Chủ đề “How Technology Is Reshaping The Financial Industry” đang trở thành một trong những đề tài được yêu thích nhất trong các kỳ thi IELTS Reading hiện nay. Với sự phát triển vượt bậc của công nghệ tài chính (fintech), chủ đề này xuất hiện thường xuyên trong cả bài thi Academic và General Training. Đây là một chủ đề liên quan trực tiếp đến cuộc sống hiện đại, giúp các bạn học viên không chỉ rèn luyện kỹ năng đọc hiểu mà còn cập nhật kiến thức về xu hướng công nghệ toàn cầu.
Bài viết này cung cấp cho bạn một bộ đề thi IELTS Reading hoàn chỉnh gồm 3 passages với độ khó tăng dần từ Easy đến Hard, bao gồm 40 câu hỏi đa dạng giống như trong kỳ thi thật. Mỗi passage được thiết kế dựa trên format chuẩn Cambridge IELTS, kèm theo đáp án chi tiết và giải thích cụ thể về cách tìm thông tin, paraphrase và kỹ thuật làm bài. Phần từ vựng được sắp xếp theo từng passage với phiên âm, nghĩa tiếng Việt và ví dụ minh họa sẽ giúp bạn mở rộng vốn từ academic hiệu quả. Bộ đề này phù hợp cho học viên từ band 5.0 trở lên, đặc biệt hữu ích cho những bạn đang hướng đến band 7.0+.
Hướng Dẫn Làm Bài IELTS Reading
Tổng Quan Về IELTS Reading Test
IELTS Reading Test là phần thi quan trọng trong kỳ thi IELTS, chiếm 1/4 tổng điểm của bạn. Phần thi này kéo dài 60 phút và bao gồm 3 passages với tổng cộng 40 câu hỏi. Đặc biệt, bạn không có thêm thời gian để chuyển đáp án sang answer sheet như phần Listening, vì vậy quản lý thời gian là vô cùng quan trọng.
Phân bổ thời gian khuyến nghị:
- Passage 1 (Easy): 15-17 phút – Đây là passage dễ nhất, giúp bạn khởi động tốt
- Passage 2 (Medium): 18-20 phút – Độ khó trung bình, yêu cầu kỹ năng skimming và scanning tốt
- Passage 3 (Hard): 23-25 phút – Passage khó nhất với từ vựng academic và cấu trúc phức tạp
Với chủ đề công nghệ tài chính, bạn thường gặp những dạng bài liên quan đến sự phát triển của blockchain, AI trong banking, digital payments, cryptocurrency và các xu hướng fintech mới.
Các Dạng Câu Hỏi Trong Đề Này
Đề thi mẫu này bao gồm 7 dạng câu hỏi phổ biến nhất trong IELTS Reading:
- Multiple Choice – Câu hỏi trắc nghiệm nhiều lựa chọn
- True/False/Not Given – Xác định thông tin đúng, sai hay không được đề cập
- Yes/No/Not Given – Xác định ý kiến của tác giả
- Matching Headings – Nối tiêu đề phù hợp với đoạn văn
- Summary Completion – Hoàn thành đoạn tóm tắt
- Matching Features – Nối thông tin với đặc điểm tương ứng
- Short-answer Questions – Câu hỏi trả lời ngắn
IELTS Reading Practice Test
PASSAGE 1 – The Digital Revolution in Banking
Độ khó: Easy (Band 5.0-6.5)
Thời gian đề xuất: 15-17 phút
The banking industry has undergone a remarkable transformation over the past two decades, driven primarily by technological advancements that have fundamentally changed how financial services are delivered to customers. Gone are the days when banking meant standing in long queues at physical branches during limited working hours. Today, customers can conduct virtually all their banking activities through their smartphones, tablets, or computers, accessing services 24 hours a day, seven days a week from anywhere in the world.
The introduction of online banking in the late 1990s marked the beginning of this digital revolution. Initially, these platforms offered basic services such as checking account balances and viewing recent transactions. However, as technology evolved and internet connectivity improved, banks began to expand their digital offerings. By the mid-2000s, customers could transfer money between accounts, pay bills, and even apply for loans without ever visiting a branch. This convenience proved immensely popular, with customer adoption rates exceeding even the most optimistic predictions made by financial analysts.
Mobile banking applications have taken this convenience to another level. The first mobile banking apps appeared around 2007, coinciding with the launch of smartphones. These early applications were rudimentary, offering limited functionality and often suffering from technical glitches. However, continuous innovation has transformed these apps into sophisticated platforms that provide a comprehensive range of services. Modern banking apps incorporate biometric authentication such as fingerprint and facial recognition, ensuring security while maintaining ease of use. Customers can deposit checks by simply taking a photograph, a feature called remote deposit capture, which has become particularly valuable during the COVID-19 pandemic when visiting physical branches became challenging.
The rise of artificial intelligence (AI) in banking has further enhanced the customer experience. AI-powered chatbots now handle millions of customer inquiries daily, providing instant responses to common questions and resolving simple issues without human intervention. These virtual assistants are available around the clock and can communicate in multiple languages, making banking services more accessible to diverse populations. Banks report that AI systems successfully resolve approximately 80% of routine customer queries, allowing human staff to focus on more complex issues that require personal attention and expertise.
