The effectiveness of blockchain technology in preventing financial cybercrime

. The primary objective of this research is to study the effectiveness of blockchain technology in preventing financial cybercrime. In this research, the researcher intends to know the effectiveness of blockchain technology in preventing financial cybercrime, the white-collar crime which is growing drastically globally. The researcher uses the primary method to collect the data. In this study, four different variables that influence financial cybercrime significantly are immutability, smart contract, distributed ledger technology and consensus algorithm. The data was collected from the targeted respondents which are accountants, IT experts and human resources. Statistical Package of the Social Sciences (SPSS) is being utilized to evaluate the relationship between the four variables which able to influence financial cybercrime. A total of 70 survey questionnaires were delivered to the targeted respondents via a convenience sampling strategy. Responses from 70 participants were entered into SPSS one by one to generate descriptive and inferential statistics. Financial cybercrime is positively correlated with immutability, smart contract, distributed ledger technology and consensus algorithms. As a result, the analysis of the collected data for this research rejects the null hypothesis, while supporting the alternative hypothesis. The conclusion that can derive from this research is that users and organizations should be aware of the financial cybercrime risks that take place around them and the importance to have vital tools that are not vulnerable to malicious attacks. This research creates awareness for users and companies on the usage of blockchain to prevent financial cybercrime.


Introduction
One of the massive current trends that swallows almost most emerging countries' reputations is white-collar crimes. This scope of crimes is defined as crimes that help to benefit one's individual desire by creating or having a financial gain through illegal activity. Unlike usual crimes heard, these crimes do not involve sharp weapons, knives or the urge to murder someone but a simple tool called data. The very basic white-collar crimes we must have heard, seen or even experienced are scams, insurance frauds, money laundering, embezzlement and not forget financial cybercrime (Gottschalk, 2020). In this globalized world with the presence of technology transformation, the digital world plays a vital role. Thus, many individuals' uses digital transactions, activities or even tools to invest, and fulfil their responsibilities, needs, and wants.
World Economic Forum in the year 2018 stated that cybercrime and frauds are part of a trillion-dollar industry as financial industries are spending more than $8.2 billion on these crimes. Many reasons cause opportunities for such crimes to take place such as diverse factors which include the level of vulnerability against these crimes which are inherent in automation and digitization, higher volume of transactions and integration within counties and internationally on the usage of financial systems (Ngo-Lam, 2019). Cybercrime and fraud cause to draw more attention than ever in most financial institutions. With highly sophisticated technology, crimes have increased more than ever with the presence of advent digitalization and automation of financial systems.
Carbanak attacks can be taken into example which took place in 2013 where it portrays the internet profile of much modern-day cybercrime and fraud. Carbanak and Cobalt, two pieces of malware created by the criminal gang, have been used to attack banks, e-payment systems, and financial organisations since 2013. More than 40 countries have been hit by illegal activity. This attack has caused a major loss of $ 1 billion under the scope of the financial industry. It is found out that these attackers are part of an organized criminal gang that has access to the vulnerable system through phishing and can transfer the fraudulent balances into their very own individual accounts or highly programmed ATMs to dispense cash (Europol, 2018). Based on Exhibit 1.1 is a summary of how the Carbanak Attack took place. This proves that those attackers highly know the bank processes and systems under a cyber environment which made them understand the processes, control and vulnerability of the governance and organization (Hasham, Joshi, & Mikkelsen, 2019). However, this questions how does the cybercriminal is well expert in this field?
In late 2013, the organised crime group launched the Anunak malware campaign, which targeted money transactions and ATM networks of financial institutions all over the world. The same coders returned the following year and created Carbanak, a more advanced variant of the Anunak malware. A series of more complex attacks based on custom malware developed with the help of penetration testing tools like Cobalt Strike began soon after. All the attacks had a consistent method in each of these incidents. With the support of Exhibit 1.1, spear phishing emails with harmful attachments would be sent to bank personnel by criminals posing as respectable companies. Criminals could remotely manipulate affected workstations using malicious software once it was downloaded, giving them access to the internal banking network and infecting ATM servers. This gave them the information they needed to get their hands on the cash (Meyer, 2018). Many reasons lead to the case behind this attack and one of them was the lack of awareness of employees. There were two employees easily tricked into opening a malicious document in a form of a spear-phishing email from the cybercriminal group. The entire system was in a centralized manner that made it easier for the hackers to into one domain and proceed with their attack. The third reason was the failure of installing any firewall or security that detects changes in transactions, that a high amount of cash is being transferred into accounts. With the failure of any combating tool, management was unaware of this attack as there was no alert (Vijayan, 2019).
Based on the annual data breach report done by The Identity Theft Research Centre (ITRC), stated that in the year 2021, there were almost 1,862 data were tampered with within the US and 68% in 2020 and 23% previously. As per the 2021 report, 294 million people's data were compromised compared to 2020 where 310 million people were involved. This report is related to the ransomware breach of data where phishing was one of the number one key factor that caused these data to be tampered with in the year 2022 based on the findings found in 2022. Usually, the insurance industry is one of the industries that are highly affected and frequently targeted for this ransomware attacks in the first half of 2021 while almost 25% of attacks take place against consumer goods and services and telecommunication. IBM security in conjunction with Ponemon Institute had made a finding of an average data of breach will approximately cost $3.86 million up to $4.24 million which is significantly increased over the year. However, ransomware attacks and any other much costlier breaches will cost an average of $4.62million and the average cost of malicious assaults that deleted data in destructive wiper-style attacks is $4.69 million. The digital transaction has its very own pros and cons, however currently the digital world has more cons than it ever should. The very common dangerous disadvantage is leading to financial cybercrimes. Financial cybercrime is an illegal activity that takes place on the internet in conjunction with using technology information or database just with a computer as a tool or weapon. These crimes are eventually involving a large amount of money with numerous transactions, scams, money laundering, a profit-motive activity like a Ponzi scheme or even internet fraud (M. Bossler & Brenblum, 2019). Fraudsters' target victims are those who widely use many computing devices for daily activities. In Malaysia, almost 10,722 cybercrime frauds took place in the year 2020 which caused an increase of 23 more cases compared to 2018. Most of the cybercrimes were under the scope of financial cybercrimes like financing loans. Due to this, Deputy Prime Minister Datuk Seri Wan Azizah decided to launch a project called the Cyber Security Modular Professional inequivalent to Industry 4.0 to combat this issue. (Bernama Malaysia, 2022) Cybersecurity is a known word as part of corporate security management that manages the guarantee of safety and comes up with security measures that help to defend against cybercrimes. A study has proven with an analysis that over 65% of internet users had become a victim of cybercrimes activities such as credit card frauds, computer viruses and identity theft. It is harder than expected for businesses to operate using a digital network platform. There are even damages through cyber-attacks that affected the financial sector. It is estimated that $2 billion will be spent on protecting from this malicious attack.
(Chikelue.C.Nwabuike, Vincent.A.Onodugo, Arachie, & Ugonna.C.Nkwunonwo, 2020) Advancements in technologies are part of business sustainability, growth and solution. Using an innovative database technology called blockchain, which is the heart of all cryptocurrencies and digital currency applications could manage to control the volatility and complexity of bitcoins. Blockchain was the most suitable database technology in this case because it could avoid hackers from hacking easily due to its features such as distributing identical copies across the network, verifiability, transparency, anonymity and authentication. (Xu, Chen, & Kou, 2019) Blockchains can be referred to as blocks of chain where it corresponds to one another. Once each transaction details are recorded into the database system, the details are impossible to tamper with as they will be shared with members of the network. In the year 2008, the concepts of blockchain and bitcoin is found using a pseudonym called Satoshi Nakamoto who proposed cryptology and digital currency application that combines with an open distributed ledger. Blockchain has become much more viable in adapting to environments other than digital currencies such as supply chain management, the tourism industry, healthcare, and e-commerce. (Bayramova, J.Edwards, & Roberts, 2021) Following key features besides immutability and smart contracts, distributed ledger technology is another database system that makes blockchain able to prevent financial cybercrime. Distributed ledger technology is based on an encoded and distributed database that serves as a ledger, storing transaction records. At its core, distributed ledger technology, a new database technique with a data architecture in which encryption is used in each transaction update and verification becomes possible across the specific blockchain network, depending on its aim and stakeholders (Simply Explained, 2018). Lastly are consensus algorithms, which is a common procedure where all the peers in the blockchain network come to an accord about the current state of the distributed ledger. This is where distributed technology and consensus algorithms come to hand. In such a way, consensus algorithms realize the reliability of blockchain networks and establish trust between unknown peers in a distributed computing environment (Geeks for Geeks, 2022).
By compromising a centralized system, the hacker can access all one thousand elements in one go. In real life, this may entail collecting the personal details of about one thousand persons merely through one security breach. With a decentralized system, cyber criminals can only access one piece at a time, making it far more time-consuming and practically impossible to see the full picture. They would have to hack several gateways several times to access someone's personal information. This would give the security system enough time to determine the source of the vulnerability and contain the breach. With this, blockchain technology is a vital tool to prevent financial cybercrime.

