Use and Abuse of Digital Technology in the context of Economic Offences
Economic and financial crime became a very captivating topic to study because once
technology developed, new methods of committing these types of crimes have made their
presence felt. Economy in financial crime into four main components: corruption, shadow
economy, money laundering and cybercrime. Economic offences are on the rise after
digitization because the quality of public governance is poor and the population is not
sufficiently educated in the financial field, neither in the cyber-protection field. Also, the level
of education can significantly affect engagement in such crimes. Economic growth flourishes
on technological advances, but criminal activity also responds and reacts creating challenges
for regulators, legitimate businesses and their customers, auditors and advisers alike.
In the digital society, very different organized crime groups coexist with different organizational
models: from online cybercrime to traditional organized crime groups to hybrid criminal groups
in which humans and machines ‘collaborate’ in new and close ways in networks of human and
non-human actors. These criminal groups commit very different organized crime activities,
from the most technological to the most traditional, and move from online to offline. They use
technology and interact with computers for a variety of purposes, and the distinction between
the physical and virtual dimensions of organized crime is increasingly blurred.
Use of Digital Technology in the Context of Economic Offences
Digital technology has tremendous potential to reduce and eradicate economic offences.
1. Digital Transactions: Digital transactions not only allow cashless transactions; they also
record a log of each and every transaction. These records provide a source for clean audits
and help in the prevention of economic offences such as banking fraud, real estate fraud
and income tax evasion. They also help to identify who commits such offences and is
involved in illegal transactions. They provide confidentiality, accountability and integrity.
Many frauds in the real estate business happen because of black money and cash
transactions. If the transactions are made to be mandatory digital transactions, such fraud
cannot happen. Digital transactions can also eradicate corruption to a larger extent.
Recording transactions using blockchains can effectively be used to trace illegal
transactions.
2. Digital Technology in Detection of Economic Offences: Nowadays, there is a lot of
digital technology that can be used in the detection of fraud related to economic offences.
Machine learning and deep learning technologies have great potential in detecting various
economic offences. Deep learning techniques like convolutional neural networks excel in
image processing. This can be used to detect various economic offences and prevent them.
Deep learning to detect Food Adulteration: A lot of research goes on in the detection of
waxed apples, adulterated milk, coloured vegetables and fruits and food mixed with
harmful adulterants using convolutional neural networks. In supermarkets, stale fish are
chemically treated and mixed with harmful chemicals such as formalin and made to appear
like fresh fish. These types of food adulteration that are done with the sole motive of moneymaking create a lot of health hazards such as stomach disorders, liver ailments and even
cancer and pose a great threat to society. The general public is in need of a technology or
device that can easily help them to identify such types of adulterated food which can not
only help them not to buy and use such food but also discourage the offenders to use such
adulterants. Technology can be used to develop mobile applications or smart devices that
can serve the purpose.
Deep Learning and IoT for detecting Counterfeiting: Deep learning techniques can also
be used to efficiently detect fake currency notes and fake products. The use of such
technologies can make people alert and help them to detect fake products, fake currency
notes and avoid them. If technology helps people detect such fraudulent activities, the
offenders will not be able to commit such offences. Corruption can also be largely
controlled since the key to controlling these offences is directly in the hands of the people.
Image sensor technology is currently used to detect fake currency notes. Counting machines
use UV (Ultra Violet), MG (Magnetic) & IR (Infra Red) sensors for detecting fake
currencies. Deep learning image processing techniques can also detect crimes against
Intellectual Property Rights such as fake logos, copyright offences etc.
Blockchain Technology: Blockchain technology can be effectively used in the detection
of IPR-related offences. Blockchain technology can also be used to identify and mitigate
the risks of human trafficking and smuggling. To better identify human trafficking and
smuggling risks, companies are using blockchain technology which allows tracking the
production of goods from their source to the final destination to increase transparency and
aid in exercising due diligence. AI technology can be used to identify how a child victim of
sex trafficking would look when he/she is an adult, to enable autonomous machine
communication with potential users of services from trafficking victims, to recognize the
features of hotel rooms where victims may be held, and to identify financial transactions
that may be indicative of human trafficking networks.
Facial Recognition: Visual processing software can be used to search for photos and videos
of victims who are trafficked for sexual exploitation. Facial recognition technology can be
used in web crawling to search for photos and videos of victims who are trafficked for
sexual exploitation. This type of technology can also help law enforcement authorities to
analyse tens of thousands of pictures and videos to identify content attributed to a particular
individual.
3. Digital Technology in the Prevention of Economic Offences: Digital Technology can be
efficiently used for the protection of crimes against women and children. Alarms can help
when children or women are trafficked. This can also help against any form of human
trafficking. Police can be immediately alerted through information communication
technologies when such offences happen and they can easily arrest the offenders.
Banks can use AI-based fraud detection software to detect banking fraud and credit card
fraud. Using AI-based systems can help banks lower their risks of being harmed by
fraudulent activities. As per statistics, in 2023, 31% of banks and financial institutions will
use this technology to protect their businesses. Digital technology can help identify people
with low credit scores and thus can help in the prevention of banking fraud. The most
important ways in which AI technology can be used in banking are:
Real-time monitoring: One of this technology’s best uses is analyzing real-time
transactions to detect anomalies and fraudulent attempts. AI excels at seeing patterns and
spotting potential problems as they occur, whereas it would take a human much longer to
identify the same fraudulent practices. This continuous monitoring allows financial
institutions to see threats as they happen instead of after the damage is done, saving time
and money.
Large sets of data: AI-based systems can also assess large data sets to identify synthetic
identities better to prevent application fraud. The more you use AI to evaluate data and
identify fraudulent applications, the smarter it becomes. The ability to search out would-be
application fraud before it happens is a solution AI is uniquely qualified for and can save
valuable resources.
