# Digital Identity Crisis and Crypto Investment Uncertainty in the AI Era: How Digital Identity Issues Influence Systemic Risks in the Crypto Market

## Project Abstract

The rise of artificial intelligence (AI) has intensified the Digital Identity Crisis, raising concerns about security, trust, and financial stability in the crypto market. This study investigates how identity-related risks contribute to uncertainty in crypto investments and systemic market risks. Using a mixed-method approach, the study will analyze survey data, construct a Digital Identity Crisis Uncertainty Index using Google Trends, and apply econometric modeling to assess how the Digital Identity Crisis impacts systemic risks and participation in digital financial transactions. Additionally, the study will propose a policy framework to mitigate the risks associated with the Digital Identity Crisis and enhance trust in AI-driven financial systems. The findings will provide guidance for policymakers, investors, and regulators on how to navigate the risks associated with the digital identity crisis in the crypto market.

## Objectives

The rapid advancement of artificial intelligence (AI) and digital financial ecosystems has ushered in a new era of opportunities and risks (Ashta & Herrmann, 2021). One of the most pressing concerns in this landscape is the issue of Digital Identity Crisis (DIC), where the increasing reliance on AI-driven identity verification systems raises significant questions about security, privacy, and trust (Knight & Saxby, 2014). As digital identities become more vulnerable to fraud, misrepresentation, and deepfake manipulations, these risks extend beyond personal security to the broader financial sector—particularly in the highly volatile crypto market (Satchell et al., 2011).

Crypto markets, already characterized by speculative trading and price instability, are further destabilized by uncertainties surrounding digital identities. Investors face growing concerns over identity theft, fraudulent transactions, and the complexity of AI-driven identity verification processes, leading to systemic risks in crypto investments. Behavioral finance theories suggest that psychological and emotional factors can also amplify market volatility, influence investment decisions through cognitive biases, and contribute to herd behavior (Almansour et al., 2023; AsleBagh et al., 2024; Raj, 2025). Moreover, the lack of standardized digital identity regulations across different jurisdictions exacerbates the problem, making it difficult for investors to assess and manage risk effectively (Gozman & Willcocks, 2019).

With this grant, we aim to advance the understanding of how DIC and crypto investment uncertainty interact to shape trust, risk perception, and financial decision-making in an increasingly AI-driven era. Drawing on an integrated theoretical framework that combines Prospect theory and Trust theory, we seek to uncover how individuals evaluate risks in AI-driven identity systems and their influence on digital financial transactions. Additionally, using Behavioral Finance and Herding Theory, we will investigate how cognitive biases and herd behavior shape uncertainty in crypto investments. Furthermore, we will explore whether identity-related risks amplify market volatility through the lens of Information Asymmetry Theory. We also aim to construct a Digital Identity Crisis Uncertainty Index using Google Trends data to quantify public concerns across different regions. And through econometric analysis, we will evaluate how fluctuations in digital identity concerns impact systemic risks in the crypto market. Finally, leveraging insights from focus groups and interviews, we aim to develop a policy framework to mitigate digital identity risks and strengthen trust in AI-driven financial systems.

Specifically, this study seeks to achieve the following objectives:

* To evaluate the perception of Digital Identity Crisis and analyze how it impacts participation in digital financial transactions.
* To analyze crypto investment uncertainty and how it is influenced by cognitive biases, overreaction to market fluctuations, and herd behavior in the crypto market.
* To examine the impact of the Digital Identity Crisis on crypto investment uncertainty.
* To develop a country-level Digital Identity Crisis Index using Google Trend data to measure public attention to digital identity concerns across different regions
* To investigate the influence of Digital Identity Crisis attention on systemic risks in crypto markets.
* To propose a policy framework to mitigate Digital Identity Crisis risks and enhance trust in AI-driven financial systems.

Success of this project will be measured by the construction of a Digital Identity Crisis Uncertainty Index, development of empirical models, actionable policy recommendations, and their potential adoption by regulators and industry stakeholders, contributing to a more secure and resilient digital financial ecosystem.