Literature Review
This chapter in whole explains the discussion on the previous research on the impact and how blockchain technology prevents financial cybercrime. This chapter will further define each factor that may create a negative or positive impact on the adoption of blockchain. As mentioned, the independent variables are consisting of immutability, smart contracts, distributed ledger technology and consensus algorithms. This chapter will further analyse whether these independent variables can help detect white-collar crimes that are taking place in the financial industry. Moreover, this chapter will apply reliable, updated existing journals wisely with the identification of literature gaps.

Base Theory
Cybercrime is part of white-collar crime that is completely illegal and part of criminal activity which involves computers and information technology. The causes of financial cybercrime are widely discussed in this literature considering the facts are the great current interest. Various authors have discussed the issues that caused financial cybercrime and its impact of it by providing insights to reduce the risk or opportunity for such crime to arise and combat this negative phenomenon. (Antonescu & Birau, 2015) Routine activity theory which is introduced by Cohen and Felson in the year 1979 stated this theory involves both victims and criminals. This is where criminals make bad choices about whether or not to commit a crime based on the opportunity and target that exist. Both the researchers stated that the motivation to perform a crime or illegal activity is always within the criminals. This is where the question comes out, what brings out the motivation within these criminals? According to (Kitteringham & J.Fennelly, 2020), once a suitable target or even chance arises which includes capable humans, guardians, civilians or even their very own neighbours, the level of motivation to perform such activity is higher than normal. The researchers also assume that criminals are always motivated rather than waiting for a chance to rise to make themselves motivated. This is how the theory differentiates from other theories of criminal activities. This theory focuses on victimization rather than crime because as has been stated above, it does not require high motivations for an offender to commit a crime as even a normal person could do. Routine activity theory also assumes that the motivation of a criminal to commit a crime is constant. From this perspective, there is no set of situations that increase or decrease the likelihood that a criminal will commit a crime. However, except in situations where it makes it easier for criminals to carry out their intentions (Nickerson, 2022).

