金融知識與自動化投資理財顧問服務之使用：以台灣為例

Financial Literacy and Robo-Advisor Adoption: Evidence from Taiwan

研究目的：本文探討金融知識與自動化投資理財顧問服務之使用的關聯性，並主張高主觀金融知識與金融知識過度自信的民眾更傾向於使用自動化投資理財顧問服務。
研究設計／方法：透過台灣金融研訓院與NN IP野村投信金融研究中心於2020年協同合作的國民金融知識調查資料，本文運用邏輯迴歸模型探討金融知識對自動化投資理財顧問服務之使用的影響。
研究結果：實證結果顯示，金融知識與自動化投資理財顧問服務之使用呈現正相關，但這主要是由主觀金融知識所驅動，而非客觀金融知識。另外，金融知識過度自信的受訪者亦傾向自動化投資理財顧問服務，且在年齡較大、較不富裕與非全職學生中更爲顯著。
研究限制／啟發：由於選擇性偏差的存在以及少數受訪者使用自動化投資理財顧問服務引發了對於臺灣民眾金融知識水平的隱憂，未來研究可採用臺灣的人口統計報告針對實際人口數進行更詳盡的研究。另外，本研究旨在探討主客觀金融知識的差異性，而本文之金融知識過度自信的衡量方式與問卷調查的問題設計上仍有不足之處。
理論／實務／社會意涵：自動化投資理財顧問服務可抵消金融知識不足所帶來的不良影響。建議金融機構可採用民眾主觀金融知識來判斷金融產品的適用性，因此提高民眾的金融知識水平乃是至關重要的因素。
創見／價值：金融科技服務的定位是以低成本、減少利益衝突來提供更有效的投資決策。透過降低民眾金融知識的過度自信的問題，金融科技服務將更具有吸引力，使其能夠於金融市場上穩定經營，促進金融創新並加速普惠金融目標的達成。

Purpose–This study aims to examine the correlation between financial literacy and the utilization of robo-advisors, which proposes that high subjective financial literacy and overconfident individuals tend to adopt the robo-advisor services.
Design/methodology/approach–A National Survey is conducted in 2020, which was undertaken by the Taiwan Academy of Banking and Finance and NN Investment Partner & Nomura SITE Financial Research Center in Taiwan. The logistic regression model is utilized to study the effect of financial literacy on robo-advisor adoption.
Findings–The empirical results reveal that robo-advisor adoption positively related to financial literacy, but this is mainly due to subjective instead of objective financial literacy. Furthermore, overconfident individuals tend to use robo-advisors, and this relationship is more pronounced among older individuals, those less wealthy, and non-full-time students.
Research limitations/implications–Since the existence of selection bias and the lack of adoption of robo-advisor services by a few respondents has raised concerns about the financial literacy of Taiwanese individuals, further studies should be conducted on the population using Taiwan’s demographic reports. This study is designed to identify the financial literacy gap between objective and subjective; however, the measurement of financial literacy overconfidence and the design of survey questions are inaccurate.
Practical implications/Social implications–Policymakers should consider that robo-advisors can help reduce the negative consequences of low financial literacy. Financial institutions must be prudent to use subjective financial literacy to judge retail financial products’suitability. Therefore, attempts to improve financial literacy among financial consumers could have a crucial impact.
Originality/value–Positioning FinTech service as providing stronger decision-making at a lower cost with fewer conflicts of interest misses the target demographic completely. We need to work on financial literacy so that people will be more attracted to FinTech services, and they can help people be financially well.