## Outcomes

This project will benefit benefits the greater Ethereum ecosystem by addressing critical challenges related to digital identity security, trust, and investment uncertainty, which are fundamental to the long-term adoption and stability of decentralized finance (DeFi) and blockchain-based transactions. As Ethereum continues to evolve as a leading platform for smart contracts, digital assets, and decentralized identity solutions, ensuring robust trust mechanisms is essential for user confidence and financial security. By analyzing the perception of Digital Identity Crisis through the lens of Prospect Theory and Trust Theory, this project will provide insights into how individuals assess risks and trust AI-driven identity systems, influencing their willingness to engage in Ethereum-based financial activities. Understanding how digital identity concerns shape investor behavior in the crypto market using Behavioral Finance and Herding Theory will further help identify patterns of market volatility, reducing the likelihood of panic-driven selloffs and speculative bubbles.
Additionally, the development of a Digital Identity Crisis Uncertainty Index using Google Trends data will provide a real-time measure of identity-related concerns at a country level, offering valuable insights into regional variations in trust and adoption of Ethereum-based solutions. This can aid developers, policymakers, and investors in identifying key market risks and implementing targeted strategies to enhance security and reduce systemic risks. By employing econometric modeling to assess how digital identity concerns impact crypto market stability, this project will offer evidence-based recommendations for mitigating identity-related risks that could otherwise hinder Ethereum’s broader adoption. Furthermore, the proposed policy framework, based on focus group insights, will contribute to regulatory discussions and technological advancements in decentralized identity verification, helping Ethereum become a more secure, transparent, and user-friendly ecosystem. Ultimately, by addressing identity trust issues and investment uncertainty, this research will enhance Ethereum’s credibility, promote wider adoption, and foster a more resilient and sustainable blockchain ecosystem.

## Grant Scope

This research explores the intersection of digital identity crises and cryptocurrency investment uncertainty, focusing on their impact on trust, risk perception, and financial decision-making within the Ethereum ecosystem in Ghana. Ghana serves as an ideal case study due to its ongoing efforts, alongside a few other African nations like Kenya, to digitalize its data systems. For instance, Ghana has modernized its financial sector through the Ghana Interbank Payment and Settlement Systems (GhIPSS), which enables instant transfers between banks. Additionally, the mobile money interoperability system introduced in the country allows users to transfer funds seamlessly between mobile wallets and bank accounts, as well as across different mobile networks. More recently, Ghana introduced the Ghanacard, a secure, multi-purpose biometric identity card designed for verification and authentication in both public and private sector transactions (Thiel, 2020). These advancements have significantly increased the volume of data that can be processed, improved accessibility, and enhanced the speed and accuracy of financial transactions (Breckenridge, 2019; UNDP, 2016). However, as digital identity systems evolve, Ghana—like several other African countries—has experienced data breaches, exposing individuals to identity theft and financial risks (Apiors & Suzuki, 2022; Musoni et al., 2023). **In light of these challenges, this study examines the risks and uncertainties associated with digital identity crises in Ghana and their implications for cryptocurrency adoption and financial trust**.

Ghana, the case study of this article, pursues a three-tier strategy for the digitization of data, layering the identification of financial transactions (through the digitization and interoperability of financial services, including card-based and mobile-money transactions) and the identification of property (among others, in the form of an app-based numeric postal address system, a planned GIS-based property registration at the level of local government, and an electronic tax number) onto new modalities of identifying inhabitants of the West African country and its diaspora, through a biometrically authenticated personal identification number (PIN). In his address at the African Open Data Conference in Accra, Ghana’s former President, Nana Akufo-Addo, reaffirmed his commitment to the national identification agenda. He cited Kenya and Rwanda’s integrated population data systems as models and linked his administration’s central vision of a "Ghana Beyond Aid" to the need for accurate and timely data. The interoperability of Ghana’s scattered population registers through new biometric ‘data journeys’ (Lemov, 2017 ) had become the central political avenue to harnessing the country’s data potential.
Drawing survey data, this study will investigate how individuals assess risks and trust in AI-driven identity systems using Prospect Theory and Trust Theory, analyzing how these factors influence engagement in Ethereum-based financial transactions. Additionally, it will examine the role of Behavioral Finance and Herding Theory in shaping investment uncertainty in the crypto market, identifying how cognitive biases, market overreactions, and herd behavior contribute to volatility. A key aspect of this research is determining whether digital identity crises exacerbate investment uncertainty, using Behavioral Finance and Information Asymmetry Theory to explore how identity-related risks and trust deficits affect investor confidence and Ethereum market stability.