Financial Cybercrime
As per (Ramadan, Putera, Sutrisno, & al, 2018), the researchers stated that the more sophisticated the technology is becoming, the greater number of criminal activities regarding cybercrime also increase. The presence of internet-connected with global networks causes many cybercrimes to exist since many organizations and companies are also involved and linked with the internet network creating an opportunity for fraudsters to perform their fraudulent activities. In the traditional method way, the only way to purchase a credit card is by performing a manual swipe tool while in the current sophisticated technology world, credit cards can be transacted online. Researchers stated to performing a cybercrime especially involving finance, is harder than expected to perform unless the security management's site is too weak to perform or install basic protection measures to be part of the defence mechanism. Most companies only focus on their companies' economic sustainability without any defence mechanism to protect which makes cybercriminals use emerging technologies and straightforward monetize what there are willing to hack or steal. Therefore, the research highly recommends, that banks and industries that are involved with finance are widely used online transactions are required to have a good and highly reliable security system to avoid malicious attacks from happening.
The following research is studied by (Akinbowale, Klingelhöfer, & Zerihun, 2020). The researchers conducted this study to explore the effects of cybercrime, especially in the banking sector and analyse the usage of the balanced score approach. From this study, it is highly confirmed that the existence of financial cybercrime has negatively impacted the growth and goodwill of the financial institution that puts trust and integrity against digital and internet infrastructure questionable through frauds. The study also gave suggestions on how to overcome cybercrime that should be considered as part of the development of a multidisciplinary approach using uncompromised intelligence involvement, utilising law enforcement and performing crime investigation together with third-party agencies for clearer scope. Even more, the financial institution could use effective crime-mitigating practices as it is already considered as part of the measures taken to increase the security mechanism. Researchers also widely believe, that one of the challenges that are widely faced could be curbed if the dissemination of information and knowledge between individuals and financial institutions could be considered as part of the strategy. The researchers suggested an emerging technology to help combat this situation.
Another research is done by (Tariq, 2018), on the global issues of financial cybercrime. The research is done to examine the impacts of cyberattacks on the financial industry by comparing the cases of cybercrime attacks that existed in five other different continents. The impact of these cybercrime attacks has caused direct and indirect losses. The direct losses are involving with money embezzlement and breach of data whereas the indirect losses involved customer dissatisfaction that leads to frustration and destruction of public correlation. The study emphasised that these attacks do not have any barriers or boundaries that are restricted. The financial institution that fails to come up with strategies to mitigate this problem is faced with heavy negative impacts. However, the researchers have come up with effective strategies that could curb and reduce the number of cyberattacks taking place in financial institutions such as having strong internal control, evaluation of cybersecurity, enhanced cyber security training and effective audit on cyber security.
The researchers (Malik & Islam, 2019), used employees who are working in the banking industry field in Pakistan on the impact of cyberattacks on their organizational performance and awareness of moderating the effects of security information. As per the study, it could be concluded that malicious attacks involving cybercrime attacks could create a negative impact on organizational performance, however, organizations who are highly aware of these attacks would increase their security defence mechanism as it affects the organization's daily management performances. The researchers emphasised that HR managers should have more security training courses and knowledge to avoid such situations from happening.

Immutability
As per the research done by (Haque & Rahman, 2020), hybrid blockchains are controlled by a group of users where all the transactions that are made and recorded are kept in private, yet they must be verified whenever needed to increase the creditability of each transaction and information. This is where immutability comes in handy. As per the researchers', the banking sector is taken as an example where sometimes individuals do argue about paying their taxes and this is where many civilians take the chances to refuse to pay the taxes or claim false information. With the presence of immutability as the key feature of blockchain, it can give out the right information and value when somebody is trying to claim false information and argue about the tax claim as blockchain can immediately give out the correct information regarding an individual's tax. With the presence of immutability, individuals can catch lying about their taxes as it is harder than ever to tamper with information that is recorded in the database system. Since immutability can maintain the authenticity of data as data cannot be erased or changed with ease in short can remain any data unchanged. It is impossible to update, edit, or overwrite an immutable collection of data that is protected by an immutable security policy. Some of these systems-specifically, "filers," which are virtual appliances at the edge-can be restored to a specific restoration point in the event of a cyberattack, maybe within seconds. Even the entire global file system can be renamed using this method.
Based on (Okazaki, 2018)), the blockchain database system has its very own key deliverables features that help to detect and prevent fraud, enhanced the accuracy level of recorded information, self-execution without intermediary and private accessible sharing of information. Cargoes that move internationally for trading purposes by sea or air must be insured to mitigate any risk that might occur in the future as set by the Institute of Cargo Clauses. This is where blockchain technology comes in handy as it helps to give better coordination between the different insurers' perspectives. With proper access to immutability and data security, insurers record all transactions securely and permanently, leading to fraud detection within and throughout the industry especially involving insurance fraud crime. Trust and compliance are two elements of an immutable system. With tons of private documents, immutability can retain those records for some time and make sure no parties accidentally delete or tamper with them for their benefit with the presence of immutability not only data cannot be edited but a security tool that gives a pop-up error if anybody is trying to tamper the data. This is where both parties are aware if manipulation of data is taking place.
Followed to the next research done by (Min, 2019), blockchain can validate and generate provenance by fully utilising an immutable digital record of an asset and assessing the life cycle of that particular asset neither both tangible nor intangible is immutable unless the owner grants access to verify a change. This is proven that immutability in the blockchain system avoids manipulation of data where the history of the ownership is untampered or fabricated. Since blockchain technology is highly transparent where is it publicly able to be viewed that permanently tracks and records all the activities relating to that particular asset in the system. As such it not only avoids fake or counterfeit assets but can track back the goods in an easier manner. Despite all the countless efforts to avoid financial cybercrime taking place in supply chain management such as installing antivirus or malware software, it is not as effective as it seems. The usage of end-to-end encryption, and the immutability nature of each peer-to-peer network, make blockchain an effective tool to combat the risk of cybercrime and hacking.
(Casino, Politou, Alepis, & Patsakis, 2019), immutability is suitable for a decentralized technology such as blockchain in the context of immutability to where data is recorded and saved as unable to be tampered with or guaranteed to be deleted once the data is uploaded by the owner or user. For some decentralised systems, each transaction is attributed with a unique cryptographic hash, therefore it is harder than expected even the slightest changes will result in a new hash that sends an alert into the system. The existence of an immutable data structure that helps to store and share across the enhanced decentralized network that includes the peer-to-peer network. With the development of such structure in the network, blockchain technology is given such a landscape that the features and applications in it are very highly sophisticated which could prevent cybercrimes from taking place. Immutability key feature can prevent undesired content from being modified or taken down without being granted by the user.
The objective of this research done by (Patil, Kadam, & Katti, 2021), is how immutability can increase the creditability of forensic reports with the presence of blockchain technology. As per the research, cybercrime does take place such as the healthcare sector as well which includes ransomware attacks, identity theft and private and confidential information being stolen which may lead to tons of financial losses as it involves lawsuits. With the presence of blockchain, whenever there is a new report being recorded into the blockchain database system, a new block is added which leads to a chain and there is when a unique cryptographic hash is generated. If any other node tries to insert new data where alteration of information is found, the entire chain will be broken which sends an alert to the system. Immutable storage technology can be used for legal holds, to supply a chain of custody, to secure digital evidence, and to protect data from cyberattacks by its users. This proves how immutability implies an important role in the healthcare sector as well. Using immutable storage makes it difficult to lose data due to equipment malfunction or human error as immutability ensures important files will not be easily deleted or overwritten.
Therefore, the proposed hypothesis is structured as it proves: -HA1: There is a relationship between immutability and the effectiveness of blockchain technology in preventing financial cybercrime.

