanding their economic life cycles, thus being unable to make wise financial decisions. To contribute to both literature and practice, in this study, we developed a personalized financial configurator to facilitate users to make optimal pension decisions.

It was developed by capitalizing on the configuration principles widely applied in other industries e. As demonstrated through its applications, the personalized financial configurator can provide rich information about, e. Such information is presented in different forms, such as Excel files and graphs.

With the recommendations and rich financial information, the user can make wise pension decisions, e. While our personalized financial configurator holds substantial promise, it is important to recognize and address potential limitations and challenges.

One potential limitation lies in data accuracy and reliability, as the configurator relies on user-provided inputs and external financial data sources. To mitigate this, we are actively exploring partnerships with financial institutions and government agencies to enhance data accuracy and timeliness.

Additionally, cybersecurity concerns and data privacy issues are paramount when the system is implemented, and we have to be committed to robust security measures and compliance with relevant regulations.

Furthermore, we acknowledge the possibility of generational and demographic biases in our algorithms and decision recommendations, and we are dedicated to refining our models to minimize such biases. As we continue to develop the configurator, ongoing user testing and feedback collection will be pivotal in identifying and resolving any unforeseen challenges.

Though the personalized financial configurator can facilitate users to make some wise financial decisions, they are limited to pension plans, which opens potential avenues for future research. In particular, further studies need to expand the financial analysis within various areas, such as incomes, housing assets, and investments in the market, to ensure the accuracy of the life cycle analysis.

These areas need to be developed concurrently to ensure their interrelationships are considered thoroughly. Moreover, in this study, we targeted Danish users who are closer to the retirement age.

Hence, improving the configurator by including younger individuals as potential users might be beneficial. Hence, young users can learn the impacts of investment decisions on their economic life cycles earlier.

Considering the diverse levels of knowledge and varying goals among different generations, future research may examine how these differences can be addressed and integrated into the improved configurator.

It is equally important to investigate how the various outputs can be better presented so that the users of different generations can easily understand the large volumes of financial information.

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