To quantify public concerns, this study will develop a Digital Identity Crisis Uncertainty Index using Google Trends data, providing a real-time measure of digital identity-related issues at a country level. This index will help assess the prevalence and intensity of digital identity concerns across different regions and their correlation with fluctuations in Ethereum market dynamics. The research will also employ econometric analysis and volatility modeling to investigate how shifts in digital identity concerns influence systemic risks in the crypto market, offering valuable insights into the interconnectedness of identity security and financial stability.
The expected output of this project includes a comprehensive empirical analysis detailing the relationship between digital identity crises and investment uncertainty, a publicly available Digital Identity Crisis Uncertainty Index to track global trends, and econometric models that quantify the impact of identity-related risks on Ethereum’s market behavior. Additionally, the study will produce a policy framework based on focus group interviews, providing regulatory and technological recommendations to enhance identity security and reduce investment uncertainty within Ethereum’s decentralized ecosystem. By addressing these challenges, this research aims to contribute to Ethereum’s long-term adoption, stability, and resilience by improving trust in its digital financial infrastructure.

## Related Work

Both digital identity and cryptocurrency investment uncertainty present significant challenges in modern digital economies, driven by technological advancements, security risks, and behavioral factors. Digital identity is a complex and evolving concept with far-reaching implications for security, privacy, exclusion, and governance. Scholars have examined its role in human development, where Masiero and Bailur (2020) highlight both its potential benefits and risks, calling for deeper research within the ICT4D framework. However, digital identity can also lead to exclusion, as Zhu et al. (2024) illustrate through elderly individuals in China’s healthcare system, who face both practical and psychological challenges due to digitalization. Similarly, Fehe (2019) explores online identity management, revealing that while individuals consciously control much of their digital presence, a significant portion remains vulnerable to risks like identity theft.

The legal and ethical dimensions of digital identity have gained prominence, particularly post-pandemic, with Beduschi (2021) advocating for frameworks that balance data privacy and human rights. Technological solutions such as verifiable credentials offer a more secure approach, as discussed by Sedlmeir et al. (2021), though privacy concerns persist. Security risks are further emphasized by Barella et al. (2022), who argue that ineffective identity management can compromise both individual and organizational security. Meanwhile, Jain et al. (2024) warn of AI-driven disinformation campaigns exploiting weak identity authentication systems, raising concerns about centralized governance and surveillance. Together, these studies reveal that while digital identity presents opportunities for efficiency and security, it also poses significant risks, requiring a balanced approach that prioritizes privacy, inclusivity, and ethical governance.

Cryptocurrency investment uncertainty stems from a lack of traditional financial fundamentals, speculative market behavior, and macroeconomic influences. Liu and Tsyvinski (2021) highlight the role of crypto-specific factors such as momentum and investor attention in predicting prices, while macroeconomic variables play a lesser role. Similarly, Dai et al. (2022) emphasize that cryptocurrency uncertainty, rather than general economic policy uncertainty, better explains co-crashes between crypto and equity markets. Behavioral biases further contribute to market volatility, with studies identifying FOMO, pump-and-dump schemes (Baur & Dimpfl, 2018), and herding behavior (Gurdgiev & O’Loughlin, 2020). Bouri et al. (2019) find that during periods of high economic uncertainty, crypto investors tend to exhibit overconfidence, reinforcing speculative trends.