Smart Contracts
Smart contract or in other words called "contract coding" focuses on legal contract agreements which involve two different parties. As per the researchers (Wang, Lau, & Mao, 2019), all smart contract transactions are trackable, irreversible, and highly transparent. This proves that smart contracts are automated with CE-specific transactions as it can eliminate bureaucracy and lesser transaction costs by bypassing a traditional and valuable intermediary. According to the researchers, smart contracts can create value by generating promising business value such as digital uniqueness, reports, derivatives, finances, research and lots more. As per all these stated above, each of them relates to finance and cash. Smart contracts can speed up approvals and payment processes that both parties can monitor as it is automated. A smart contract system, it has highly secure, and this is because encrypted blockchain transaction records make them extremely difficult to break. Hackers would have to alter the entire chain of the distributed ledger in a smart contract if they wanted to change a single record on a blockchain. The study also supports that a supply chain management smart contract together with the Internet of Things (IoT) can increase the transparency level of goods being tracked and thus reduce the risk of fraud involving counterfeits or relating to payment.
The basic knowledge of blockchain is a distributed database system where all records which are recorded digitally are executed and shared with respective users. This is where each and all recorded transactions are authenticated by their unique consensus hashes. Blockchain is invented with the concept of maintaining the volatility of digital currency that has automated algorithms, just like big data and artificial intelligence. One of the basic products is a smart contract that could be found in blockchain. According to (Negara, Hidyanto, Andryani, & Erlan, 2021) smart contracts can establish their own rules and define their predetermined conditions as the contracts can be executed automatically. One of the advantages of the existence of the smart contract is, that it can avoid hacking or any forge contract from taking place. Smart contracts are built with digital codes that encode real-world contract deals as it helps to bind a contract. However, smart contracts refuse to engage with third-party functions as both present parties have a digital contract key already. Since no third party is engaged and because encrypted records of transactions are shared among participants, there is no need to question if the information has been altered for personal gain which increases the trust and transparency between the rightful, respective parties of the contract.
Besides looking into other industries and scope, digital currency platforms are being overlooked especially involving cryptocurrency as it is one of the future financial cybercrime schemes to take place. The researchers Trozze, et al., (2022) believe that cryptocurrency fraud has become a global concern that involves various governments finding ways to mitigate the scams that are taking place. Cryptocurrency platforms such as Bitcoin insert smart contracts which are programmed by the computer as it generates a smart contract code that is transparent on the system. Parties who are involved with digital currency transactions could be able to trust and proceed with their agreements, not only because it is transparent but also highly secured.
Thus, the proposed hypothesis is structured as it proves: HA2: There is a relationship between smart contracts and the effectiveness of blockchain in preventing financial cybercrime.

Distributed Ledger Technology
(Vujicic, Nermin, Maro, & Leo, 2020), evaluate the usage of Distributed Ledger Technology (DLT) in the shipping industry. (DLT) can be utilised in collecting information on the best discharge areas and speeding up the shipping process. The entire operation is easier and more ecologically friendly as DTL eliminates the need to fill out numerous forms and records. The adoption of a structured communal data transmission ensures that data is sent to all relevant parties effectively and appropriately. By using DTL, pieces of information like who can access the data, who is restricted, and the amount of data that can be shared in the network can be controlled effectively. DLT make use of separate computers (referred to as nodes) to record, share, and synchronise transactions in each electronic ledger (instead of keeping data centralised as in a traditional ledger). Data is organised into blocks and then chained together using the blockchain solely in an add mode. This consequently can prevent the industry from cybercrime and piracy. Most importantly, wastewater discharges overboard would be carefully managed, documented, and metered, with distributed ledger technology preventing any unlawful activities or document fabrication, assuring environmental sustainability. (Sirohi, 2021), conduct a study to investigate blockchain applications in banking operations. As blockchain has this distributed ledger technology, it interconnects the transactions and data to all the users and servers in the network. However, due to its high security, data inside the network could not be hacked or stolen by any criminals. . This is because, since the number of users is enormous in the system, the hacker/ theft faces difficulties in identifying where specific information is being kept. Even when a user operates the system, his unique transactions are highly carried out with increased transparency, resulting in a lower rate of cybercrime in the banking industry. Most banking industries are now adopting Fin-tech-based technology with DTL features in it to facilitate mobile banking and multi-currency card.
Financial crimes especially fraudulent insurance claims are increasing drastically across the nation. For evidence, Australia is estimated to encounter approximately $2 billion yearly due to insurance fraud. Distributed ledgers in blockchain can reduce and detect insurance fraud by checking the legitimacy of customers, policies and transactions using historical data. For example, DLT aids the insurers in identifying repeated claims and suspect parties who are engaging in this fraud as all the claiming details would have been stored in the system and authorized by insurers. In addition, DLT also detects forged injuries/ damages reports. In this case, DLT makes sure the insurers authorize the legitimacy of policy records and examine the time and date of insurance purchase, as well as prior policy claims. This may help in distinguishing potential trends and patterns of insurance fraud crime by the fraudster (Tarr & Julie-Anne, 2018) The proposed hypothesis is structured as it proves: HA3: There is a relationship between distributed ledger technology and the effectiveness of blockchain technology in preventing financial cybercrime.