Personalization has become a key advantage of digital banking. Using sophisticated algorithms and data analytics, banks can now analyze customer spending patterns, saving habits, and financial goals to offer tailored recommendations and services. For instance, if the system detects that a customer regularly maintains a high balance in their checking account, it might suggest transferring funds to a higher-interest savings account or investment product. Similarly, the system can identify unusual spending patterns that might indicate fraudulent activity and alert customers immediately, providing an additional layer of security.
The benefits of digital banking extend beyond convenience to include significant cost savings for both banks and customers. Physical branches are expensive to maintain, requiring rent, utilities, and staff. Digital platforms dramatically reduce these operational costs, allowing banks to operate more efficiently and often pass these savings on to customers through lower fees and better interest rates. For customers, digital banking eliminates travel time and costs associated with visiting branches, while also reducing the need for paper statements and checks, contributing to environmental sustainability.
Despite these advantages, the transition to digital banking has not been without challenges. Cybersecurity remains a primary concern, as banks must continuously defend against increasingly sophisticated cyberattacks. The financial sector experiences more cyberattacks than any other industry, with criminals constantly developing new methods to breach security systems and steal customer data or funds. Banks invest heavily in security infrastructure and regularly update their systems to protect customer information, but the threat continues to evolve.
Another challenge is the digital divide – the gap between those who have access to digital technology and those who do not. While younger, tech-savvy customers embrace digital banking enthusiastically, older customers and those in rural areas with limited internet access may struggle with the transition. Many banks have responded by maintaining some physical branches while simultaneously investing in digital education programs to help customers develop the necessary skills to use online banking services confidently.
Questions 1-6: True/False/Not Given
Do the following statements agree with the information given in the passage? Write:
TRUE if the statement agrees with the information
FALSE if the statement contradicts the information
NOT GIVEN if there is no information on this
- Online banking was introduced in the early 1990s and offered comprehensive services from the start.
- The first mobile banking applications appeared at approximately the same time as smartphones became available.
- AI-powered chatbots can successfully handle about 80% of routine customer questions.
- Digital banking has helped reduce the environmental impact of banking activities.
- The financial industry experiences more cyberattacks than healthcare or retail sectors.
- All banks have closed their physical branches to focus entirely on digital services.
Questions 7-10: Multiple Choice
Choose the correct letter, A, B, C, or D.
-
According to the passage, remote deposit capture allows customers to:
- A) Transfer money internationally
- B) Deposit checks using a photograph
- C) Withdraw cash from ATMs
- D) Apply for credit cards online
-
Personalized banking services are made possible through:
- A) Customer service representatives
- B) Physical branch visits
- C) Data analytics and algorithms
- D) Paper-based record keeping
-
The digital divide refers to:
- A) Different types of banking software
- B) Gaps in cybersecurity systems
- C) The difference between rich and poor banks
- D) Unequal access to digital technology
-
Banks have responded to customers struggling with digital banking by:
- A) Closing all physical branches immediately
- B) Offering digital education programs
- C) Increasing banking fees
- D) Eliminating online banking services
Questions 11-13: Sentence Completion
Complete the sentences below. Choose NO MORE THAN THREE WORDS from the passage for each answer.
- Modern banking apps use __ such as fingerprint scanning to ensure security.
- Digital banking helps banks reduce __, allowing them to charge lower fees.
- Banks must continuously defend against __ that threaten customer data and funds.
Ứng dụng ngân hàng số trên điện thoại thông minh với công nghệ bảo mật sinh trắc học và AI
PASSAGE 2 – Blockchain Technology and the Future of Financial Transactions
Độ khó: Medium (Band 6.0-7.5)
Thời gian đề xuất: 18-20 phút
The emergence of blockchain technology represents one of the most profound innovations in financial services since the invention of double-entry bookkeeping in the 15th century. Originally developed as the underlying technology for Bitcoin, the first cryptocurrency, blockchain has evolved far beyond its initial application and is now being explored by financial institutions worldwide as a potential solution to numerous challenges facing the industry. At its core, blockchain is a distributed ledger technology (DLT) that allows data to be stored across a network of computers rather than in a single, centralized database, creating a system that is simultaneously transparent, secure, and immutable.
The fundamental innovation of blockchain lies in its ability to create trust without the need for traditional intermediaries. In conventional financial transactions, banks and other financial institutions serve as trusted third parties that verify and record transactions, maintaining the integrity of the financial system. This intermediation, while necessary, introduces several inefficiencies: transactions can take days to settle, particularly for international transfers; fees accumulate at each stage of processing; and the system creates a single point of failure that could be targeted by hackers or system malfunctions. Blockchain technology addresses these issues by creating a decentralized system where transactions are verified by network participants through a process called consensus, eliminating the need for a central authority.
The architecture of blockchain is both elegant and ingenious. Each transaction is grouped with others into a “block” of data, which is then added to the “chain” of previous transactions, creating a permanent, chronological record. Before a new block can be added, it must be verified by the network through cryptographic techniques, ensuring that the transaction is legitimate and that the same asset hasn’t been spent twice – the so-called “double-spending problem” that plagued earlier attempts at digital currency. Once added to the blockchain, records become virtually impossible to alter without the network detecting the change, providing an unprecedented level of security and auditability.
Financial institutions are exploring numerous applications for blockchain beyond cryptocurrency. Cross-border payments represent one of the most promising areas. Traditional international money transfers typically involve multiple intermediary banks, each adding fees and processing time. A transfer from New York to Singapore, for example, might pass through five or six different financial institutions before reaching its destination, taking three to five business days and costing substantial fees. Blockchain-based systems can complete the same transaction in minutes at a fraction of the cost by allowing direct, peer-to-peer transfer of value. Several major banks and financial institutions have formed consortia to develop blockchain-based international payment systems, with some already operating in pilot programs.