The speculative nature of cryptocurrencies is further reinforced by their lack of intrinsic value, as investment returns rely solely on capital gains rather than cash flows (Berentsen & Schar, 2018). The shift from technological utility to speculative interest has amplified volatility, with media-driven hype influencing investor sentiment (Kharpal, 2018). Corbet and Gurdgiev (2018) note that market cycles are heavily driven by waves of speculative investment, as seen in the rapid rise and subsequent crash of the market in 2017–2018. These factors collectively indicate that cryptocurrency markets remain highly unpredictable, influenced by investor psychology, speculative behavior, and fluctuating external conditions.
Existing literature highlights the security, privacy, and exclusion risks of digital identity but lacks a comprehensive understanding of how Digital Identity Crisis interacts with financial markets, particularly cryptocurrency investment uncertainty. While studies explore digital identity risks (Masiero & Bailur, 2020; Beduschi, 2021) and AI-driven threats (Jain et al., 2024), they do not quantitatively assess how public concerns over digital identity influence investment behaviors and market stability. Additionally, research on crypto investment uncertainty primarily focuses on speculative behavior and market cycles (Liu & Tsyvinski, 2021; Bouri et al., 2019) but does not account for emerging systemic risks stemming from identity-based disinformation and AI-driven fraud.

Our research seeks to bridge these gaps by quantifying the relationship between DIC and CIU through a behavioral finance perspective, integrating both qualitative and quantitative approaches. We will first assess public perceptions of DIC and its influence on crypto investment uncertainty through survey data, capturing insights into investor sentiment and risk perception. Next, we will construct a Digital Identity Crisis Uncertainty Index (DICUI) using Google Trends data to measure country-level variations in digital identity concerns and assess how shifts in identity-related uncertainty affect the crypto market. To establish empirical relationships, we will employ econometric modeling techniques to analyze the impact of DIC on crypto market systemic risks, identifying potential spillover effects and volatility patterns. Finally, through expert focus group discussions, we will develop a policy framework to address the risks of DIC in AI-driven financial systems, ensuring that technological advancements in identity authentication do not compromise market stability or investor confidence.

## Project Team

Our research team consists of the following members:

* **Dr. Emmanuel Joel Aikins Abakah**, Principal Investigator from the Department of Finance, University of Ghana Business School, Ghana & The University of the Witwatersrand, Johannesburg, South Africa, will contribute more than 60 hours per month to the project.
* **Dr Mohammad Abdullah**, co-Principal Investigator from University of Southampton Malaysia, Southampton Malaysia Business School, will also allocate over 40 hours per month to the research.
* **Dr. Freeman Brobbey Owusu**, co-Principal Investigator from the Loughborough University, Loughborough Business School’s Department of Accounting and Finance, will contribute more than 40 hours per month to the project.

## Background

Our team has the combined expertise to achieve the project objectives:

* **Dr. Emmanuel Joel Aikins Abakah** is a data driven finance academic and youth trainer with a growing reputation in the areas of digital finance, financial data science & analytics, empirical finance, financial education, corporate finance, financial economics and applied finance. I also have interest in pro-poor programs aimed at training and developing the next generation of young African entrepreneurs, inclusive growth, sustainable development, inequality and climate change issues. He holds a Ph.D. in Finance degree from the University of Adelaide, Australia, MPhil in Finance from University of Ghana, Ghana and a BSc in Statistics with Computing from University of Cape Coast, Ghana. He is a Senior Lecturer in Finance at the University of Ghana Business School, Ghana, Postdoc Fellow at the University of Witwatersrand, South Africa, Research Fellow at the Faculty of Business and Management, University Sultan Zainal, Malaysia and Principal Consultant at African Review of Economic and Finance (AREF) Consult. He also consults for industry, government institutions and MSMEs. His partial collaborator include Bank of Ghana-Ghana, Ethereum Foundation, Switzerland, Development of Ghana-Ghana, PwC, KPMG etc. His publication records of over 80 peer-reviewed published articles in the broad field of finance and economics in high quality ABDC ranked A*/A/B scholarly journal cements his position as a data driven academic whose research tends to cross the boundaries of narrowly defined fields as he constantly looks for promising ideas from several perspectives.

