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The world has shifted drastically with the pandemic. With its lingering effects, more people are relying on financial technology with its reliable and contactless transactions to meet their needs. The use of Advanced Analytics and AI in fintech has become critical to ease-of-use and security in the context of AML. Usage of AA and AI allows for risk mitigation as well as cost-efficiency; saving investigators’ time in tracking activity that is seen as a potential threat.
The latest OpenGovLive! Virtual Breakfast Insight on 8 September 2020, looked at how financial institutions from Malaysia can apply real-world AI and advanced analytics applications to ensure a world-class integrated banking system that has comprehensive risk management, efficient fraud anticipation and complete regulatory compliance with an eye on bettering customer experience and improving enterprise profitability.
A comprehensive risk assessment and understanding is a must for financial institutions
OpenGov Asia Group Managing Director and Editor-in-Chief, Mohit Sagar, opened the session by observing that the world has become chaotic and the status quo been disrupted.
In these turbulent times, he stressed it is critical to ask key questions: How do we stay ahead of the curve? How do we keep safe? How do we stay compliant?
These questions become more pertinent and urgent when bad actors are evolving rapidly and becoming increasingly sophisticated.
Being compliant is just the first step. Mere check-box implementation could possibly make organisations more vulnerable as it is a broad, general framework.
Ideally, organisations need to have a comprehensive risk assessment and understanding of their organisation and their context – not an easy nor simple undertaking.
Given the complexity and finesse required, it is best to find the right partners to ease through the process of augmenting a corporate’s existing AML system.
Augmenting and not replacing existing AML capabilities is the priority
After Mohit’s introduction, Managing Director, SAS Malaysia, Cheam Tat Inn, explained that his organisation’s analytics solutions have been used across different parts of the banking landscape.
They have been deployed to enable digital transformation, enhance customer experience, improve risk management and strengthen fraud and security intelligence.
He added that the SAS Solutions optimise and enhance existing AML capabilities and not replace them entirely.
Ahmed Drissi, Anti-money Laundering Lead, APAC, SAS, joined Cheam to give weightage to the need for external expertise. He opined that financial companies need to invest in Machine Learning and AI to automate and speed up the onboarding process.
He showed the delegates a graph that depicted clearly how some regional and tier-1 banks had improved their operational efficiency. Expounding on their proposition, he explained that the SAS Solution had several key capabilities:
- Transaction Monitoring
- Customer Risk Rating/Due Diligence
- Customer screening
- Transaction screening
- AML & CTF Investigation
- Reporting
These key capabilities can be applied to an organisation’s existing AML systems to improve and strengthen its ability to combat financial crimes through advanced analytics.
Entity resolution in the context of AML will help in the reconciliation and gathering of normal multiple data and uncover hidden relationships through the analysis in customer’s attributes. This is important to establish a single view of the customer. It will help investigators have a holistic view of a customer.
Ahmed re-emphasised that SAS’s goal is not to replace existing AML capabilities but to optimise and/or augment them as part of segmentation.
Challenges in AML regulation from an HSBC lens
After Ahmed, Lee Ashmore, Global Head of Anti-Money Laundering Technology & Head of Compliance IT-APAC gave a presentation on the challenges on AML regulation through an HSBC perspective.
Lee explained that customer segmentation models can be complex and can take a long time to develop in HSBC.
He shared that there were problems they encounter when a high number of false positives are flagged while using a rule-based TM that needs to be addressed
Lee was of the opinion that it might be difficult to transition from one system to another in their current situation. Fine-tuning systems are time-consuming and thresholds can be severely impacted by market volatility through external events such as COVID-19.
After these insightful presentations, the virtual insight moved into a time of interaction through OpenGov Asia’s polling session.
On the first question asked the delegates where they were in their current AML journey, close to half (44%) said that they have replaced their current AML solution in the previous year.
While discussing answers, a senior executive from a prominent bank in Malaysia shared that they shared their solution about 2 years ago, but are still facing some challenges including false positives, calibrations etc. He also shared that it is an ongoing journey for them, and they are looking to incorporate AI in their AML solution.
Interestingly, in the last session with Singapore-based delegates, for the same question, 62% answered that they were looking for technology that would complement their existing AML solution.
The second poll question asked if the current AML platform/solution provides real-time screening capabilities. Over 48% confirmed their platforms can only screen transactions by batch while 44% said that their AML platform has real-time screening in place.