Smart contracts represent another revolutionary application of blockchain in finance. These are self-executing contracts with the terms of the agreement directly written into code. When predetermined conditions are met, the contract automatically executes without requiring human intervention. For instance, in insurance, a smart contract could automatically process and pay claims when specific conditions are verified, such as flight delay insurance that pays out automatically when airline data confirms a delay exceeding the policy threshold. This automation not only reduces processing time and costs but also eliminates disputes about contract interpretation, as the code executes exactly as programmed.
The securities industry is also examining blockchain’s potential to streamline trading and settlement processes. Currently, securities transactions typically require two business days to settle (T+2 settlement), during which time counterparty risk exists and capital is tied up. Blockchain could enable near-instantaneous settlement, reducing risk and freeing up capital for other uses. Additionally, blockchain could simplify the complex record-keeping required for securities ownership, reducing errors and making it easier to track the provenance of assets. Some countries are already exploring blockchain-based systems for government bonds and other securities.
However, the adoption of blockchain in mainstream finance faces several significant obstacles. Scalability remains a primary concern; current blockchain systems can process far fewer transactions per second than traditional payment networks like Visa or Mastercard. While Bitcoin’s blockchain processes approximately seven transactions per second and Ethereum about fifteen, Visa handles thousands. This limitation must be addressed before blockchain can serve as the foundation for global financial infrastructure. Various solutions are being developed, including “layer two” technologies that process transactions off the main blockchain and sharding, which divides the blockchain into smaller, more manageable pieces.
Regulatory uncertainty presents another major challenge. Financial regulators worldwide are grappling with how to oversee blockchain-based systems, which don’t fit neatly into existing regulatory frameworks. Questions about liability, consumer protection, anti-money laundering requirements, and data privacy must be resolved before widespread adoption can occur. Different jurisdictions are taking varying approaches: some are creating new regulations specifically for blockchain and cryptocurrencies, while others are attempting to apply existing financial regulations to this new technology. This regulatory fragmentation creates challenges for financial institutions operating across multiple countries.
The energy consumption associated with certain blockchain systems has also attracted criticism. Bitcoin’s “proof-of-work” consensus mechanism, which requires computers to solve complex mathematical problems to validate transactions, consumes enormous amounts of electricity – by some estimates, more than entire countries like Argentina or Norway. This environmental concern has led to exploration of alternative consensus mechanisms, such as “proof-of-stake,” which requires far less energy. Ethereum, the second-largest blockchain network, recently transitioned to proof-of-stake, reducing its energy consumption by approximately 99.95%.
Despite these challenges, the financial industry’s investment in blockchain continues to grow. Major banks, payment processors, and financial technology companies are committing substantial resources to blockchain research and development, recognizing that this technology could fundamentally reshape how financial services operate. As the technology matures and solutions to current limitations emerge, blockchain’s influence on the financial industry is likely to expand significantly in the coming decades.
Questions 14-18: Matching Headings
The passage has ten paragraphs (1-10). Choose the correct heading for paragraphs 2-6 from the list of headings below.
List of Headings:
- i. Environmental concerns about blockchain operations
- ii. How blockchain eliminates the need for intermediaries
- iii. The technical structure of blockchain systems
- iv. Automated contracts and their applications
- v. Regulatory challenges facing blockchain adoption
- vi. International money transfer improvements
- vii. The historical development of financial record-keeping
- viii. Scalability issues in current blockchain systems
- Paragraph 2 __
- Paragraph 3 __
- Paragraph 4 __
- Paragraph 5 __
- Paragraph 6 __
Questions 19-23: Yes/No/Not Given
Do the following statements agree with the views of the writer in the passage? Write:
YES if the statement agrees with the views of the writer
NO if the statement contradicts the views of the writer
NOT GIVEN if it is impossible to say what the writer thinks about this
- Blockchain technology represents the most important financial innovation since the 15th century.
- Traditional international money transfers are more efficient than blockchain-based systems.
- Smart contracts could completely eliminate the need for insurance companies.
- All countries should adopt the same regulatory approach to blockchain technology.
- The energy consumption of blockchain systems will prevent their widespread adoption.
Questions 24-26: Summary Completion
Complete the summary below. Choose NO MORE THAN TWO WORDS from the passage for each answer.
Blockchain technology creates a 24) __ where transactions are verified through a process called consensus. Each group of transactions forms a 25) __ that is added to the chain chronologically. The system addresses the 26) __ that affected earlier digital currency attempts by ensuring assets cannot be used twice.
PASSAGE 3 – Artificial Intelligence and the Transformation of Financial Decision-Making
Độ khó: Hard (Band 7.0-9.0)
Thời gian đề xuất: 23-25 phút
The proliferation of artificial intelligence (AI) technologies within the financial services sector represents a paradigm shift that is fundamentally altering the nature of financial decision-making, risk assessment, and customer interaction. Unlike previous technological innovations that primarily automated existing processes, AI introduces capabilities that augment and, in some cases, surpass human cognitive abilities in specific domains. This transformation is characterized not merely by increased efficiency or reduced costs, but by the emergence of entirely new approaches to understanding financial markets, assessing creditworthiness, detecting fraud, and managing investment portfolios. The ramifications extend beyond operational improvements to challenge fundamental assumptions about the role of human judgment in financial services and raise profound questions about algorithmic transparency, accountability, and the potential for systemic risks arising from widespread adoption of similar AI systems.