Weblinks

UGBS Profile: http://ugbs.ug.edu.gh/faculty/emmanuel-joel-aikins-abakah
Google Scholar:https://scholar.google.com.au/citations?hl=en&user=0baKC5wAAAAJ&view_op=list_works&sortby=pubdate

Selected Research Publications:
https://www.sciencedirect.com/science/article/pii/S0275531925000406
https://www.emerald.com/insight/content/doi/10.1108/jrf-04-2024-0095/full/html
https://www.sciencedirect.com/science/article/pii/S1044028324000619
https://www.tandfonline.com/doi/full/10.1080/00036846.2023.2167921 https://www.sciencedirect.com/science/article/pii/S0140988322006272 https://onlinelibrary.wiley.com/doi/full/10.1111/irfi.12393 https://www.sciencedirect.com/science/article/pii/S0040162520312087 https://www.sciencedirect.com/science/article/pii/S1059056020301489

* **Mohammad Abdullah**:

Dr. Mohammad Abdullah is working as Assistant Professor of Finance & FinTech at University of Southampton Malaysia. He completed his Ph.D. in finance from Universiti Sultan Zainal Abidin, Malaysia. He holds an MBA and BBA degree in Finance from Independent University, Bangladesh (IUB). Prior to his current position, he worked at IUB, and held various positions in the banking sector of Bangladesh. Dr. Abdullah has published several scholarly articles on emerging financial issues in different international journals and possesses expertise in econometrics modeling, machine learning, sentiment analysis, deep learning, and big data analytics. His research interests include asset pricing, machine learning in finance, blockchain market, cryptocurrency, FinTech, etc.

Profile Link: https://sites.google.com/view/abdullahm/

Related article links:
https://www.sciencedirect.com/science/article/pii/S1044028325000092?via%3Dihub
https://www.sciencedirect.com/science/article/pii/S0275531925000406?via%3Dihub
https://www.sciencedirect.com/science/article/pii/S1544612324013011?via%3Dihub
https://www.sciencedirect.com/science/article/pii/S1057521923001588?via%3Dihub
https://www.sciencedirect.com/science/article/pii/S0957417424006067?via%3Dihub
https://doi.org/10.1016/j.intfin.2022.101691

* **Dr. Freeman Brobbey Owusu**:

Dr. Freeman Brobbey Owusu is an Assistant Professor of Accounting and Finance at Loughborough Business School. Prior to this role, he was a Senior Lecturer at Nottingham Business School, Nottingham Trent University, and has also held an academic position at Sheffield Hallam University. He holds a PhD from the University of Nottingham, along with an MPhil in Finance and a BSc in Accounting from the University of Ghana. He is a member of the Association of Certified Chartered Accountants (ACCA) and a Fellow of the Higher Education Academy (FHEA). Dr Owusu specializes in corporate reporting, FinTech, and banking. He has expertise in data analysis using Stata and applying advanced statistical techniques to financial data.

Profile Link:https://www.lboro.ac.uk/schools/business-school/our-people/freeman-brobbey-owusu/

Google scholar: https://scholar.google.com/citations?user=dRxhWqkAAAAJ&hl=en

Related article links:
https://doi.org/10.1016/j.frl.2025.107204
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ijfe.1860
https://link.springer.com/article/10.1007/s10644-015-9174-6
https://www.emerald.com/insight/content/doi/10.1108/sef-02-2023-0070/full/html
https://www.emerald.com/insight/content/doi/10.1108/jfra-07-2023-0425/full/html

## Methodology

This study will employ a mixed-method approach, integrating primary data from surveys and focus groups with secondary data from Google Trends, econometric modeling, and market analysis. The research aims to comprehensively examine the relationship between Digital Identity Crisis (DIC), crypto investment uncertainty (CIU), and systemic risks in the crypto market. To assess individuals' perceptions of DIC through the lens of Prospect Theory and Trust Theory, a structured survey will be conducted targeting crypto investors and digital financial service users. This survey will measure risk perception, loss aversion, and trust in AI-driven identity verification through a 5-point Likert scale. Using stratified random sampling, responses will be collected via physical survey across the 16 regions in Ghana. Overall, a total of 500-600 respondents comprising individuals, firms and regulators will be used. The data will be analyzed using descriptive statistics, factor analysis, and regression modeling to determine how trust and risk perception influence engagement in digital financial transactions.