Consensus Algorithms
As per the research conducted by (Litke, Anagnostopoulos, & Varvarigou, 2019), the usage of blockchain in the supply chain is found widely as it can bring more advantages than ever.
By recording a product's cycle from its manufacturing details to its end-user in the database system, chain nodes will be produced that help to increase the transparency and trust level among the involved users and parties. Involving trusted thirds may increase the number of users to participate in the chain of custody and increase creativity and innovation as blockchain also recommends instant payments through digital currencies. The uniqueness of consensus algorithms can keep an agreement between nodes of the network in a form of transaction information. With such, each of those transaction records is timestamped with the user recorded time, details, amount executed and lots more. This can avoid frauds, failures, or errors to occur easily.
According to (Wadha, Somaya, Abdulghani, Ali, & Muhammad, 2020), there are many types of financial cybercrime taking place in many industries and globally. One of the ways to resolve the issue being suggested is blockchain technology due to its algorithms. Unlike cryptographic hashes, algorithms are much more in-depth to detect a malicious attack or an unusual movement taking place. Algorithms proven by these researchers are one of the most suitable especially when involving tons of transactions in daily activity, for example, in the banking sector. The banking industry has tons of users' deposits and withdraws cash, cheque, requesting loans and lots more relating to financial services. To avoid tampering with data algorithms can read when each of the data is being inserted into the database system. This eventually avoid any illegal activities from taking place.
(Nicholls, Kuppa, & Le-Khac, 2016),stated that algorithms are one of the solutions in combating financial cybercrime frauds. A survey was conducted by this research to prove the effectiveness of algorithms in curbing financial cybercrime. It is reviewed that almost 23% of financial fraud detection used Support Vector Machine (SVM) while the balance of 77% used algorithms. Consensus algorithms are used to preserve the security of blockchain which means the vulnerability of the system against malicious attacks can be lowered. When a new block is added to the system, the integrity of the data or information will be recorded in a form of timestamped hashes. All these timestamped hashes and consensus algorithms are highly useful as it is being supported with Proof of Work (PoW), Proof of Stake(PoS) and also Proof of Authority(PoA) where it's a whole new level of security.
Therefore, the proposed hypothesis is structured as it proves: HA4: There is a relationship between consensus algorithms and the effectiveness of blockchain technology in preventing financial cybercrime.

Research Philosophy
In this research, interpretivism is the philosophical stance that will be used. The reason behind the usage of the interpretivism philosophy is supported by research that is conducted (Ryan, 2018), over the adoption of interpretivism defines there is an in-depth understanding of a topic that should be based on interpretation. According to (Pham, 2018), the author explains interpretivism represents a shift from determining the causal relationship between variables to focusing on depth analysis as to why certain aspects take place.

Research Approach
The deductive approach is the most suitable in a quantitative primary mode as part of its strategy that consists of a survey approach which helps to obtain data from respondents that further test the hypothesis. Besides that, a deductive approach consists of a framework that helps to identify in analyze data (Azungah, 2018). With this, the researcher can create a logical structure based on his or her assumptions and specifically achieve the study objective.

Research Strategy
Based on this research, a survey would be the most appropriate strategy as it helps to collect quantifiable information from the target respondents to gain more knowledge. As a quantitative study, creating a questionnaire and collecting answers from respondents will be part of the data analysis as the data collection will be efficient and reliable (Apuke, 2017). A quantitative study framework uses analysis and statistical techniques or assumptions in research. From this, the reliability of research is high as it is based on direct observation and firsthand source data.

Research Methodological Choices
The quantitative primary mode will be applied to further progress in this research. Based on (Bhandari, 2021), primary data are sources that are original and collected specifically for that research. According to (Rahman, 2017), the quantitative method creates a much more holistic view and in-depth understanding based on other people's points of view. (Woiceshyn & S.Daellenbach, 2018), explains that in conjunction with the deductive approach, researchers use a quantitative approach to collect a large amount of data by creating a questionnaire based on their target respondents. Quantitative helps to create reasoning by generalizing and observing the targeted population.

Time Horizon
Cross-sectional is adopted in this research as the data collected will be gathered once using the survey strategy. This research studies the effectiveness of blockchain technology in preventing financial cybercrime that involves data collection at that specific time of moment from respondents (Melnikovas, 2018).

Type of Data
This study is conducted using primary data as the objective to gather first-hand information through a survey using digital questionnaires focusing on the target respondents who are accountants, IT expert and human resources who are working in Malaysia.

Sources of Data Collection
Data will be collected from the distribution of digital questionnaires specifically through Google Forms. This approach will help respondents feel comfortable by selecting the Likert scale based on their perspectives and opinion.

Sampling Method
According to the Raosoft sample size calculator as per Exhibit 3.1, the target population will be 10,000 and the expected response rate is to be assumed, 50% (5,000 out of 10,000). Based on the sample size calculator, the margin error is 10%, the confidence level is 90% and the population are 10,000 which leads to 68 respondents being required to be the sample size for this research. The sampling method that will be used is non-probability sampling focusing based on the convenience of the researcher.

Data Preparation
Data is collected to be used as part of the analysis to achieve the objective of this research. The researcher will carry out coding to transcribe respondents' answers into numerical data analysis followed by data editing. Data editing helps to check the reliability and incompleteness of the created questionnaire. The final data will be recorded in a form of a table using an Excel spreadsheet by subsequently using the SPSS program if further analysis is required (Abdallah, Du, & Webb, 2017)

Data Analysis
Statistical Package for the Social Sciences (SPSS) will be the software used to analyze a huge amount of data that will be collected from the questionnaire to test the hypothesis. Descriptive analysis is widely used in quantitative research as it helps to describe the results of the information using statistical analysis which includes sum, mode, median, mean and percentage. To evaluate the reliability of the data, Cronbach Alpha, Pearson's Correlation Coefficient and Multiple Regression Model will be further used to support the numerical data.

Results, Findings and Discussions
This chapter designates information that is obtained through the data collection process. The relationship between the dependent variable which is financial cybercrime and independent variables which are immutability, smart contracts, distributed ledger technology and consensus algorithms of data will be found by analyzing the data that is collected. The objective of the tables and chart that is created in this chapter is to make readers aware and understand the research better.

Number of Items Likert Scale
Cronbach's Alpha 36 1-5 .893 The output of the Alpha is 0.893. The N of items represents the number of questions created in the questionnaire from the dependent variable which is financial cybercrime and the independent variable which is immutability, smart contract, distributed ledger technology and consensus algorithm which adds up to 36 questions in total.
Therefore, as per the results, it distinguishes that the value of reliability is more than 0.7 so therefore it proves that the overall questionnaire is consistent and acceptable to be used for the intention of analysis of the research that assesses the effectiveness of blockchain in detecting financial cybercrime.