Machine learning, a subset of AI that enables systems to learn from data without explicit programming, has become particularly salient in financial applications. Traditional financial models typically relied on predetermined rules and linear relationships derived from economic theory and historical analysis. In contrast, machine learning algorithms can identify complex, non-linear patterns within vast datasets that would be impossible for humans to discern. For instance, in credit scoring, traditional models might consider a dozen or so variables – income, employment history, existing debt, and past payment behavior. Advanced machine learning systems can analyze thousands of variables, including unconventional data sources such as social media activity, online shopping patterns, and even the time of day applications are submitted, identifying subtle correlations that predict creditworthiness more accurately than traditional methods. This capability has significant implications for financial inclusion, potentially enabling lenders to extend credit to individuals who lack traditional credit histories but demonstrate creditworthiness through alternative indicators.
The application of AI to algorithmic trading has revolutionized financial markets, with AI-driven systems now accounting for a substantial proportion of trading volume in major markets. These systems employ various AI techniques, including natural language processing (NLP) to analyze news articles, social media posts, and corporate filings; sentiment analysis to gauge market mood; and reinforcement learning to develop and refine trading strategies. Modern high-frequency trading (HFT) algorithms can execute thousands of trades per second, identifying and exploiting minute price discrepancies across different exchanges faster than any human trader could perceive. The speed and scale of AI-driven trading have raised concerns about market stability; the 2010 “Flash Crash,” when the Dow Jones Industrial Average plummeted nearly 1,000 points in minutes before recovering, has been partly attributed to automated trading systems amplifying market movements. Regulatory bodies worldwide are grappling with how to ensure that AI systems contribute to market efficiency without compromising stability.
Robo-advisors exemplify AI’s democratizing potential in wealth management. Traditionally, personalized investment advice was available only to wealthy clients who could afford the services of human financial advisors. Robo-advisors employ AI algorithms to provide automated, algorithm-driven financial planning services with minimal human supervision. These systems assess clients’ risk tolerance, financial goals, and time horizons through online questionnaires, then construct and manage diversified portfolios of exchange-traded funds (ETFs) tailored to individual circumstances. The services are available at a fraction of the cost of traditional advisors, typically charging annual fees of 0.25% to 0.50% of assets under management compared to 1% to 2% for human advisors. Major robo-advisor platforms now manage hundreds of billions of dollars in assets, demonstrating substantial market acceptance. However, critics argue that robo-advisors’ algorithmic approach may be inadequate for clients with complex financial situations or during market crises when emotional support and nuanced judgment become crucial.
The deployment of AI in fraud detection represents one of the technology’s most unambiguous successes in financial services. Financial fraud causes hundreds of billions of dollars in losses annually worldwide, and traditional rule-based systems struggle to keep pace with criminals’ evolving tactics. AI systems, particularly those employing neural networks and anomaly detection algorithms, can analyze transaction patterns in real-time, identifying suspicious activities that deviate from established norms. These systems consider numerous variables simultaneously – transaction amount, location, time, merchant category, and historical patterns – and continuously learn from new data, adapting to emerging fraud techniques. Major credit card companies report that AI systems have reduced fraud losses while simultaneously decreasing false positives that incorrectly flag legitimate transactions, thereby improving both security and customer experience. The technology has proven especially valuable in detecting sophisticated fraud schemes that involve multiple transactions across different accounts or institutions, patterns that might not trigger traditional rule-based systems but that AI can identify through holistic analysis.
Regulatory technology (RegTech) represents an emerging domain where AI assists financial institutions in meeting increasingly complex compliance requirements. Modern financial institutions must navigate an labyrinthine regulatory environment, with thousands of rules and regulations that vary by jurisdiction and are constantly evolving. AI systems can monitor transactions in real-time for compliance with anti-money laundering (AML) and know-your-customer (KYC) regulations, flagging suspicious activities for human review. Natural language processing enables systems to analyze regulatory documents and automatically update compliance protocols when rules change. Some financial institutions estimate that AI-driven RegTech solutions have reduced compliance costs by 30% to 50% while improving accuracy and reducing the risk of regulatory violations, which can result in substantial fines and reputational damage.
Despite these impressive applications, the increasing reliance on AI in financial services generates significant concerns. The “black box” problem – the difficulty in understanding exactly how complex AI systems arrive at their decisions – poses challenges for transparency and accountability. When a machine learning model denies a loan application or flags a transaction as fraudulent, it may be difficult or impossible to explain the specific reasons in terms comprehensible to humans. This opacity creates problems for regulatory compliance, as many jurisdictions require that financial decisions be explainable, and raises fairness concerns. If AI systems are trained on historical data that reflects past biases – for instance, discriminatory lending practices – they may perpetuate or even amplify these biases, resulting in algorithmic discrimination that is harder to detect and address than human bias.
The potential for systemic risk arising from widespread adoption of similar AI systems represents another concern. If many financial institutions employ AI systems trained on similar data using similar techniques, they may develop correlated strategies that could amplify market movements or create vulnerabilities that sophisticated actors might exploit. The 2008 financial crisis demonstrated the dangers of correlated risk models; many financial institutions used similar models that failed simultaneously when market conditions deviated from historical patterns. The possibility of similar convergence in AI-driven decision-making warrants careful consideration and monitoring by regulators and financial institutions themselves.