To explore crypto investment uncertainty through Behavioral Finance and Herding Theory, the study will employ survey research. The survey will assess investors’ risk tolerance, overreaction to price volatility, and susceptibility to herd behavior. A combination of correlation analysis, behavioral segmentation, and regression modeling will be used to examine whether psychological biases significantly contribute to uncertainty in crypto investments.

To analyze the impact of DIC on crypto investment uncertainty using Behavioral Finance and Information Asymmetry Theory, survey data will be combined with Structural equation modelling. Survey respondents will indicate whether concerns about fraud, AI-driven identity theft, and data breaches influence their willingness to invest in crypto. The study will construct an index based on Likert-scale responses measuring DIC perception. A multiple regression model will then be applied, with crypto investment uncertainty as the dependent variable and DIC perception indicator as independent variables. Control variables such as investor experience, risk appetite, and trust in digital platforms will be incorporated to refine the analysis.

To measure public attention to DIC at the country level, this study will construct a Digital Identity Crisis Uncertainty Index (DICUI) using Google Trends data. Search queries related to digital identity theft, AI fraud, online identity risks, and blockchain security will be collected from Google Trends at the country level. This data will be normalized and aggregated to form the DICUI, allowing for cross-regional comparisons. A time-series analysis will track fluctuations in digital identity concerns and their correlation with major crypto market events, such as security breaches and regulatory developments. The findings will be visualized through heatmaps and trend charts, illustrating global variations in DIC attention.

To investigate whether fluctuations in DIC attention contribute to systemic risks in the crypto market, this study will employ advanced econometric modeling techniques. The DICUI will serve as the key independent variable, while market risk indicators such as price volatility, trading volume, and market capitalization fluctuations will be retrieved from financial databases like CoinGecko, Binance, and CryptoCompare. A Vector Autoregression (VAR) model will assess how shocks in DICUI influence crypto market risks over time. A Granger Causality Test will determine whether DIC concerns can predict crypto market instability. Additionally, sentiment analysis of crypto news and social media discussions will be incorporated to capture qualitative factors affecting market perceptions.

To develop policy recommendations for mitigating DIC risks in the AI-driven financial landscape, this study will conduct focus group discussions with around 30 experts from multiple sectors. Participants will include blockchain developers, cybersecurity specialists, regulators, policymakers, crypto investors, and fintech professionals. The discussions will cover strategies for enhancing identity security in AI-driven ecosystems, regulatory policies for mitigating DIC risks, and investor education programs to improve risk awareness in crypto markets. Thematic analysis will be conducted to extract key insights, and a policy framework will be synthesized from expert recommendations. The final output will provide actionable guidelines for regulators, industry stakeholders, and technology developers to enhance identity security, reduce investment uncertainty, and promote trust in Ethereum-based financial transactions.

### **Summary of Methodology**

| Objective | Method | Data Source | Analysis Approach |
| ----- | ----- | ----- | ----- |
| 1\. Digital Identity Crisis perception | Survey | Primary survey | Factor analysis & regression |
| 2\. Crypto investment uncertainty perception | Survey | Primary survey | Factor analysis & regression |
| 3\. Impact of DIC on CIU | Survey \+ Econometric Analysis | Primary survey | Regression analysis |
| 4\. Measuring DIC at country level | Google Trends | Search volume data | Index construction & time-series analysis |
| 5\. Impact of DIC on crypto market risks | Google Trends \+ Crypto Market Data | DICUI \+ Financial databases | VAR model & Granger Causality test |
| 6\. Policy Framework | Focus Group | Expert discussions | Thematic analysis |

## Timeline

This study will be a 2-year project with five structured phases, culminating in a peer-reviewed academic article. In addition to academic dissemination, we aim to present the findings at DevCon or other Ethereum Foundation (EF) events and summarize key insights through an EF blog post or podcast to reach a broader, non-academic audience.

