3.9: AI, DSS, and Automation (Part 2)

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Из курса от партнера The Hong Kong University of Science and Technology

FinTech Foundations and Overview

17 оценок

The Hong Kong University of Science and Technology

FinTech Foundations and Overview

17 оценок

Our primary goal is to help you to understand FinTech and to become more confident and persuasive in your ability to analyze and make recommendations to executives within the finance industry regarding how to react to these changes. This FIRST MOOC ON FINTECH IN ASIA-PACIFIC offered by HKUST presents the views of several professors from the top business school in Asia as well as perspectives from industry professionals. HKUST has been ranked for many years as the number one EMBA program in the world, as the number one Finance program in Asia, and as the top MBA program in Asia by multiple independent rating and review journals and surveys. This course offers the combined strengths of HKUST in Business, Finance, and Technology as one the world's leading academic institutions on an important area of technology and business innovations. For students from outside Asia, this also gives an insight into changes happening in the most advanced FinTech markets of the world, since Asia leads worldwide in FinTech adoption and creative innovations. This course (FinTech Foundations and Overview) is part of the HKUST FinTech specialization, there will be 3 other courses in the specialization including FinTech Security & Regulation (RegTech), FinTech Risk Management, FinTech Innovative Disruption: Implications for Society. The FinTech specialization will be launched in Fall 2018, stay tuned!

Из урока

The Tech of FinTech

The Technology enabling and supporting FinTech is important to understand, and this module provides a brief introduction to each of the areas of technology that enable FinTech business changes, including identity and privacy technologies, blockchain and encryption, big data analytics, AI and automation, and consumer tech innovations. This introduction is designed to be at a level appropriate for business managers or students of business, and is not intended to excite or engage tech geeks.

3.2: Identity, Privacy, and Anonymity (Part 1)9:35

3.3: Identity, Privacy, and Anonymity (Part 2)8:56

3.4: Blockchain and Encryption (Part 1)8:23

3.5: Blockchain and Encryption (Part 2)8:28

3.6: Big Data and Analytics (Part 1)8:03

3.7: Big Data and Analytics (Part 2)8:40

3.8: AI, DSS, and Automation (Part 1)8:46

3.9: AI, DSS, and Automation (Part 2)8:16

3.10: Smartphones & Customer Tech (Part 1)8:54

3.11: Smartphones & Customer Tech (Part 2)6:36

Познакомьтесь с преподавателями

Theodore Henry King CLARK
Associate Professor
Information Systems, Business Statistics and Operations Management Department

What's being automated today using these AI tools or DSS which is new in finance?

I think in the past,

a lot of the automation,

a lot of the so-called computerizations,

they're all focused under the back-end or the middle office of a bank.

So, it helps the banks to improve their operational efficiencies.

Nowadays, I mean, we are talking about a lot of the front-end and user computing,

and the user want to get control of the banking data.

Now of course, the money that I deposit in the bank is definitely in mine.

I want to have control of it.

But in the past, people don't realize that actually,

by spending your credit card,

by doing things online,

I leave a digital trail.

Now, those digital footprint,

does it belong to you or me?

Does it belong to the Internet?

So, you're seeing this is empowering

end users by automating their interface with the banking system.

Even the banks realize that if they could capture

all the digital footprint of all their customers,

then they may be able to understand the customer better than the customer himself.

Let me share something I find interesting about automation.

When we talk about automation in the old days,

the back-end, the things you describe,

who's losing their job due to the computer?

Who's getting fired?

It's basically the bank,

the staff in the bank.

Which staff at the bank? The VP?

No. It's the one.

Clerks?

The clerks, yeah.

People that don't make much money?

Yeah, the reception, yeah,

or maybe some middle management, right?

Maybe a few.

Yeah. Few, yeah.

Who's getting replaced when we are automating our mutual funds,

when we're automating our hedge funds,

when we're automating our investments?

Who is Goldman Sachs laying off today?

Fund managers, right?

How much do they make?

Well.

A lot, right?

Much bigger than you and I.

How?

These are people making a million plus a year losing their jobs because of automation.

This is different from a bank teller losing his or her job.

So, we are now seeing automation not just in banks and other industries as well,

but more and more high value workers are beginning to be replaced by

systems which are doing things that we always used to think only a human could do.

Right.

Only a human can pick stocks.

Only a human can do trading.

Goldman Sachs laying off hundreds of traders.

