如何利用理財機器人協助理專管理長尾客戶

Abstract

近年來因低利率環境，市場瞬息萬變，投資市場波動大幅增加，更凸顯出銀行財富管理的重要性，目前國內銀行每位理專平均約有500位客戶，但熟客僅約100人，同時財管收益貢獻集中於相當少數的客戶，這表示大多數客戶並未得到妥善的金融服務，因應Fin Tech的蓬勃發展，理財機器人的自動再平衡投組或自動提供投組建議的機制，可提升理專之投資理財服務效能並且協助管理理專轄下不熟之長尾客戶。 由個案X銀行的研究與理專問券分析中發現，14%的理財客戶貢獻高達91%的收益，理專平均熟客約109人且每月平均可開發近5位客戶進行投資理財，約70%的理專因為績效不錯或是本身投資過且經驗佳而推薦理財機器人，且高達約75%的理專願意推薦理財機器人之主要原因為公司要求，反而KPI加分的效果不如管理力道有效。同時實際驗證發現，於2019年有購買的理財機器人的理財戶，未來七個月的理財收益年成長為14%，高於全體理財戶的9.5%，表示理財機器人確實有助於理專管理長尾客戶。 本研究認為國內財富管理業務未來有二大發展趨勢，一為理專搭配智能理財之人機協作經營模式，二為大量運用數據的精準行銷以提升理專銷售成效。同時建議銀行應將智能理財建置於理財規劃系統中，讓理專垂手可得相關的銷售工具，並要求智能理財商品配置比例或銷量目標且納入理專獎勵金之財務指標中，才能激勵理專推薦收益低的智能理財商品。

In recent years, low interest rates have led to rapidly changing markets and a significant increase in the volatility of the investment market, highlighting the importance of wealth management banking. At present, financial specialists in domestic banks manage about 500 customers on average, but only have about 100 regular customers. At the same time, revenue contributions are only concentrated in a relatively small number of customers, which means that most customers are not receiving proper financial services. With the the rapid development of Fin Tech, automatic portfolio rebalancing or automatic portfolio recommendation mechanisms of robo-advisors can help financial specialists improve their performance of investment banking services and also help them with managing unfamiliar long-tail customers. According to the case study of Bank X and the questionnaire analysis, this research found that 14% of wealth management customers contributed up to 91% of the bank’s revenue, and that a financial specialist manages around 109 regular customers and develops around 5 new customers on average per month for providing investment banking services. Approximately 70% of financial specialists are willing to recommend robo-advisors because of its good performance or because they have used it in the past and have had good experience. On the other hand, approximately 75% of financial specialists are willing to recommend robo-advisors to their customers mainly due to company requirements, indicating that the impact on KPI improvement is not as effective as management requirements. According to empirical evidence, we also found that those who subscribed to the purchase of a robo-advisor in 2019 saw a 14% annual growth in financial returns over the next seven months, which is higher than the 9.5% growth rate of all wealth management customers. This suggests that robo-advisors can effectively help financial specialists manage long-tail customers. This study has identified two major trends in the future of wealth management business in Taiwan: first, a human-robot collaboration business model where financial specialists work together with robo-advisors; second, precision marketing using large volumes of data to increase sales performance of financial specialists. It is also recommended that banks should build smart wealth management into their financial planning systems so that relevant sales tools can be made readily available to financial specialists. Banks should also make requirements to smart wealth management product allocation ratios or sales targets which should be included in the financial indicators of incentives in order to encourage financial specialists to recommend low-yielding smart wealth management products.