Claim Missing Document
Check
Articles

Found 2 Documents
Search

The Evolution of Financial Technology in Indonesia Albert Manawar; Chandra Lukita; Lista Meria
Startupreneur Business Digital (SABDA Journal) Vol. 2 No. 2 (2023): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v2i2.367

Abstract

Financial technology has its origins in industrialized nations with well-established infrastructure, cutting-edge technology, and a more digitally-oriented populace. Fintech has had trouble entering poor countries and enhancing their financial inclusion, even if this is not the case for emerging nations. This study attempts to identify global fintech best practices and examine how they could enhance the economic well-being of those living in poor nations. We categorized the issues into three categories: a lack of infrastructure, a society that is less digital, and an unorganized and informal culture. Then we looked at Microfinancing, Crowdfunding, Digital payment system as the three fintech’s that best embody the three categories. The development of financial technology began in industrialized countries with advanced infrastructure, cutting-edge technology, and a population that was more accustomed to using digital devices. Even while this is not the case for rising countries, fintech has difficulty reaching poor countries and improving their financial inclusion. This study looks for global fintech best practices and considers how they could improve the economic security of people in developing countries. We divided the problems into three groups: a dearth of infrastructure, a society that uses less technology, and an unstructured and disorganized culture. The three fintech’s that most closely represent the three categories were then examined: Micro Financing, Crowdfunding, Digital payment system.
Simulation-Based Evaluation of Portfolio Optimization Algorithms for Robo-Advisory Systems Chandra Lukita; Meria Zakiyah Alfisuma; Natasha Leonie
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.722

Abstract

This study investigates the performance of portfolio optimization algorithms in robo-advisory systems within the digital finance landscape. The research compares three approaches Modern Portfolio Theory (MPT), Post-Modern Portfolio Theory (PMPT), and a heuristic equal-weight model using a simulation-based computational framework with synthetic financial data under controlled marketconditions. Key evaluation metrics include Sharpe ratio, Sortino ratio, and maximum drawdown to assess risk-adjusted performance and downside protection. The results show that optimization-based models outperform the heuristic approach across all metrics. MPT achieves the highest Sharpe ratio (1.25), indicating strong overall risk-adjusted returns, while PMPT provides superior downside risk management with a higher Sortino ratio (1.60) and lower maximum drawdown (0.14). The heuristic model demonstrates the weakest performance due to its lack of adaptive allocation. These findings highlight the trade-offs between return optimization and risk sensitivity across different algorithms. Despite their effectiveness, the models are limited by reliance on historical data and simplified assumptions in the simulation environment. This study suggests that future robo-advisory systems should integrate artificial intelligence and behavioral finance to enhance adaptability, personalization, and decision transparency in dynamic market conditions.