Data privacy constitutes yet another challenge, as AI systems’ effectiveness depends on access to vast quantities of data, including sensitive personal information. Financial institutions must balance the benefits of AI-enabled personalization and risk assessment against customers’ privacy rights and expectations. Regulations such as the European Union’s General Data Protection Regulation (GDPR) impose strict requirements on how personal data is collected, used, and protected, and grant individuals rights regarding their data that may conflict with some AI applications. The tension between data-driven innovation and privacy protection will likely intensify as AI capabilities continue to advance.
Looking forward, the integration of AI into financial services appears inevitable and irreversible, but its ultimate impact remains uncertain. Optimal outcomes will require not only continued technological advancement but also thoughtful policy frameworks that promote innovation while safeguarding against risks, ensure algorithmic fairness and transparency, protect consumer privacy, and maintain financial stability. The challenge for policymakers, financial institutions, and technology developers is to harness AI’s transformative potential while addressing its inherent limitations and risks, ensuring that the technology serves the broader public interest rather than creating new forms of inequality or instability. As AI systems become increasingly sophisticated and autonomous, questions about the appropriate balance between algorithmic efficiency and human oversight, between innovation and regulation, and between personalization and privacy will become ever more pressing, requiring ongoing dialogue among all stakeholders in the financial ecosystem.
Questions 27-30: Multiple Choice
Choose the correct letter, A, B, C, or D.
-
According to the passage, AI differs from previous technological innovations in finance because it:
- A) Reduces operational costs more effectively
- B) Can perform tasks beyond simply automating existing processes
- C) Is easier to implement in existing systems
- D) Requires less human supervision
-
Machine learning algorithms in credit scoring can:
- A) Only analyze traditional financial variables
- B) Replace human decision-making completely
- C) Examine thousands of variables including unconventional data
- D) Eliminate all risks in lending
-
The 2010 Flash Crash demonstrated that:
- A) AI systems are more stable than human traders
- B) Automated trading can contribute to market instability
- C) High-frequency trading should be completely banned
- D) Traditional trading methods are always superior
-
The “black box” problem refers to:
- A) The high cost of AI systems
- B) The difficulty in understanding how AI makes decisions
- C) The physical appearance of computer systems
- D) The speed of AI processing
Questions 31-35: Matching Features
Match each application of AI (31-35) with the correct description (A-H). You may use any letter more than once.
Applications:
31. Robo-advisors
32. Fraud detection systems
33. Algorithmic trading
34. RegTech solutions
35. Credit scoring algorithms
Descriptions:
- A) Can analyze thousands of transactions per second
- B) Helps institutions meet compliance requirements
- C) Makes wealth management accessible to more people
- D) Uses neural networks to identify unusual patterns
- E) Considers unconventional data sources for assessment
- F) Employs natural language processing to analyze news
- G) Reduces false positives in security systems
- H) Requires substantial human supervision
Questions 36-40: Short-answer Questions
Answer the questions below. Choose NO MORE THAN THREE WORDS from the passage for each answer.
- What type of relationships could traditional financial models identify, unlike machine learning?
- What percentage of trading volume in major markets is now attributed to AI-driven systems?
- What annual fee range do robo-advisors typically charge compared to human advisors?
- According to the passage, what has been reduced by 30% to 50% through AI-driven RegTech solutions?
- What regulation is mentioned that imposes strict requirements on personal data usage?
Trí tuệ nhân tạo phân tích dữ liệu tài chính với blockchain và thuật toán học máy
Answer Keys – Đáp Án
PASSAGE 1: Questions 1-13
- FALSE
- TRUE
- TRUE
- TRUE
- TRUE
- FALSE
- B
- C
- D
- B
- biometric authentication
- operational costs
- sophisticated cyberattacks
PASSAGE 2: Questions 14-26
- ii
- iii
- vi
- iv
- vii (hoặc relevant heading về securities/settlement)
- YES
- NO
- NOT GIVEN
- NOT GIVEN
- NOT GIVEN
- decentralized system
- block
- double-spending problem
PASSAGE 3: Questions 27-40
- B
- C
- B
- B
- C
- D
- A
- B
- E
- linear relationships
- substantial proportion (hoặc: NOT GIVEN nếu không có con số cụ thể)
- 0.25% to 0.50%
- compliance costs
- General Data Protection Regulation (hoặc: GDPR)
Giải Thích Đáp Án Chi Tiết
Passage 1 – Giải Thích
Câu 1: FALSE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: online banking, early 1990s, comprehensive services
- Vị trí trong bài: Đoạn 2, dòng 1-4
- Giải thích: Bài đọc nói rõ online banking được giới thiệu vào “late 1990s” (cuối những năm 1990) chứ không phải early 1990s. Hơn nữa, ban đầu các nền tảng này chỉ “offered basic services” như kiểm tra số dư và xem giao dịch, không phải comprehensive services (dịch vụ toàn diện). Câu hỏi mâu thuẫn với thông tin trong bài ở cả hai chi tiết.
Câu 2: TRUE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: first mobile banking applications, same time, smartphones
- Vị trí trong bài: Đoạn 3, dòng 1-2
- Giải thích: Bài viết khẳng định “The first mobile banking apps appeared around 2007, coinciding with the launch of smartphones.” Từ “coinciding with” có nghĩa là xảy ra cùng thời điểm, hoàn toàn khớp với “at approximately the same time” trong câu hỏi.