A delegate reflected that batch screening is appropriate for more complex non- sanction transactions. But for screening sanctions, it should be done real-time. However, ideally, it would be to have a combination of both which is something new to explore.
The third asked about the main challenges that delegates are facing during the AML investigation process. A majority of them (38%) felt the lack of data/insight around customers, accounts and entities is the main problem.
On this one of the delegates shared an interesting reflection. She shared that the major issue is customer information not being updated. When the information is not updated, the risk profiling and mitigation also turns out to be inaccurate. So even when the claims and transactions are not actually high-risk, they seem suspicious.
On the final question on the extent to which organisations are incorporating AI/ML in their risk and compliance programs, half of our audience (50%) voted that they are still evaluating AI and ML before actually incorporating it.
Ahmed shared that it is good to see that majority of organisations were in different stages of their adoption cycle. They have either already adopted it or are evaluating it to understand its benefits. In the same vein, Ahmed brought the session to a closing where he thanked the delegates for the great insights they had all shared.
He closed by reminding them that AI/ML are not plug-and-play solutions that replace current solutions. They augment existing capabilities and strengthen existing systems. Further, SAS has worked hard to create a way of implementing their solution that can be customised to each organisation’s specific requirements and context.
The entire session, with the deep interaction among delegates and experts, led to an intense time of discovery and learning. Advanced Analytics, AI and AML capabilities can be a great tool in strengthening existing systems to combatting financial cybercrime and fraud – activities that may pose high-risk to customers and that can seriously affect an organisation’s credibility.
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The Department of Information and Communications Technology (DICT) invites all stakeholders, advocates, and concerned individuals to submit feedback, comments, and suggestions on the drafted National Cybersecurity Plan (NCSP) 2023-2028 to provide a safe and reliable cyberspace for all Filipinos.
The goal of the public consultation on the draught of the NCSP 2023-2028 is to improve the final document, which is expected to be released by the end of 2023. All parties interested may offer their suggestions and comments to the Office of the Assistant Secretary for Cybersecurity and Upskilling via email at oascu@dict.gov.ph. The outline NCSP 2023-2028 is organised around six (6) pillars, including:
- Enactment of the “Cybersecurity Act” to strengthen the policy framework;
- Secure and protect Critical Information Infrastructures (CII);
- Proactively defend the government and people in cyberspace;
- Operational and well-coordinated network of Computer Emergency Response Team (CERT) and SOC;
- Capacitate workforce in cybersecurity; and
- Enhancing international cooperation.
Ivan John E. Uy, secretary of the DICT, emphasised the importance of concerted action from all interested parties to create a trusted, dependable, and safe online environment for Filipinos.
“The NCSP 2023-2028 shows the importance of convergence among all government agencies in delivering our mission. It outlines steps on how each government agency can coordinate all their cybersecurity initiatives through the National Cybersecurity Inter-Agency Committee (NCIAC). It also harmonises all organisation CERT and defined two national-level CERTs,” said Secretary Ivan.
He also stated that there was a steady increase in internet-based transactions during and after the COVID-19 outbreak. The country gradually evolved to cashless transactions as electronic commerce and e-banking became commonplace, mostly because of inventions from the private sector. Cybercrime incidences rose as these advanced.
Cyberthreat actors took use of flaws and vulnerabilities in processes, technology, and human behaviour. In response to these changes, the National Cybersecurity Plan 2023–2028 (NCSP 2023–2028) was created.
The goal of DICT is to give every Filipino access to a trusted, secure, and reliable online environment. This demonstrates the necessity of protecting the government and the public online, as well as the significance of fostering the kind of trust required for online commerce to flourish.
The NCSP’s second iteration drew on the preceding strategy’s results while also demonstrating a policy shift. DICT is now attempting to establish a Cybersecurity Act to balance the economic linkages impacting noncompliance with cybersecurity legislation.
The new strategy also promotes policy based on standards and risk-based methods. Individual organisations, rather than entire sectors, are designated as CIIs if they fail, depending on their size and influence. A renewed emphasis on developing the cyber workforce, as well as the significance of improving international collaboration in cybersecurity, was also emphasised.
Most particularly, the NCSP 2023-2028 demonstrates the importance of collaboration among all government departments in carrying out its mandate. It details how each government agency can use the National Cybersecurity Inter-Agency Committee (NCIAC) to coordinate all their cybersecurity initiatives. It also unifies all organisation CERTs and establishes two national-level CERTs.
Though the NCSP 2023-2028 has a sublime goal, DICT thinks this strategy can be successful with the assistance of all government agencies, the private sector, and all departments of government.