Transactional fraud detection: Last, AI can analyze transaction data to determine any
transactions that fall out of the typical pattern. For example, AI can reject suspicious
transactions or alert banks to investigate them further. This allows for quicker and more
targeted investigations. In turn, AI learns from investigators’ results, allowing it to provide
more accurate information in the future.
Mobile Transaction Fraud Prevention: AI-powered tools can also provide protection
against mobile transaction frauds such as, identity theft, account takeover and friendly
fraud. Real-time, actionable alerts can help to proactively detect transaction fraud. Risk
scores associated with individual transactions can be calculated easily that can help in
preventing frauds. Fraud trend visualization and interpretation can help financial
organizations to optimize the risk management process. Biometric authentication can also
help to reduce such fraud.
Prevention of Credit Card Fraud: Credit card frauds can happen in many ways.
Counterfeit fraud – creating fake credit cards with stolen information.
Lost or stolen card fraud – using a card that has been reported as lost or stolen.
Card not present (CNP) fraud – using stolen card information to make purchases online or
over the phone.
Skimming – stealing card information through a device that reads the magnetic strip.
Phishing – tricking people into revealing their credit card information through fake
websites or emails.
Financial institutions can implement robust risk management policies, procedures and
technologies to help lower the risk of fraud, such as transaction limits, activity monitoring,
biometric authentication, tokenization and more. Most importantly, financial institutions
can use advanced analytics and machine learning algorithms to analyze large amounts of
transaction data, identifying patterns and trends that show fraudulent activity. AI and
machine learning models can use entity analysis and deep learning tools to track enormous
amounts of data to uncover any peculiar transactions or patterns at play.
Law Enforcement: Technology can also be used by law enforcement officials. For
example, biometric citizen identification technology can be used to identify criminals,
double dippers in public welfare distribution schemes, etc. Criminals involved in
transnational schemes such as human trafficking, organ trading etc. can be easily identified
using face recognition technology. Lie detectors can help police officials to identify real
criminals and punish them. Satellite imagery and geospatial mapping—used to identify and
locate remote and high-risk sectors that may be engaged in illegal activity and require
additional investigation.
Abuse of Digital Technology in the Context of Economic Offences
Abuse of Technology in Producing Counterfeit Notes: Economic offenders use technological
advancements such as colour printing, scanning, high-quality printers etc. to produce fake notes
that largely resemble real currency notes. As per the NCRB records, high-quality fake currency
seized in 2020 was more than ₹92.17 crore. Over the last two years, NIA has investigated about
two dozen cases related to fake currency, of which, 12 cases pertain to the seizure of highquality Indian counterfeit currency.
Cybercrimes: Computers and information technology are largely used in committing
cybercrimes, child trafficking, stealing identities and stealing Intellectual property. Phishing is
one of the techniques fraudsters use to steal money from innocent people’s bank accounts.
Malware is also largely used in committing cybercrimes. High-tech criminals use a suite of
malware tools, ranging from banking trojans to ransomware and phishing, to stage their attacks.
Abuse of Computers and Internet in Crimes: Drug offenders may use computers to record
information on their money laundering, trafficking, and other illegal activities. Computers are
also involved in software piracy, black marketeering, and theft of computer equipment. Some
unique problems related to computer crime pertain to intellectual property issues as well.
Criminals also make use of mobile telephones, electronic pagers and electronic ‘mail sorting’
systems to avoid traditional telephone taps. In such cases, new technology is used by
organisations to carry out traditional criminal activities such as drug smuggling or racketeering.
Such types of crimes also include fake lottery games offering huge prizes and provision of nonexisting bank services. The Internet also has provided a means by which fake and nonexistent
educational institutions collect fees from aspiring students and provide them with fake degrees.
Innovations such as ‘electronic purses’ pose a potential danger in the form of electronic money
laundering.
Abuse of Technology in Human Trafficking and Smuggling: Technology is frequently
misused to facilitate human trafficking and smuggling. Perpetrators and their associates
communicate through encrypted applications or use the Dark Web to connect. Recruitment of
victims takes place through fake social media accounts and fake profiles on applications.
Additionally, cryptocurrency allows traffickers to conduct financial transactions and move
criminal proceeds anonymously. Online interaction facilitates the targeting of potential victims,
access to personal data, arrangement of logistics and transportation, and recruitment through
social media. The misuse of technology can also make it easier for traffickers to engage in
transactions with users, enter new marketplaces and expand criminal operations. For example,
with regard to trafficking for sexual exploitation, where women and girls represent 94% of
identified victims globally,6 technology - and specifically the Internet—helps traffickers to
advertise victims and connect more easily with a large market of users. Additionally, large
online platforms hosting advertisements for sexual services provide sex traffickers with the
means to attract customers and, in turn, to sexually exploit victims.
Traffickers may use GPS software in phones to track the movements of victims or, in the case
of domestic servitude and other forms of labour exploitation, monitor and control victims
through video surveillance. In the context of trafficking for sexual exploitation, threats to share
sexually explicit images are used to control victims. Traffickers can also use live-streaming to
reach a broader market of customers who may never have physical contact with the victim.
Abuse of Technology in Organ Trafficking: Criminals use the dark web to facilitate illegal
organ transplants. Agents organize such organ transplants and gather the greater part of the
instalment utilizing cryptocurrency that is now and then directed to finance other criminal
operations. To gather and dispense instalments at abroad areas, they generally resort to money
laundering for finding the money at worldwide spots without being seen by security agencies.
With the ease Internet getting to show up in a portion of the influenced nations, online activities
of organ trading in the hidden world of DW are utilized to wrongfully exchange human vital
body parts. Even medical professionals are involved in such operations.