Pearson's Correlation Coefficient
The Pearson's Correlation Coefficient in SPSS software is used to conduct the hypothesis test which is mentioned before. As per (ShaunTurney, 2022), the most common way of measuring a linear correlation is by using Pearson's Correlation Coefficient. It helps to measure the strength and direction of the relationship between two variables using the number between -1 and 1. When the correlation coefficient of -1 is shown, it represents the two variables having the perfect negative relationship where one value of one variable increases, and the value of another variable decreases. Nevertheless, the correlation coefficient of 1 represents two variables that have a perfect relationship which means that when the value of one variable increases, the value of another variable also increases. If there is any possibility that the correlation coefficient is equal to zero, therefore it means there is no relationship between the two variables. According to Table 4.2 above, the results for Pearson correlation had been demonstrated. Through observation, IV2 (smart contract) has indicated the strongest relationship with DV (financial cybercrime) with a correlation coefficient of 0.567. The strength of the relationship between these variables was considered moderate while the positive sign of the correlation coefficient showed that the variables were positively related. As the correlation is significant at the 0.01 level, the relationship between the smart contract and financial cybercrime was significant with the sig. value 0.000. Followed by the second strongest relationship with DV (financial cybercrime) with IV3 (distributed ledger technology) with a correlation coefficient of 0.558. The strength of the relationship was considered moderate and resulted in a positive sign correlation coefficient had shown that the variables were positively or directly related. Since the correlation was significant at the 0.01 level, the relationship between IV3 (distributed ledger technology) and DV (financial cybercrime) was significant as the sig, with the value shown as 0.000.
The third independent variable was IV4 (consensus algorithm) which results in a correlation coefficient of 0.542 proving a moderate relationship with DV (financial cybercrime) while a positive sign of the correlation coefficient demonstrated that these two variables were positively related. The correlation was significant at a 0.01 level, thus, the relationship between IV4 (consensus algorithms) and DV (financial cybercrime) was significant as the sig. the value shown in the table was 0.000.
Finally, the fourth independent variable was IV1(immutability) which shows the weakest relationship with DV (financial cybercrime). The results of the correlation coefficient were 0.517, which meant that the strength of this relationship was relatively weak compared to other independent variables. The positive sign of the correlation coefficient explained that these two variables were positively or directly related. As the correlation was significant at the 0.01 level, the relationship between IV1 (immutability) and DV (financial cybercrime) was significant as the sig. value in the table above stated 0.000. R-value is known as the coefficient correlation whereby helps to indicate the range between the dependent and independent variable in terms of a strong positive relationship as +1 and a strong negative relationship as -1. Based on the analysis, the result of the R-value is 0.592 which determines that as a positive relationship between financial cybercrime and all the other independent variables.

Multiple Linear Regression
Other than that, the value of R² is relatively equivalent to 0.350 which further can also be recognized as 35% which helps to calculate approximately the capacity of the model to clarify varieties in the dependent variable through the variety in the independent variables (Zach, 2022). From this, it can be deduced that there is a correlation between financial cybercrime with immutability, smart contract, distributed ledger technology and also consensus algorithm has a significant correlation. The balance of 65% of financial cybercrime could have other factors that impact it.

Dependent Variable: Financial Cybercrime b. Predictors: (Constant), Consensus Algorithm, Immutability, Distributed Ledger Technology, Smart Contract
The output of the AVOVA test for multiple regression had been shown. Using the ANOVA table, as its name implied, further examination of the model's variance is achieved. Concerning the above ANOVA model, it helps to indicate whether there is a significant positive relationship between the model and between the variables or not. The df is discussed to the degree of freedom which explained the total number of independent variables in the regression model. Table 4.4 shows that df is 4(df=5-1=4) which justifies the degree of freedom which was generated by 5 variables that involve the dependent and independent variables. A further consideration is the residual degree of freedom, which is 70, given the size of the sample. From this 70-sample size, the 5 variables are deducted from the sample size to obtain 65. Followed by the aggregate of 4 for the degree of freedom calculation and 65 is produced based on the outcome of 69 for the total degree of freedom.
At the same time, this model's fit for the data can be evaluated using the F and as such, the F value is generated from the regression mean square divided by the residual mean square. According to the table, the sig. value is 0.000. In short, the equation that is generated was F (4, 65) =8.764, p (0.000) <0.05. Further explanation is supported since the p-value is below 0.05, and the slope of the regression line does not fall to zero, which proves that the regression model is a good fit of data and there is a significant linear relationship between the dependant and independent variables. Hypothesis testing will be performed followed by this.

a. Dependent Variable: Financial Cybercrime
The coefficients table that had been shown after the multiple regression had been performed. According to the observation, the constant has a result of 1.947 which is a forecasted value supporting the dependant variable. Next, the value of the unstandardized coefficient implied how much the dependent variable had altered with an independent variable when the other independent variables were held constant. As per the analysis, IV2 (smart contract) generated a result of 0.206. This result is supported that for every unit increased in the smart contract, there was a 0.206 increase in financial cybercrime. The smart contract is considered one of the highest unstandardized coefficients. Moving on, every unit increased in IV3 (distributed ledger technology) contributed to a 0.180 increase in financial cybercrime. The third highest unstandardized coefficient is IV4(consensus algorithm) which generates the result of 0.111. This result is further explained that every unit increase in the consensus algorithm leads to a 0.111 increase in financial cybercrime. The lowest unstandardized coefficient is IV1(immutability) which results in 0.062. This is justified that every unit increase in immutability leads to a 0.062 increase in financial cybercrime. Based on the observed analysis, all the independent variables in the table have resulted in positive values, which further explains, that an increase of every unit in the predictor would contribute to the increase of the dependent variable.
Furthermore, beta weight is also known as standardized coefficients. Whenever the criterion and the predictor variables are both standardised, they are utilised. If all other predictor variables remain constant, the beta weight is used to estimate the increase in the dependent variable caused by a standard deviation rise in the predictor variable (Stephanie, 2016). Observing and quantifying the relative importance of the predictor factors in explaining the dependent variable was an important step in the research process. According to Table 4.5, the highest resulting standardized coefficient was IV2(smart contract) which was β=0.226, which indicated an increase of one standard deviation in smart contract caused an increase of 0.226 in financial cybercrime. Followed by the second highest independent variable was IV3(distributed ledger technology) which resulted in β=0.207 and the third highest was IV4(consensus algorithm), β=0.137. The lowest was IV1(immutability) which had β=0.069. Hence, the ranking and order had been studied.
In addition, the last column of Table 4.5 is realised to be as sig. value that had been demonstrated for all independent variables. Through the analysis, IV1(immutability) had shown 0.724, IV2(smart contract) had shown 0.336, IV3(distributed ledger technology) had shown 0.362 and the IV4(consensus algorithm) had shown 0.503. Based on these, it had proven that the results are more than the p-value which must be less than 0.05. However, the following table had shown the hypothesis testing for the respective independent variables to conclude the results of the analysis.