Traders, yeah.

And hiring many hundreds more, programmers.

Programmers, yeah.

So, a lot of jobs for IT people,

a lot less jobs for people who used to think they can

make good decisions about finance or placing their bets.

We don't need you to place the bets anymore.

We'll place the bets on the horse ourselves or the stock ourselves using the Algo Models.

Yeah.

That's interesting.

That's a new type of automation that reduces cost,

but some of it is a very high salary people.

So, that means even people at the top are being threatened now, right?

Yeah.

Unlike the old days.

Yeah.

Because of they used to be sitting in the top because

they basically generate revenue for the company.

Yeah.

Now, people consider that, "Oh,

a robot is doing better than me."

Yeah.

Robot could be smarter than me, right?

Robotraders beating the best hedge fund managers.

Yeah.

Wow. People like Warren Buffett,

who's really a great stock picker saying, "You know what?

For most of my investments,

I'd use an index fund."

That's impressive.

He's saying, "Give me a robot."

It'll do better than most of the humans who are advising you.

Yeah. But also, I mean,

some people would take it from another perspective.

Let's say, if there's more robots,

and everybody's using robots,

at the end, would human being be able to advance to manage those, right?

Or they actually, they are the designer of those algorithms, right?

I mean, they also catch up as well, right?

Or instead of some of the fiction movies saying that,

robot is controlling humans.

So, now, that's something I think still arguable.

I personally believe that despite that there's a lot of robots in our algorithm around.

I think human are still smart enough to be able to program it.

In the bottom end of the day,

these robots are programmed by people.

Right.

You cannot delegate your stock choices or

your decisions to a computer science guy who doesn't understand finance.

Right.

We still need people who know finance and finance markets.

Right.

We need people who know finance, who know lending,

who know banking, who know insurance, and programming.

Because we want to automate the best experts and lay off the mediocre ones.

Correct. Because I think human,

at the end of the day, you see even today,

a lot of these systems,

they have backdoors, they have backdoors built-in.

Which can be risky.

Is risky, but a lot of people design it in

a way that because when they do system support,

when they lose the super administrators key,

they could go through the backdoors to assess the system to do things. Now of course.

Sometimes you need that.

Yeah, exactly. This is not normal to a lot of general people,

but they have that, especially,

even for very high security system.

Right.

One of the reasons you trust this high security system because there

is another control system to control the backdoor.

If their system has no backdoor,

what happen if somebody,

did the super user's keys lost, or whatever,

then, you lose total control of the system at all.

Before we leave this topic,

let me put in a plug for another course.

We have a course in this series on FinTech talking about compliance and assurance.

Yes.

When you are automated,

when you're using technology to replace people,

you better be able to audit that.

You'd better be in a keep compliance high,

security high, assurance high.

Also recovery. Business contingency bank.

You need something like that.

Exactly.

Because otherwise, you're in deep trouble.

Yeah.

So, that's one of the four courses in this series on FinTech.

This course is the foundations and overview.

We have another course on regulation.

We have of course on implications for society.

But that compliance and assurance is one of the critical things that banks do well

traditionally and FinTech companies probably ought to worry about.

Right. Yeah. That's why some people also propose that,

it's because it's just an emerging field.

The regulators just need a bit of time to get there.

Then, gradually regulation will comes in to regulate the FinTech company as well.

Companies that are startups who don't do compliance and insurance are going to be

dead if something is going to go wrong and they're not going to be able to handle it

Right.

So, it's just a matter of time and you don't want to be the investor

in that and have your company go under.

Right.

All right. So, in summary, AI matters.

Decision support is something that leverages some aspects of AI,

it's a little bit less advanced than AI.

Many people used to talk about expert systems.

We try not to use that term anymore.

Often, we think of assistance or intelligent assistance to help you in your business,

but they are to help you make better decisions.

So, you may still use a person but that person says,

"Is this a good credit risk or not?"

the computer says, "Watch out."

Okay, no thank you.

Automation which is changing because the levels of jobs being replaced tend to be higher,

paid higher value jobs than the ones we were placing in the 1950s and '60s.

So, that's exciting.

It's also challenging, but it means,

if you want to make the big bucks,

you better know not just finance, but also technology.

You must know tech as well as Fin,

if you're going to play in this financial market.

Right.

All right. Well, thank you very much for your time.

Thank you.

Okay.

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