The National Cybersecurity Plan must be developed by DICT in accordance with RA 10844, hence, the National Cybersecurity Plan 2028 (NCSP 2028) draft is meant to serve as a guide for consultations, with the goal of using comments to improve the final version of the NCSP, which is scheduled to be released before the end of 2023.
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The Privacy Commissioner, Michael Webster, has issued warnings regarding safeguarding personal information while utilising artificial intelligence (AI), addressing the private and public sectors. In releasing his expectations, Webster emphasised the need for adaptability as technological advancements in AI continue to evolve rapidly.
Webster’s emphasis on organisations exercising caution in handling personal information within the realm of AI highlights the critical need to balance the potential gains in productivity with the inherent privacy risks involved. With the increasing reliance on AI systems like ChatGPT, it becomes crucial to address the challenges associated with managing and controlling the information fed into these systems.
One key concern lies in the difficulty of retrieving information once it has been input into AI systems. Unlike traditional data storage methods, where retrieval is relatively straightforward, AI systems often lack easily accessible mechanisms to retrieve specific information. This poses significant challenges in ensuring the accuracy, integrity, and privacy of the data that has been processed.
Furthermore, the controls governing the usage of personal information within AI systems are often limited in scope. As AI technologies rapidly advance, it becomes imperative to establish robust frameworks and mechanisms to regulate and govern the use of personal data. Without adequate controls, there is a risk of unauthorised access, misuse, or inappropriate handling of sensitive information, leading to privacy breaches and potential harm to individuals.
Webster’s warning reminds organisations to carefully evaluate and address these concerns before implementing AI solutions. Organisations must thoroughly assess AI’s potential risks and implications, especially when handling personal or confidential information. This includes considering the AI system’s privacy impact, security measures, and ethical considerations.
In light of these concerns, Webster emphasised that agencies should conduct comprehensive due diligence and privacy analyses to ensure compliance with the law before venturing into the realm of generative AI. He advised against incorporating personal or confidential information into AI systems unless explicit confirmation is obtained that such data will not be retained or reused. One alternative approach could involve removing any re-identifiable information from input data.
Considering the potential privacy implications, staff members were encouraged to evaluate the necessity and proportionality of using AI and to explore alternative methods if available. Seeking approval from supervisors and privacy officers and transparently informing customers about the use of AI were recommended practices. Additionally, Webster emphasised the importance of human review of any AI-generated information before taking any consequential actions based on it.
Webster further outlined the steps agencies should undertake when considering the implementation of AI. These include conducting due diligence, performing a privacy analysis, and carrying out a Privacy Impact Assessment. Seeking feedback from impacted communities, including Māori, and requesting clarification from AI providers regarding privacy protections designed into their systems were identified as critical components of the evaluation process.
Before this, the commissioner had communicated his concerns to government agencies, cautioning against the hasty adoption of AI without proper assessment. He underscored the need for a holistic, government-wide response to address the emerging challenges posed by this technology.
The Privacy Commissioner’s warnings emphasise the imperative of preserving privacy rights when utilising AI. Organisations must exercise caution, conduct thorough assessments, and implement adequate safeguards to protect personal information in the face of AI’s evolving landscape.
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Although today’s artificial intelligence systems possess immense size and capability, they frequently struggle to differentiate between what is real and what is a hallucination. For instance, autonomous driving systems can fatally overlook pedestrians and emergency vehicles positioned directly in their path. Similarly, conversational AI systems confidently fabricate information and often provide inaccurate assessments of their level of uncertainty, particularly after undergoing reinforcement learning.
However, a collaboration between researchers at MIT and the University of California, Berkeley, has yielded a novel approach to constructing advanced AI inference algorithms. This method enables the algorithms to generate multiple plausible explanations for data while also accurately gauging the quality of these explanations.
The newly developed method utilises a mathematical technique called Sequential Monte Carlo (SMC). SMC algorithms are commonly used for uncertainty-calibrated AI to propose likely explanations for data and assess their plausibility as more information becomes available.
However, SMC falls short when applied to complex tasks due to the simplicity of generating probable explanations. Particularly in challenging domains like self-driving, where analysing video data, identifying objects, and predicting hidden motion paths are involved, sophisticated algorithms are required to make plausible guesses. Regular SMC cannot support such advanced algorithms.