Hypothesis Testing
It can be understood that ANOVA can provide a significant level of estimating results. The further explanation of ANOVA and justification of hypothesis testing will be explained in this section. As it had been known the df stands for the number of independent variables or degree of freedom. This is where the df will be calculated by deducting 1 from the number of variables(df=n-1) (Bevans, 2022). Apart from that F value is used to describe the variances between the variables.
Despite the sig. value of Table 4.5 illustrates that there is no significant relationship between the dependant and independent variables due to its value higher than 0.05, however, as per Table 4.4, the significance level is 0.000 which is lower than 0.05, therefore this further supports that the relationship between the dependant variables and independent variables which are immutability, smart contract, distributed ledger technology and consensus algorithm is significant with financial cybercrime. Hence, the null hypothesis is rejected.
Relationship between immutability and financial cybercrime In this research, the null hypothesis, H01 is rejected while the alternative hypothesis, HA1 is accepted. Based on the research done by (Venkatesh & R.Gordon, 2020) stated that immutability in blockchain technology would appear to limit the value of leveraging for criminal activity. Immutability appears to make blockchain systems less vulnerable to malicious attacks. This is also further supported by (Shrestha & Nam, 2019) that believes based on the research conducted by them, with lesser immutability features in a blockchain system, there is a higher chance of 51% of malicious attack and an increased probability of financial cybercrime.
The objective of this research is achieved as it is to study the effectiveness of immutability in blockchain technology in preventing financial cybercrime. Immutability is a feature that

H01
There is no relationship between immutability and the effectiveness of blockchain technology in preventing financial cybercrime.

HA1
There is a relationship between immutability and the effectiveness of blockchain technology in preventing financial cybercrime.
helps to remain permanent and unable to alter any history of transactions. As such, data or information are hard to be manipulated, erased, replaced, or even falsified by any individual or employee. It gives a harder time for hackers to perform financial cybercrime as it can easily be detected or traced (Boireau, 2018) . The researcher has achieved the first objective by proving hypothesis 1.
Relationship between smart contract and financial cybercrime According to (Unal, Hammoudeh, & Kiraz, 2020), there are many benefits of smart contract that makes blockchain system trustworthy. As per the researcher, in the smart contract, there will not be any third-party involvement since all the records or transactions are encrypted which will only be shared across the involved parties. This is further supported by (Vivar, Turegano, Lucila, & Garcia, 2020), who stated that a smart contract with a very high level of programming that helps users to generate a special type of transaction with a series of data would avoid any third-party to encrypt or even change any records. It is also further justified that each record is also linked to the previous and subsequent records on the distributed ledger where it's harder for hackers to alter the system as they are required to change the entire chain. With this, the alternative hypothesis, HA2 is accepted and the null hypothesis, H02 is rejected.
Followed by the second objective of this research is to examine the reliability of smart contracts in blockchain technology to prevent financial cybercrime. There are many advantages to the implementation of smart contracts in the blockchain system which are highly reliable, trust and transparency, security, and savings. In a smart contract, a network of computers executes certain actions such as releasing funds to the respective parties. Once the transactions are completed and updated, there is not any chance for the transaction to be changed as only respective parties are given the right to see results (Sayeed, Marco-Gisbert, & Caira, 2016). With this, it can be concluded the researcher has achieved the second objective by proving hypothesis 2.
Relationship between distributed ledger technology and financial cybercrime (Richardson, 2022) research that with distributed ledger technology in place with blockchain technology, it results in a tamper-proof system. The presence of distributed ledger technology makes the system transparent and traceable which makes any information that is recorded unaltered or even deleted. This hypothesis is further supported by (Chinyamunjiko, Makudza, & Mandongwe, 2022). The researchers acknowledged that distributed ledger technology also offers decentralization. Therefore, hackers have even more of a difficult time accessing data as there isn't any single point of entry. Independent computers (referred to as "nodes") are used by distributed ledgers to record, share, and synchronise transactions in each electronic ledger (instead of keeping data centralised as in a traditional ledger). With the proven justifications of researchers, the alternative hypothesis, HA3 is accepted while the null hypothesis, H03 is rejected.
The objective of this independent variable is to analyze the efficiency of distributed ledger technology in blockchain technology in preventing financial cybercrime. Since distributed ledger technology works more like a decentralized system, it is harder for cybercriminals to H02 There is no relationship between smart contracts and the effectiveness of blockchain technology in preventing financial cybercrime.

HA2
There is a relationship between smart contracts and the effectiveness of blockchain technology in preventing financial cybercrime.

H03
There is no relationship between distributed ledger technology and the effectiveness of blockchain technology in preventing financial cybercrime.

HA3
There is a relationship between distributed ledger technology and the effectiveness of blockchain technology in preventing financial cybercrime. hack into a system as it has several other networks, unlike a centralized system. The users can acquire an identical copy of the recordings shared across the network. In case the blockchain is updated or appended, the changes are replicated and copied to the users. To make sure that the database is accurate, it is synchronized. This proves that distributed ledger technology is highly efficient (BIS Quarterly Review, 2017). The researcher has achieved the third objective by proving hypothesis 3. Relationship between consensus algorithm and financial cybercrime The null hypothesis, H04, is rejected while the alternative hypothesis, HA4, is accepted. (Li, Zhao, Yang, Andriotis, & Xu, 2019) found out that a consensus algorithm can prevent financial cybercrime which further proves that these two variables have a relationship. The study explains that to trust unknown peers in a distributed computing environment, blockchain networks require a consensus algorithm, which is a mechanism that allows all participants to reach a common agreement (consensus) on the current state of the ledger's data. This results in a win-win situation. In addition, (BangBit Technologies, 2018), a consensus algorithm is one of the features that make blockchain technology a vital tool to fight against malicious attacks.
The final objective of this research is to study the consensus algorithm function in preventing financial cybercrime by using blockchain technology. With the presence of distributed settings in blockchain technology, the consensus algorithm helps the mechanism achieve coordination. Many algorithms work in the system such as proof of work (Pow), proof of stake (PoS) and many more. The presence of a consensus algorithm allows the blockchain to validate and confirm each transaction moving in and out of the system. This eliminates the need for a third-party intermediary (O. Vashchuk & R.Shuwar, 2018). With this, it can be concluded the researcher has achieved the fourth objective by proving hypothesis 4.