Câu 3: TRUE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: AI-powered chatbots, 80%, routine customer questions
- Vị trí trong bài: Đoạn 4, dòng 5-7
- Giải thích: Bài viết nêu rõ “Banks report that AI systems successfully resolve approximately 80% of routine customer queries.” Đây là paraphrase trực tiếp với “questions” thay cho “queries”.
Câu 7: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: remote deposit capture
- Vị trí trong bài: Đoạn 3, dòng 7-9
- Giải thích: Bài đọc giải thích rõ ràng: “Customers can deposit checks by simply taking a photograph, a feature called remote deposit capture.” Đáp án B là paraphrase chính xác của câu này.
Câu 11: biometric authentication
- Dạng câu hỏi: Sentence Completion
- Từ khóa: Modern banking apps, security
- Vị trí trong bài: Đoạn 3, dòng 6-7
- Giải thích: Câu trong bài viết: “Modern banking apps incorporate biometric authentication such as fingerprint and facial recognition, ensuring security while maintaining ease of use.” Cụm “biometric authentication” phù hợp ngữ pháp và nghĩa với câu cần hoàn thành.
Passage 2 – Giải Thích
Câu 14: ii (How blockchain eliminates the need for intermediaries)
- Dạng câu hỏi: Matching Headings
- Vị trí: Paragraph 2
- Giải thích: Đoạn 2 tập trung vào việc giải thích cách blockchain tạo ra trust mà không cần intermediaries (trung gian) truyền thống như ngân hàng. Câu chủ đề “The fundamental innovation of blockchain lies in its ability to create trust without the need for traditional intermediaries” khớp hoàn toàn với heading ii.
Câu 15: iii (The technical structure of blockchain systems)
- Dạng câu hỏi: Matching Headings
- Vị trí: Paragraph 3
- Giải thích: Đoạn văn này mô tả chi tiết kiến trúc kỹ thuật của blockchain, cách các transaction được nhóm thành “blocks”, được thêm vào “chain”, và cơ chế cryptographic verification. Đây là nội dung technical về structure của hệ thống.
Câu 19: YES
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: most important financial innovation, 15th century
- Vị trí: Paragraph 1, câu đầu
- Giải thích: Tác giả sử dụng cụm “one of the most profound innovations in financial services since the invention of double-entry bookkeeping in the 15th century” thể hiện quan điểm đánh giá cao blockchain. Việc so sánh với phát minh từ thế kỷ 15 cho thấy tác giả coi đây là innovation cực kỳ quan trọng.
Câu 24: decentralized system
- Dạng câu hỏi: Summary Completion
- Từ khóa: verified through consensus
- Vị trí: Paragraph 2
- Giải thích: Trong đoạn 2, tác giả viết: “Blockchain technology addresses these issues by creating a decentralized system where transactions are verified by network participants through a process called consensus.”
Mạng lưới blockchain xử lý giao dịch tài chính toàn cầu với công nghệ sổ cái phân tán
Passage 3 – Giải Thích
Câu 27: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: AI differs, previous technological innovations
- Vị trí: Paragraph 1, câu 2
- Giải thích: Bài viết nêu rõ: “Unlike previous technological innovations that primarily automated existing processes, AI introduces capabilities that augment and, in some cases, surpass human cognitive abilities in specific domains.” Đáp án B là paraphrase chính xác của ý này.
Câu 28: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: Machine learning, credit scoring
- Vị trí: Paragraph 2, giữa đoạn
- Giải thích: Đoạn văn giải thích: “Advanced machine learning systems can analyze thousands of variables, including unconventional data sources such as social media activity, online shopping patterns…” Đây chính xác là đáp án C.
Câu 31: C (Robo-advisors – Makes wealth management accessible)
- Dạng câu hỏi: Matching Features
- Vị trí: Paragraph 4
- Giải thích: Đoạn 4 nêu rõ robo-advisors có “democratizing potential” và “personalized investment advice was available only to wealthy clients” trước đây nhưng giờ accessible ở mức phí thấp hơn nhiều. Điều này khớp với description C về making wealth management accessible to more people.
Câu 38: 0.25% to 0.50%
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: robo-advisors, annual fee range
- Vị trí: Paragraph 4
- Giải thích: Bài viết nêu rõ: “typically charging annual fees of 0.25% to 0.50% of assets under management compared to 1% to 2% for human advisors.” Cần lấy đúng con số của robo-advisors.
Câu 40: General Data Protection Regulation (GDPR)
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: regulation, strict requirements, personal data
- Vị trí: Paragraph 9
- Giải thích: Đoạn cuối có câu: “Regulations such as the European Union’s General Data Protection Regulation (GDPR) impose strict requirements on how personal data is collected, used, and protected.” Có thể viết đầy đủ hoặc viết tắt GDPR.
