Page 61 - CMA Journal (July-August 2025)

Focus Section

Professional qualifications are beginning to respond. In Emerging Technologies in Finance
2021, the CFA Institute added fintech and AI modules,
The finance industry is now shaped by a suite of
while GARP included cryptocurrency risks in its FRM
technologies that are fundamentally redefining its
syllabus. ACCA plans a major redesign by 2027, adding
operations:
papers on sustainability, AI, and data science, reflecting
the need for evolving curricula in a rapidly changing • Blockchain and Cryptocurrencies: Beyond Bitcoin
financial landscape. and Ethereum, blockchain powers decentralized
finance (DeFi), non-fungible tokens (NFTs), and smart
Country-level initiatives vary. Singapore has national
contracts. These applications automate transactions,
fintech standards, Estonia mandates blockchain literacy
reduce costs, and eliminate intermediaries. Central
in higher education, and the UK has expanded
banks are also testing CBDCs, which could reshape
fintech-focused degree programs in partnership with
monetary policy.
financial institutions.
• Artificial Intelligence (AI) and Machine Learning:
Industry reports emphasize urgency such as: PwC found
AI algorithms improve fraud detection, credit
80% of firms struggle to recruit fintech talent; Deloitte
scoring, and sentiment analysis. Machine learning
estimates 65% of finance professionals will need
models enhance portfolio optimization and
retraining within five years, and McKinsey projects 90% of
robo-advisory services. These tools require strong
finance roles will require some digital competency.
knowledge of programming, statistics, and data
Challenges remains consistent as faculty often lack governance.
current technology knowledge, textbooks are outdated,
• Data Analytics: Big data enables hyper-personalized
regulatory approvals are slow, and building fintech labs
financial services, from dynamic insurance pricing to
requires significant investment. These factors contribute
predictive credit scoring. Professionals must now be
to a slow, uneven transition toward fintech-oriented
competent in data storytelling, visualization tools, and
finance education.
predictive modeling.
Status Quo of Finance Education
• Cloud Computing: Financial firms increasingly rely
Traditional finance education still prioritizes theories and on SaaS, PaaS, and IaaS platforms, which lower costs
methods developed decades ago. Undergraduate and but introduce new cybersecurity risks. Students
postgraduate students study Discounted Cash Flow must learn about distributed systems, data security,
(DCF) valuation, the Capital Asset Pricing Model (CAPM), and compliance frameworks.
and Modern Portfolio Theory. While important, these
• Internet of Things (IoT): IoT devices generate new
frameworks are no longer fully comprehensive. Payments
forms of financial data. Insurance companies, for
courses focus on legacy systems like checks and SWIFT
instance, now use telematics to calculate car
transfers rather than digital wallets, QR codes, or
insurance premiums based on driver behavior.
blockchain-based settlements. Risk management
Agriculture lenders use IoT sensors to evaluate crop
curricula emphasizes Basel capital requirements but
conditions and lending risks.
often overlook cybersecurity, algorithmic trading risks,
and fintech regulatory challenges. • Open Banking and APIs: By enabling third-party
apps to access bank data, open banking fosters
Professional certifications show similar gaps. The CFA
innovation and competition. Finance professionals
emphasizes equity research and bond valuation, with
need to understand data integration, privacy, and
minimal coverage of Decentralized Finance (DeFi) or
regulatory frameworks like GDPR and PSD2.
blockchain. The FRM does not fully address digital risks
such as cloud infrastructure or cyber threats. Even project These technologies demonstrate that the finance
management qualifications like PMP focus on linear professional of tomorrow must be as comfortable with
methodologies, while fintech projects increasingly rely algorithms and data structures as with balance sheets
on agile, DevOps, and iterative approaches. and financial ratios.
The outcome is a generation of students strong in theory Skills Gap
but weak in practical skills. Few gain exposure to coding
(Python, R, SQL) or data visualization (Power BI, Tableau). Research shows a stark skills deficit in the finance
Blockchain is usually optional, and structured internships profession. Around 85% of finance professionals cannot
in fintech firms are rare, leaving graduates without write a simple program, while only 40% can perform
hands-on experience. This disconnect between basic data analysis. Less than 25% understand blockchain
education and industry needs frustrates both students concepts beyond cryptocurrency trading, and
and employers. knowledge of machine learning is even scarcer.
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