Silahkan ikuti intruksi di bawah ini:
1. Mengikuti perkuliahan BD307 di Zoom maupun Offline (Absen Hadirkugo)
2. Membaca Materi BD307 – Business Financial Technology yang telah diberikan pada email masing-masing dan mengerjakan Modul 11.
3. Berikan dokumentasi mengenai pengerjaan progress jurnal Business Financial Technology.
4. VLC PKM Orange Box https://www.youtube.com/watch?v=mGOWlkCyEP8
5. Mengerjakan Paper s.d Section Result and Discussion.
Status : 100%
Keterangan : Saya telah mengerjakan tugas dengan baik dan benar
Bukti :
Module 11: Capital Markets and Robo-Advisors
This module explores how fintech is democratizing access to capital markets and investment management. It covers the mechanics of robo-advisors, fractional share investing, and high-frequency trading, analyzing their impact on traditional investment firms and individual investors.
- Suggested Materials:
- Wealthfront or Betterment websites (explore their service offerings).
- Academic paper on the performance of robo-advisors vs. human advisors.
- Online articles on the democratization of investing.
- Checklist of Questions:
- How do robo-advisors make investing more accessible for new investors?
- What are the main advantages and disadvantages of using a robo-advisor?
- Discuss the role of AI in high-frequency trading.
Answer:
- Robo-advisors essentially democratize investing by addressing the key obstacles often faced by beginning investors.
- Key Advantages
- Cheap and Efficient: Low fees result in higher net returns over the long term.
- Objective Decisions: Investment decisions are based purely on data and your risk profile, eliminating the human emotions or biases that often harm investor performance.
- Convenience: The platforms are user-friendly and available 24/7.
Key Disadvantages
- Limited Personalization: Not suitable for highly complex financial planning needs (e.g., estate planning or complicated business tax arrangements).
- Lack of Emotional Support: During a market crisis, they cannot provide the guidance or psychological support needed to prevent an investor from panicking and selling at a loss.
- High-Frequency Trading (HFT) is extremely rapid trading executed in milliseconds, which heavily relies on Artificial Intelligence (AI) and Machine Learning (ML):
- Fast Data Analysis: AI processes real-time market data (in microseconds) to find fleeting trading opportunities.
- Optimal Execution: AI algorithms ensure trading orders are placed and filled at the best time and price, while minimizing the market impact of large orders.
- Rapid Adaptation: AI systems can automatically learn and adjust their trading strategies instantly when market conditions change, making them highly competitive and resilient.
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4. Research Results and Discussion
4.1 AI Effectiveness in Regulatory Interpretation
The results indicate that AI, particularly natural language processing, significantly enhances the ability of financial institutions to interpret complex and unstructured regulatory texts. AI systems are capable of identifying relevant regulatory obligations and mapping them to internal compliance processes more efficiently than manual approaches.
4.2 Impact on Compliance Monitoring and Risk Management
Findings show that machine learning-based monitoring systems improve the detection of compliance risks and anomalies in real time. These systems support proactive risk management by identifying potential violations before they escalate into regulatory breaches.
4.3 Alignment with Research Objectives and Abstract Questions
The results directly address the research objectives outlined in the abstract by demonstrating that AI improves accuracy, speed, and adaptability in navigating complex financial regulatory frameworks. The applied methodology confirms that AI-driven compliance systems reduce operational burden while enhancing transparency, provided that governance and explainability mechanisms are properly implemented.