The newly introduced SMC method with probabilistic program proposals (SMCP3) addresses these limitations. SMCP3 enables more intelligent approaches to generate probable explanations for data, update them based on new information, and accurately estimate their quality. Unlike previous versions of SMC, which only allowed simple strategies with calculable probabilities, SMCP3 allows using any probabilistic program that incorporates random choices. This flexibility enables sophisticated guessing procedures with multiple stages, overcoming the previous restriction.
The research paper on SMCP3 demonstrates that employing advanced proposal procedures can enhance the precision of AI systems in tracking 3D objects, analysing data, and improving the algorithms’ estimations of data likelihood. Previous studies conducted by MIT and other institutions have revealed that these estimations can be utilised to infer the effectiveness of an inference algorithm in explaining data compared to an idealised Bayesian reasoner.
George Matheos, the first co-author of the paper and soon-to-be MIT EECS PhD student, expressed great enthusiasm for SMCP3’s ability to enable the practical application of well-established, uncertainty-calibrated algorithms in complex problem scenarios where previous versions of SMC were ineffective.
Today, many new algorithms propose explanations based on data but often lack uncertainty calibration and fail to consider alternatives or assess their explanations. SMCP3 offers the potential to use these algorithms more effectively by incorporating uncertainty calibration, ensuring trustworthy AI systems for reliable and safe decision-making.
Vikash Mansinghka, the paper’s Senior Author, further explains, “Monte Carlo methods have been fundamental in computing and artificial intelligence since the advent of electronic computers.” However, designing and implementing them has always been challenging, requiring manual derivation of mathematical equations and awareness of intricate mathematical constraints. SMCP3 automates these complex mathematical aspects while expanding the range of possible designs.
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Indonesia’s National Consumer Protection Agency (BPKN) is committed to protecting consumers’ interests and ensuring Indonesia’s banking sector’s integrity. In light of the increasing threats posed by cyber-attacks, BPKN recognises the significance of robust security measures, particularly for financial institutions like BSI operating in the realm of Islamic banking.
Mufti Mubarak, the Deputy Head of BPKN, said that the agency is committed to ensuring boosting cybersecurity further. He emphasised that the agency will diligently monitor all cyber incidents until they are resolved.
By asserting its commitment to comprehensive cyber security, BSI demonstrates its dedication to protecting its customers’ confidential information, financial transactions, and the overall integrity of its banking operations. BPKN’s guarantee instils confidence in BSI’s customers and the general public, assuring them that BSI has taken significant measures to fortify its cyber defences.
As technology advances, cybercriminals continue evolving tactics, making it crucial for financial institutions to remain vigilant and proactive in countering potential threats. BPKN’s unwavering vigilance and commitment to overseeing this matter ensures that cyber-attacks targeting BSI will be swiftly addressed and resolved.
The report stated that Indonesia’s cybersecurity index score was 38.96 out of 100 in 2022. This figure places Indonesia as the third lowest among G20 countries. On a global scale, Indonesia ranks 83rd out of 160 countries on the list mentioned in the report. Enhancing cyber security requires significant support and collaboration from relevant stakeholders.
This support is evidenced by the National Cyber and Crypto Agency (BSSN) and the Indonesian ICT Association are recently actively engaged in cybersecurity initiatives. They coordinated a seminar to educate and create awareness about cyber security. The workshop’s objective is to enhance public understanding of the significance of cyber security in the digital era.
The field of cybersecurity has long been confronted with various challenges. In order to establish a strong and resilient cyber security framework, it is crucial for all stakeholders, including the private sector and the government, to collaborate and foster more effective models that can proactively anticipate and mitigate future cyber attacks, which often transpire unpredictably.
Furthermore, the government, through Presidential Regulation Number 53 of 2017 concerning the National Cyber and Crypto Agency (BSSN), and its amendment, Presidential Regulation Number 133 of 2017, established the BSSN. The agency is responsible for effectively and efficiently implementing cybersecurity by utilising, developing, and consolidating all elements related to national cybersecurity.
BPKN’s dedication to upholding the highest standards of cybersecurity is a testament to its role as a consumer protection agency, safeguarding the rights and interests of individuals who entrust their financial well-being to institutions like BSI.
BSSN formulates the Indonesian Cyber Security Strategy as a shared reference for all stakeholders involved in national cyber security. This strategy is a framework for acquiring and developing cybersecurity policies within their respective institutions.
Their commitment to diligently resolving this case demonstrates their tireless efforts and dedication to addressing the emerging challenges posed by the rapidly evolving digital landscape. By proactively tackling these challenges head-on, they strive to foster a resilient and secure banking ecosystem that safeguards the interests of all stakeholders involved.