Conclusion
Data is the lifeblood of business. Faster time and more accuracy are both desirable. Blockchain is ideal for the delivery, and protection of important data, transactions or information because of its features that provide immutability, smart contracts, distributed ledger technology and consensus algorithm. Orders, payments, and accounts may all be tracked via a blockchain network. The fact that every user has access to the same version of reality means that more trust is achieved and can take advantage of new efficiencies and opportunities as a result. Using distributed records, information can be decentralised, sequentially hashed, and encrypted, making it nearly hard for attackers to decode the data (C.Komalavalli, Saxena, & Laroiya, 2020).
With the explanation above, all the relationships between the independent and dependant variables are accepted and able to influence each other. The hypotheses were put to the test, and the results revealed some interesting relationships.
The awareness of financial cybercrime is important for individual users, organizations, and industries. A secured system with high firewalls and effective tools can reduce the vulnerability to financial cybercrime. With this, blockchain technology is a suitable and essential tool to reduce, avoid and protect from financial cybercrime. Many researchers have conducted studies and proven that financial cybercrime and blockchain technology determinants have a positive relationship. Since blockchain technology aims to protect, reduce and avoid the presence of financial cybercrime, awareness of blockchain technology

H04
There is no relationship between consensus algorithms and the effectiveness of blockchain technology in preventing financial cybercrime.

HA4
There is a relationship between consensus algorithms and the effectiveness of blockchain technology in preventing financial cybercrime. and financial cybercrime is essential. Therefore, the information and data of users and organizations can be secured and stored in a proper method with supporting tools to increase the firewall and reduce the weakness against malicious attacks. In this study, the researcher proposes four variables of blockchain technology to create a particular awareness among industries.
This research has focused on the degree of blockchain technology which includes immutability, smart contract, distributed ledger technology and consensus algorithm influences on financial cybercrime. Throughout this study, it can be concluded that all four independent variables which are stated above have a positive and significant impact on financial cybercrime. It can be defined that the level of effectiveness of blockchain technology factors increases the degree of financial cybercrime also increases. In this research, the most significant relationship is smart contracts and financial cybercrime. However, it does not conclude that the other three variables do not impact but have their very own significant impact on financial cybercrime which should be taken into consideration by other users.

Recommendations
Blockchain technology is becoming increasingly popular in today's technologically savvy world. It can replace the use of the traditional method which is paper-based and manual transaction processing. It's easy for users to save and trade information via this platform, which is convenient. Now more organizations with an increase of 2.8% in total worldwide use blockchain technology to store highly secured information or transactions (Tuwiner, 2022). However, there are some setbacks to the usage of blockchain technology. Many organizations stated that blockchain solution consumes too much energy which increases other costs. This leads to consideration by all users or organizations that use blockchain technology.
The algorithm used to evaluate proof-of-work is reliant on trial and error because the hash value changes in a non-uniform manner. A new block of bitcoin, for example, is mined in around 10 minutes by the network's miners. This procedure has unquestionably led to an increase in efficiency but at the expense of large amounts of energy (Ghosh & Das, 2020) To address such drawbacks, analysts have suggested ways to solve this problem of energy consumption. One of the recommendations that could be used is the usage of renewable energy. This method is further evident in Mongolia which used coal power for the usage of blockchain technology. As a result, global warming and environmental damage are inevitable. Since blockchains consume a large quantity of energy, renewable energy sources should be used instead of non-renewable ones for generating electricity. Green blockchains are preferred by companies like IBM and Intel for the transaction process. The first step in achieving this goal is the decentralisation of power. Wind and solar energy will be used to create power. Peer-to-peer communication between power users will be enabled through blockchains. The entire set-up is referred to as a "microgrid". It is possible to use blockchains to transfer power from whom have excess capacity to those who need it without human interference. With the decentralisation of power that is sustainable, green blockchains can be utilised (Ghosh & Das, 2020) The second method is by lighting the network. A lightning network is a method of lowering energy consumption by allowing transactions to be recorded only when the channels between the users have been closed. This method is proposed by Thaddeus Dryja and Joseph Poon in 2015. User-initiated transactions can be handled without the involvement of third parties in this system. Whenever a channel is closed, data is no longer retained. It is not accessible to the public. A transaction is only updated once it's been completed or finished. As a result, it uses a lot less energy because the energy used per transaction is reduced. Galaxy digital predicted that the existing banking sector will use 263.72 TWh of energy annually by 2021. At first glance, blockchain technology appears to utilise a lot of energy -even if only for transactional purposes -yet its carbon emissions are lower than those of many commonplace activities that are rarely cited as energy-intensive, which as Lighting Network.

Limitation
Firstly, this research on the effectiveness of blockchain in preventing financial cybercrime merely comprises four independent variables which are involved immutability, smart contract, distributed ledger technology and consensus algorithm. Despite having four independent variables, there are not sufficient to evaluate or analyse the effectiveness of blockchain technology in preventing financial cybercrime. There is still room for more detailed information and more research to improvise the findings for the upcoming researchers. The demographics part will be initiated to look for much more precise facts to enrich the topic matter of the research. More previous researchers should be included to make sure the literature review is well detailed explained and more significant to the study.
Even more, the sample size of the respondents should be bigger to achieve more accurate results in the study which helps to make a thorough analysis of the study. In this research, the total of 70 respondents that provided their judgement through the survey was not enough and inadequate to demonstrate a better analysis of opinion. It is suggested for future researchers to increase the population and attain the right sample size that leads to precise data for analysis. Due to the high sample size, researchers may reach a comprehensive conclusion and give accurate specified data in this study.
The study of the effectiveness of blockchain technology in preventing financial cybercrime was only focused on industries and public listed companies in Malaysia. However, financial cybercrime is a global white-collar crime that does not only take place in Malaysia but globally. The narrow down scope of focusing on a specific country makes the study prevail from the certain knowledge that could be useful from another global perspective. Another viewpoint may lead to other factors that can be supportive of this study.
Finally, the statistical analysis software that is being used in this study is SPSS. Upcoming researchers are suggested to use or even try out other software to conduct and generate data analysis to provide more acceptable and reliable, significant results for the research. By doing such, it can create more impact by supporting a more accurate analysis of the awareness of financial cybercrime to readers.