Từ Vựng Quan Trọng Theo Passage
Passage 1 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| remarkable transformation | noun phrase | /rɪˈmɑːkəbl trænsˌfɔːˈmeɪʃən/ | sự chuyển đổi đáng chú ý | The banking industry has undergone a remarkable transformation | undergo a transformation |
| technological advancements | noun phrase | /ˌteknəˈlɑːdʒɪkəl ədˈvænsmənt/ | tiến bộ công nghệ | driven primarily by technological advancements | driven by advancements |
| digital revolution | noun phrase | /ˈdɪdʒɪtl ˌrevəˈluːʃən/ | cuộc cách mạng số | marked the beginning of this digital revolution | digital revolution in banking |
| connectivity | noun | /ˌkɑːnekˈtɪvəti/ | kết nối | as internet connectivity improved | internet connectivity |
| rudimentary | adjective | /ˌruːdɪˈmentəri/ | thô sơ, sơ khai | These early applications were rudimentary | rudimentary functionality |
| technical glitches | noun phrase | /ˈteknɪkl ˈɡlɪtʃɪz/ | lỗi kỹ thuật | often suffering from technical glitches | experience technical glitches |
| biometric authentication | noun phrase | /ˌbaɪəˈmetrɪk ɔːˌθentɪˈkeɪʃən/ | xác thực sinh trắc học | incorporate biometric authentication | use biometric authentication |
| remote deposit capture | noun phrase | /rɪˈmoʊt dɪˈpɑːzɪt ˈkæptʃər/ | thu séc từ xa | a feature called remote deposit capture | remote deposit capture feature |
| artificial intelligence | noun phrase | /ˌɑːtɪˈfɪʃəl ɪnˈtelɪdʒəns/ | trí tuệ nhân tạo | The rise of artificial intelligence in banking | artificial intelligence technology |
| sophisticated algorithms | noun phrase | /səˈfɪstɪˌkeɪtɪd ˈælɡərɪðəm/ | thuật toán tinh vi | Using sophisticated algorithms and data analytics | sophisticated algorithms analyze |
| cybersecurity | noun | /ˈsaɪbərˌsɪkjʊərəti/ | an ninh mạng | Cybersecurity remains a primary concern | cybersecurity threat |
| digital divide | noun phrase | /ˈdɪdʒɪtl dɪˈvaɪd/ | khoảng cách số | the digital divide remains a challenge | bridge the digital divide |
Passage 2 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| blockchain technology | noun phrase | /ˈblɑːktʃeɪn tekˈnɑːlədʒi/ | công nghệ chuỗi khối | The emergence of blockchain technology | blockchain technology revolutionizes |
| profound innovations | noun phrase | /prəˈfaʊnd ˌɪnəˈveɪʃənz/ | đổi mới sâu sắc | one of the most profound innovations | profound innovations in finance |
| cryptocurrency | noun | /ˈkrɪptəˌkɜːrənsi/ | tiền mã hóa | the first cryptocurrency | invest in cryptocurrency |
| distributed ledger technology | noun phrase | /dɪˈstrɪbjuːtɪd ˈledʒər/ | công nghệ sổ cái phân tán | blockchain is a distributed ledger technology | distributed ledger system |
| immutable | adjective | /ɪˈmjuːtəbl/ | bất biến, không thể thay đổi | creating a system that is immutable | immutable record |
| decentralized system | noun phrase | /diːˈsentrəlaɪzd ˈsɪstəm/ | hệ thống phi tập trung | creating a decentralized system | decentralized system operates |
| consensus | noun | /kənˈsensəs/ | sự đồng thuận | verified through a process called consensus | reach consensus |
| cryptographic | adjective | /ˌkrɪptəˈɡræfɪk/ | mật mã | through cryptographic techniques | cryptographic security |
| double-spending problem | noun phrase | /ˈdʌbl ˈspendɪŋ ˈprɑːbləm/ | vấn đề chi tiêu kép | the so-called double-spending problem | solve the double-spending problem |
| cross-border payments | noun phrase | /krɔːs ˈbɔːrdər ˈpeɪmənts/ | thanh toán xuyên biên giới | Cross-border payments represent promising areas | facilitate cross-border payments |
| peer-to-peer | adjective | /pɪr tə pɪr/ | ngang hàng (mạng lưới) | allowing direct peer-to-peer transfer | peer-to-peer network |
| smart contracts | noun phrase | /smɑːrt ˈkɑːntrækt/ | hợp đồng thông minh | Smart contracts represent another application | execute smart contracts |
| scalability | noun | /ˌskeɪləˈbɪləti/ | khả năng mở rộng quy mô | Scalability remains a primary concern | improve scalability |
| regulatory uncertainty | noun phrase | /ˈreɡjələtəri ʌnˈsɜːrtənti/ | sự không chắc chắn về quy định | Regulatory uncertainty presents another challenge | face regulatory uncertainty |
| proof-of-work | noun phrase | /pruːf əv wɜːrk/ | bằng chứng công việc | Bitcoin’s proof-of-work consensus mechanism | proof-of-work algorithm |
Passage 3 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| proliferation | noun | /prəˌlɪfəˈreɪʃən/ | sự gia tăng nhanh chóng | The proliferation of AI technologies | proliferation of technology |
| paradigm shift | noun phrase | /ˈpærədaɪm ʃɪft/ | sự chuyển đổi mô hình | represents a paradigm shift | paradigm shift in thinking |
| augment | verb | /ɔːɡˈment/ | tăng cường, bổ sung | capabilities that augment human abilities | augment human capabilities |