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Graduates of the Information Technology Programme at the Hong Kong Institute of Vocational Education (IVE) have created a system that uses artificial intelligence (AI) technology to evaluate emotional distress and depression levels, as well as associated risks, by analysing various factors such as the caller’s voice, emotions, and keywords.
Currently, various government departments and social welfare organisations offer mental health helplines and online support services. The “AI Early Depression Screening System” has been specifically developed for individuals seeking emotional assistance and the dedicated counselling volunteers who assist them.
For instance, within this system, counselling volunteers from the organisation can engage in online sessions with those seeking help through the platform. They can access the medical records and past conversation logs of the help-seekers.
As the online conversation begins, the system automatically analyses the caller’s speech tone, voice, and content to gain insights into their emotions. Additionally, the system provides a real-time transcription of the caller’s voice, enabling the identification of specific words used during the conversation.
To train the AI system and analyse the conversation content, the team used the depression research lexicon created by Stanford University, which consists of over 2,000 depression-related keywords. For instance, instances have been observed where single mothers repeatedly use the keyword “useless” to describe themselves. In such cases, the system records the frequency of usage and analyses its association with other words, allowing an estimation to be made that the help seeker may be experiencing emotional distress.
Once the conversation is concluded, the system performs an initial assessment of the social worker’s risk of depression or emotional distress. It displays keywords associated with depression and potential causes of the condition. Additionally, it automatically identifies words related to substance abuse, alcohol, gambling, and self-harm as part of assessing the potential suicidal tendencies of the help-seekers. In conclusion, the system offers mental health guidance and suicide prevention advice while generating reports for further analysis and follow-up by professionals.
A senior lecturer at the Department of Information Technology at IVE (Tsing Yi) and the project’s guiding authority, highlights the convenience and user-friendly nature of the integrated online consultation and intelligent analysis system. The system effectively presents counselling conversation data, aiding in preliminary screening and serving as a reference tool for professional counselling or medical staff. However, he emphasised that the diagnosis and treatment of mental health conditions still require the professional judgment of healthcare and counselling teams.
It is suggested that this system is suitable for mental health institutions, hospitals, clinics, and even insurance companies. The continuation of conversations regularly is encouraged to enable the system to gather more data, thereby improving the accuracy of its analysis. Currently, the system exclusively supports English, but the next objective is to optimise it to accommodate additional languages such as Cantonese and Mandarin.
The system has garnered significant recognition and achievements through participation in various competitions in China and Hong Kong.
IVE’s IT Discipline has developed a comprehensive range of programmes to equip learners with the necessary knowledge and skills to thrive in the fast-paced and ever-evolving career landscape. These programmes cover various domains within the field of Information and Communications Technology (ICT) as well as Multimedia and Entertainment Technology (MET). By offering a wide array of courses, the IT Discipline aims to ensure that learners stay up-to-date with the latest advancements and acquire the relevant expertise required in these dynamic industries.
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Researchers at MIT McMaster University have identified a new antibiotic that can dispatch a type of bacteria responsible for many drug-resistant infections using an algorithm based on machine learning.
If the drug is formulated for patient usage, it could potentially aid in combating Acinetobacter baumannii, a bacterial species commonly present in healthcare facilities and associated with severe infections such as pneumonia, meningitis, and other critical ailments. Furthermore, this microorganism is a primary cause of infections among injured military personnel in Iraq and Afghanistan back then.
Jonathan Stokes, a former MIT postdoc who is now an Assistant Professor of Biochemistry and Biomedical Sciences at McMaster University, explained, “Acinetobacter has the ability to persist on hospital doorknobs and equipment for extended durations, and it can acquire antibiotic resistance genes from its surroundings. It is increasingly prevalent to encounter A. baumannii strains that resist nearly all available antibiotics.”
The scientists employed a machine-learning model to examine approximately 7,000 potential drug compounds and identify the new medication. The model was trained to assess whether a chemical compound could effectively hinder the growth of A. baumannii.
James Collins, the Termeer Professor of Medical Engineering and Science at MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering, said, “This discovery further reinforces the notion that AI has the potential to greatly accelerate and expand our quest for innovative antibiotics. I am thrilled that this research demonstrates the utility of AI in addressing challenging pathogens like A. baumannii.”