Below is the revised timeline and milestones:

| Milestone | Details | Duration |
| ----- | ----- | ----- |
| Phase One: Data Collection (Survey) | Conduct structured surveys targeting crypto investors and general internet users to assess Digital Identity Crisis perception and Crypto Investment Uncertainty (CIU). | 6 Months |
| Phase Two: Google Trends & Market Data Collection | Gather daily Google Trends data for relevant search terms across multiple countries. Construct a Digital Identity Crisis Uncertainty Index (DICUI) to quantify country-level variations in public concern. Collect historical crypto market data (volatility, price swings) for behavioral finance analysis. | 3 Months |
| Phase Three: Econometric & Statistical Analysis | Analyze the collected survey data using Structural equation modelling. Perform econometric modeling (VAR, GARCH, and Granger causality tests) to examine the impact of Digital Identity Crisis on Crypto Investment Uncertainty and market systemic risks. Validate findings with robustness checks. | 6 Months |
| Phase Four: Focus Group Interviews for Policy Framework | Conduct expert focus groups (blockchain developers, policymakers, cybersecurity specialists, and crypto investors) to formulate policy recommendations for mitigating Digital Identity Crisis risks in AI-driven financial markets. | 3 Months |
| Phase Five: Compilation & Dissemination of Findings | Prepare a comprehensive research report, submit for peer-reviewed publication, and create a policy brief. Present findings at DevCon and EF events and publish a blog post/podcast for a wider audience. | 6 Months |

## Budget

Requested grant amount and how this will be used. Please provide an requested amount and outline of how the grant will be used. A detailed budget proposal would be helpful and some items you could include are:

| Budget Item | Unit | Unit Cost (USD) | Total Cost (USD) |
| :---- | :---- | :---- | :---- |
| | | | |
| **1\. Principal Researchers Costs** | | | |
| Dr. Emmanuel Joel Aikins Abakah (PI) | 1 | 2,000.00 | 2,000.00 |
| Dr. Mohammed Abdullah (Co-PI) | 1 | 2,000.00 | 2,000.00 |
| Dr. Freeman Brobbey Owusu (Co-PI) | 1 | 2,000.00 | 2,000.00 |
| SUB-TOTAL (1) | | | 6,000.00 |
| | | | |
| **2\. Other Staff Costs** | | | |
| Two Research Assistant (2 RAs for 18 months) | 2 | 5,500.00 | 11,000.00 |
| SUB-TOTAL (2) | | | 11,000.00 |
| | | | |
| **3\. Data Collection Costs** | | | |
| Survey cost \[64 surveyor (4 person in each 16 regions of Ghana) will be employed to collect total 600 questionnaires\] Inclusive all cost | 64 | 550 | 35,200.00 |
| Focus group interview (Focus group will be conducted with approx 30 regulator level personnel from financial, Trade and commerce, telecommunication, etc) Inclusive Honorarium and other related cost | 30 | 300 | 9,000.00 |
| SUB-TOTAL (3) | | | 44,200.00 |
| | | | |
| **4\. Indirect Costs** | | | |
| Ethics committee application fees and professional proofreading | 1 | 1,000.00 | 1,000.00 |
| Workshop For Stakeholders, Academia and Industry Players on Data issues & focus group and discussions of research findings | 2 | 2,000.00 | 4,000.00 |
| Submission/Publication fees | 1 | 500.00 | 500.00 |
| SUB-TOTAL (4) | | | 5,500.00 |
| | | | |
| **BUDGET TOTAL (i.e. sub totals 1-4)** | | | **66,700.00** |
| Contingency (2%) | | | 1,334.00 |
| **GRAND TOTAL** | | | **68,034.00** |

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