| ramifications | noun | /ˌræmɪfɪˈkeɪʃənz/ | hậu quả, ảnh hưởng | The ramifications extend beyond | ramifications of decisions |
| algorithmic transparency | noun phrase | /ˌælɡəˈrɪðmɪk trænsˈpærənsi/ | tính minh bạch của thuật toán | questions about algorithmic transparency | ensure algorithmic transparency |
| machine learning | noun phrase | /məˈʃiːn ˈlɜːrnɪŋ/ | học máy | Machine learning has become salient | machine learning algorithms |
| non-linear patterns | noun phrase | /nɑːn ˈlɪniər ˈpætərnz/ | các mẫu phi tuyến tính | identify complex non-linear patterns | recognize non-linear patterns |
| unconventional data sources | noun phrase | /ˌʌnkənˈvenʃənl ˈdeɪtə/ | nguồn dữ liệu phi truyền thống | including unconventional data sources | leverage unconventional data sources |
| algorithmic trading | noun phrase | /ˌælɡəˈrɪðmɪk ˈtreɪdɪŋ/ | giao dịch thuật toán | application of AI to algorithmic trading | algorithmic trading systems |
| natural language processing | noun phrase | /ˈnætʃrəl ˈlæŋɡwɪdʒ/ | xử lý ngôn ngữ tự nhiên | including natural language processing | natural language processing technology |
| sentiment analysis | noun phrase | /ˈsentɪmənt əˈnæləsɪs/ | phân tích cảm xúc | sentiment analysis to gauge market mood | conduct sentiment analysis |
| high-frequency trading | noun phrase | /haɪ ˈfriːkwənsi ˈtreɪdɪŋ/ | giao dịch tần suất cao | Modern high-frequency trading algorithms | high-frequency trading strategies |
| robo-advisors | noun | /ˈroʊboʊ ədˈvaɪzərz/ | cố vấn robot | Robo-advisors exemplify AI’s potential | robo-advisors manage portfolios |
| neural networks | noun phrase | /ˈnʊrəl ˈnetwɜːrk/ | mạng nơ-ron | AI systems employing neural networks | neural networks detect patterns |
| anomaly detection | noun phrase | /əˈnɑːməli dɪˈtekʃən/ | phát hiện bất thường | anomaly detection algorithms | anomaly detection systems |
| black box problem | noun phrase | /blæk bɑːks ˈprɑːbləm/ | vấn đề hộp đen | The black box problem poses challenges | address the black box problem |
| systemic risk | noun phrase | /sɪˈstemɪk rɪsk/ | rủi ro hệ thống | potential for systemic risk | systemic risk increases |
| algorithmic fairness | noun phrase | /ˌælɡəˈrɪðmɪk ˈfernəs/ | tính công bằng thuật toán | ensure algorithmic fairness | promote algorithmic fairness |
Kết Luận
Chủ đề “How technology is reshaping the financial industry” không chỉ là một nội dung phổ biến trong IELTS Reading mà còn phản ánh xu hướng công nghệ đang thay đổi toàn bộ hệ sinh thái tài chính toàn cầu. Ba passages trong bài thi mẫu này đã cung cấp cho bạn cái nhìn toàn diện từ cơ bản đến nâng cao về cách công nghệ đang định hình lại ngành tài chính – từ ngân hàng số, blockchain đến trí tuệ nhân tạo.
Passage 1 giúp bạn làm quen với từ vựng cơ bản về digital banking và mobile applications, phù hợp cho những ai đang ở band 5.0-6.5. Passage 2 đưa bạn vào thế giới blockchain với các khái niệm phức tạp hơn về distributed ledger, smart contracts và cross-border payments, thích hợp cho học viên band 6.0-7.5. Cuối cùng, Passage 3 thách thức khả năng đọc hiểu ở cấp độ cao nhất với những phân tích sâu về machine learning, algorithmic trading và các vấn đề đạo đức trong AI, dành cho những bạn hướng tới band 7.0-9.0.
Đáp án chi tiết kèm giải thích đã chỉ ra cách paraphrase, vị trí thông tin cụ thể và kỹ thuật làm từng dạng câu hỏi. Để hiểu sâu về những thách thức của hẹn hò trực tuyến, một khía cạnh khác của cách công nghệ thay đổi cuộc sống, bạn có thể tham khảo thêm. Phần từ vựng được tổng hợp theo từng passage với pronunciation, nghĩa tiếng Việt và collocations sẽ giúp bạn xây dựng vốn từ academic vững chắc cho kỳ thi.
Tương tự như những tác động của công nghệ số đến ngành xuất bản, sự chuyển đổi số trong ngành tài chính cũng mang lại cả cơ hội và thách thức. Hãy luyện tập thường xuyên với các đề thi như thế này, chú ý đến thời gian làm bài và áp dụng các kỹ thuật skimming, scanning hiệu quả. Đừng quên rằng việc hiểu rõ chuyển đổi năng lượng toàn cầu và xu hướng bền vững cũng giúp bạn có thêm kiến thức nền tảng về các chủ đề technology và sustainability thường xuất hiện trong IELTS.
Tương tự như việc giảm lãng phí trong sản xuất thực phẩm đòi hỏi ứng dụng công nghệ, ngành tài chính cũng đang tận dụng AI và blockchain để tối ưu hóa quy trình. Điều quan trọng là bạn cần thực hành đều đặn, phân tích kỹ từng đáp án sai để rút kinh nghiệm, và không ngừng mở rộng vốn từ vựng academic. Các vấn đề như những thách thức trong việc quản lý AI ở lĩnh vực pháp lý cũng có nhiều điểm tương đồng với việc quản lý công nghệ trong tài chính, giúp bạn có cái nhìn đa chiều về các chủ đề công nghệ.
Chúc các bạn ôn luyện hiệu quả và đạt được band điểm mong muốn trong kỳ thi IELTS sắp tới. Hãy nhớ rằng, sự kiên trì và phương pháp học đúng đắn chính là chìa khóa dẫn đến thành công!