During the initial experiment, the researchers educated a machine-learning algorithm to recognise chemical compositions with the potential to impede the growth of E. coli. Employing this algorithm, they screened over 100 million compounds and discovered a molecule called halicin. Their investigations demonstrated that halicin could eliminate not only E. coli but various other bacterial strains that resist conventional treatment methods.
To gather training data for their computational model, the researchers initially exposed A. baumannii cultivated in a laboratory dish to approximately 7,500 distinct chemical compounds to identify those capable of impeding the microbe’s growth. Subsequently, they input the structure of each molecule into the model while providing information regarding whether each structure could inhibit bacterial growth. It enabled the algorithm to grasp the chemical characteristics associated with growth inhibition.
Once the model was trained, the researchers employed it to analyse a set of 6,680 compounds, which had not been previously encountered by the model. This analysis selected several hundred top candidate compounds within less than two hours. Among these candidates, the researchers handpicked 240 for experimental laboratory testing, focusing on compounds possessing distinct structures from existing antibiotics or molecules within the training data.
From the test’s results, the researchers discovered nine antibiotics, one of which exhibited exceptional potency. Interestingly, this particular compound, initially investigated as a potential treatment for diabetes, showcased remarkable efficacy in eliminating A. baumannii while having no impact on other bacterial species such as Pseudomonas aeruginosa, Staphylococcus aureus, and carbapenem-resistant Enterobacteriaceae.
The ability of this antibiotic to exhibit a narrow-spectrum killing effect is a highly desirable characteristic as it reduces the risk of bacteria swiftly developing resistance to the drug. Additionally, this attribute offers the advantage of potentially sparing beneficial bacteria in the human gut, which play a crucial role in suppressing opportunistic infections like Clostridium difficile.
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A seminar aimed at providing IT Security knowledge to public health groups, schools, and government sectors was inaugurated by Mr Siraphop Maneerat, Manager of Central Region Sales and Operations at the National Telecommunication Public Company Limited (NT), and Mr Sanae Kamphaeng, Telecommunications Officer of Prachuap Khiri Khan Province.
The objective of this seminar is to equip IT officers from government agencies, schools, and local government organisations in the province with the necessary knowledge and understanding to safeguard data and mitigate cyber threats.
NT is prepared to offer a range of services and provide guidance in developing plans and budgets to prevent cyber-attack risks that could significantly impact organisational operations and management.
As the National Cyber Security Agency (NCSA) reported, Thailand witnessed a significant surge in cybersecurity threats, from 135 incidents in 2021 to over 772 incidents in 2022. The majority of these incidents involved data breaches, particularly through educational and public sector websites.
According to Mr Sanae, a Prachuap Khiri Khan Province Telecommunications representative, many organisations often neglect the regular maintenance of database security and lack proper protocols for handling cyber threats. In such cases, they require dedicated professionals to manage their systems, as threats continuously evolve, and new vulnerabilities emerge.
The Thai government has been concerned regarding the effectiveness of their organisation’s security protocols in mitigating data leaks. They acknowledge that insufficient personnel can result in significant damage. Seeing this, Thai government legislation, namely the Personal Data Protection Act (PDPA) and some Thai enterprises, passed the Cybersecurity Act in 2019.
The Cybersecurity Act aims to establish legal protections and measures to safeguard cyberspace security. One significant aspect of this act is implementing a cybersecurity risk assessment plan to prevent and address cybersecurity threats that could potentially jeopardise national security and public welfare. These threats encompass the economy, healthcare, international relations, and other governmental functions. The act aims to ensure the stability and integrity of these areas in the face of cybersecurity challenges.
Additionally, the Cybersecurity Act gives the Thai government the authority to monitor and access digital data if it determines that cyber threats pose a risk to the critical digital infrastructure of the country. Private organisations operating in sectors such as national security, financial services, and public services are obligated to provide the names and contact details of key stakeholders who own, use, or possess computer systems, comply with the code of conduct and cybersecurity standards as mandated by law, conduct comprehensive risk assessments, and notify stakeholders about any incidents involving cyber threats.
Basic protection needs to be improved in the current digital landscape, where online threats come in various forms. A comprehensive defence system is crucial. This law and issue is truly new for Thailand itself, so NT allows institutions or even individuals to dig for information regarding cyber security further. “Interested agencies can reach out to the National Telecommunication Company for inquiries and guidance regarding IT Security services,” said Sanae.
Thailand is more serious about bolstering its cybersecurity systems to create a safe environment in a digital era. Supporting this, NT has introduced IT Security services to provide system and equipment security for government and private sector agencies.
