Page 17 - CCFA Journal - Third Issue

CCFF2020/加拿大中国金融论坛 2020
主持人：以上两位嘉宾对未来的挑战抱着很乐观的态度，
那卓女士，从加拿大人的角度来看，您是抱着乐观还是悲
观的态度？假如您是 CIBC 的 CEO，您将如何面对这些挑战？
卓女士：我和前两位嘉宾一样对此都是抱着积极的态度。
我想说既有机遇也有挑战，挑战可能来源于数据，而我们
已经和数据供应商合作，使用他们的服务作为另一个分销
渠道。从基础建设的角度来看，我们与一家全球性科技公
司合作，希望将更多遗留程序转到云端上以更好的节约成
本。在过去几次的金融危机中，加拿大银行业的韧性赢得
了客户的信任，而这种信任是建立在实践基础上的，不会
轻易被打破。如果你从交易的角度来看的话，也存在挑战
和机遇，我们可能会失去一些交易量，但从机会的角度来
看，这是一个建立以关系为基础的现代银行的好方法。
主持人：最后一个问题，韩玫博士，你是如何说服科技人
才加入金融行业？
韩玫博士：我在招人的时候，我总是告诉他们，这就像你
的一个梦想一样，你可以看到人工智能应用正在被应用到
传统的商业公司里。我们都是商业驱动的研究人员，从真
正的商业伙伴那里得到要求和反馈。我们在研究所中建立
和开发算法或机器学习模型，而这些迭代可以推进人工智
能的研究，整个研究社区也会因此受益。
主持人：Touyz 博士，您不仅在第一资本运用数据科学，
而且还是一位教授，建立了一个拥有超 2500 多名本地成
员的数据科学社区，您对那些对数据科学感兴趣的年轻职
场人有什么建议？他们如何学习数据科学？
Touyz 博士：当我在思考数据学科和一些更复杂的科技时，
我会浓缩到 4 或者 5 点。我认为第一个职业建议就是要谦
虚，世界上有很多聪明的人，你总是有学习的机会。第二
点就是活在当下，参与其中。像数据科学这样的东西有很
多机会，我觉得很容易自学到很多东西，但最好的学习方
法是跟他人互动，而不需要成为一名真正的数据科学家。
我和一些产品经理、商业分析师、技术人员以及其他领域
的人有过很多次很好的交流，我也试着去理解他们的问题。
做任何事不管是数据科学、机器学习还是人工智能，总会
有失败的可能，但多一堑,长一智，你要对你所做的事充
满热情。我们往往会陷入很多在这些领域中存在着巨大的
差异化价值的想法中，成功路上总有失败，但是没关系，
只要你对这个过程保有热情。
主持人：卓女士，您有社会科学的背景，在加拿大的年轻
的职场人确实需要多种技能，可能也会面临跨学科学习，
他们如何在未来的数字世界中更好地装备自己，对此您什
么建议呢？
卓女士：我的建议是要抱着一颗开放和好奇的心态。多问
问 题 、 多 与 人 接 触 ， 与 行 业 专 家 保 持 联 系 ， 加 入像
Joshuah 他们的社区。Joshuah ，我考虑明年加入你们社区
（笑）。我对想要进入这个领域的人的建议是，除了要有
技术知识，还需要了解商业环境，比如开放式银行正进入
加拿大，这意味着什么呢？政府正在审核开放式银行又意
味着什么呢？ 除了掌握技术技能以外，了解未来趋势也很
重要。我在招人的时候，看到很多擅长算法的数据科学家
但并不一定擅长编程。编程很重要因为我们经常要处理无
效和不归发的数据，必须通过特征工程来完成，另外高效
建立机器学习项目管理管道也需要很强大的编程技能。所
以如果你充满热情和好奇心，你可以通过很多自学平台学
习和成长。
CCFA JOURNAL OF FINANCE
加中金融
Moderator: Okay. We have two speakers who are very
optimistic about future challenges. Ms. Zhuo, are you
optimistic or pessimistic from a Canadian point of view? How
do you face the challenges if you are sitting in the CEO CIBC
office today?
Ms. Zhuo: First, I will say I am in the same camp as the previous
two speakers. I would say there're both opportunity and challenges.
Challenges can come from the data. Today we are already working
with data vendors and using their services as another distribution
channel. From an infrastructure perspective, we partner with a
global tech company and we are now looking to move more of our
legacy applications to the cloud to achieve higher cost savings.
Canadian banking has earned the trust of its customers because of
this resilience against over several financial crises in the past. I
would say there are also challenges and opportunities if you're
looking from a transactions’ perspective. We might lose some
volume, but from an opportunity’s perspective, it is a great way to
build a relationship based modern bank.
Moderator: Let me ask a final question. Dr. Han, how do you
convince technology talents to join the financial industry?
Dr. Han: When I recruit people, I always tell them it's like a dream
because you can see true AI application being applied to a
traditional business company. We are all business-driven
researchers, we get requests and feedback from real business
partners, (we build and develop) the algorithms or machine
learning models in the lab. These iterations can advance AI
research and benefit the entire research community.
Moderator: Dr. Touyz, you are not only practicing data
science at Capital One but you are also a professor that has
built a data science community which has over 2,500 local
members. What is your suggestion for young professionals
who are interested in data science? How do they learn data
science?
Dr. Touyz: When I think about engaging with data science and
some of these more sophisticated technologies, I'd probably boggle
it down to four or five points. I think the first one is, be humble.
There are so many smart people out there, and there's always an
opportunity to learn. The second thing is, be present and get
involved. There are tons of opportunities out there for things like
data science, but the best way to learn is really to engage with other
people who don't need to be data scientists. A lot of the best
conversations that I've had have really been with folks who are
product managers, business analysts, technologists and in other
fields, and really trying to understand their problems. I think that
we tend to get wrapped up in a lot of these ideas where there's a
tremendous amount of differentiated value of going into these
fields, but to actually be successful, you have to learn that you
won't always succeed and that's okay, (as long as) you have passion
about the journey.
Moderator: Ms Zhuo, you come from a social science
background. What's your advice to young professionals in
Canada? We're talking about cross disciplines and they really
need multiple skill sets. How would you advise young
professionals to better equip themselves in a digital world in
the future?
Ms. Zhuo: I would say be very open and have a curious mindset.
Ask the questions and reach out to people and stay connected with
the industry experts and join communities like Joshuah's. Joshuah,
For folks who wants to go into this field, my suggestion in addition
to having technical knowledge is to also gain knowledge about the
business environment. For example, open banking is coming to
Canada. what does that mean? The government is reviewing it,
what are the implications? So to understand the future is also
important in addition to mastering the technical skills. When I hire
people, I see a lot of data scientists who are good at algorithms, but
they're not necessarily very good at programming. Programming is
very important because we often deal with dirty data. We have to
do feature engineering to fulfill those tasks and be efficient in
building machine learning project pipelines, which all require
strong programming skills. So, if you are passionate and curious -
there are a lot of a self-learning platforms available for you to take
the time to learn and grow yourself.
MARCH 2021 Page 17