Name: Subject Snapshot | AI at FinovateSpring
Uploaded: 2023-07-12T16:41:45.644Z
Duration: 596.48
Description: Artificial Intelligence: friend or foe to financial services? Here's what the experts think - from how it will transform the labour workforce, to issues with diversity and inclusion, to which sectors of fintech and banking will be most disrupted or improved.

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English

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Artificial intelligence is polarizing

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in the financial technology space.

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For some, it unlocks amazing new

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capabilities, giving us new ways to

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engage customers and incredible new

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capabilities for existing platforms.

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For others, it's terrifying with

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the potential to replace humans

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in key jobs or opening up the

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industry to new sources of risk.

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Let's talk a little bit about how

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it makes the FinTech community feel.

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Excited.

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Excited.

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Inevitable.

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Curious.

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Optimistic.

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The recent Cambrian explosion of

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artificial intelligence has thrust

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this futuristic technology into the

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consciousness of the banking industry.

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But what stage are financial

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services firms at when it comes

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to jumping on the AI bandwagon?

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I think it's super early.

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Anybody that's claiming to really play

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in that space is experimenting at best.

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Those are probably the overachievers,

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but if we remove them for the

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packet for a second most financial

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services organizations do not

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have their data estate in order.

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If you don't have those fundamentals in

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place, there is no way that you're able

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to really take advantage of these tools.

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Coastal Community Banks, SVP

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of Technology, operations and

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Implementation, Barb McLean told us

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how AI automation and machine learning

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could transform the financial services

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labor force in the next 30 to 40 years.

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You don't need an army of

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data scientists to do this.

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Again, we're trying to make the

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tools easy to deploy and use.

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But I think it's actually things

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like critical thinking skills.

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Do I actually trust?

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Or how can I validate the output that

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some of these tools are giving me?

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Creativity, being able to learn

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and willingness to experiment

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that kind of change readiness

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and being resilient to change.

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Those are the things that are actually

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really important for those kind of future

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employees and for our existing employees.

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How do we make sure that

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we bring our teams with us?

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We can't abandon them.

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They got us here, and we need to be able

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to take them on those journeys with us.

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AI petrifies me as a

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civil rights organizer.

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There's no reason why people of color

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who are not going to be involved in

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the testing, right the, data should

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expect to find their lived experience,

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experience in it.

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I have a friend actually who's working on

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you know, creating a common sense database

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and you know, who's common sense, right?

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Who gets to be included.

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And so unfortunately, as we saw

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with tech, it started off with these

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really promises for democratization

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and it still is very much not that.

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And so the scariest thing is companies

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are relying on it so quickly that a lot

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of people are, gonna get lost in that.

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And Rocio Wu, principal at F Prime

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Capital had a word of advice for leaders

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looking to build a team of AI talent.

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So I would say the banks, they have to

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first of all realize, you know, they

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actually have abundant data, they have the

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data supremacy and that they can attract

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a lot of talent to mine the proprietary

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and also private data that's not captured.

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By the large language models

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that only capture public data.

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And the second I think there has to

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happen this organizational willingness

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because AI alone is not enough.

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You need to have a superior ux,

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like a, the whole journey cut, like

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the product discovery to support

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the whole product experience.

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So how can you encourage a

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cross-functional collaboration within

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the banks, you know, which they are

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not known for collaboration or Like

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information sharing, et cetera.

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So how can you instill this

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collaboration and openness culture

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inside the traditional banks?

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I think that would be key to, to observe.

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In the companies that I think have leaned

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in, it's often an individual, like it's

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a leader of a unit, especially in large

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incumbent financial institutions, like

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within large banks or large organizations.

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It's usually an individual who's really

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excited about the possibility and sees

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not just the positive potential, like

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the ability to create new products or

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drive new revenue, but also the cost

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savings potential as well, which is

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especially critical in this environment.

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And so usually takes that

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leader to like champion the idea

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and really bring together the

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leadership team to give it a go.

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And I would contrast that to

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organizations where maybe that leader

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doesn't exist for whatever reason.

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And so I think they're gonna be

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more of the stragglers behind.

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MSU Federal Credit Union's Chief Digital

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Strategy and Innovation Officer Ben Maxim,

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delved into what makes conversational

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AI so beneficial to bank's operational

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efficiency and customer experience.

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So I think the employees, again,

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robot's gonna take my job well.

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We actually have proven out and, I

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think it was really important to stay

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upfront we're not trying to take your

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job, we're trying to take away the

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mundane thing you don't wanna answer.

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Like, what if everyone asks you,

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Hey, what's our routing number?

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Even though it's right next to the,

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button that you push to initiate the chat.

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So, you know, those are the things that

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like, that make you, know, wanna claw

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your eyes out a little bit to answer.

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Well, the chat bot's really good

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at doing that and can do it well.

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The other thing.

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As a credit union, we are not able to

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staff a twenty four seven call center.

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So when we were exploring how to

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extend service hours, you know, we

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were able to, because anyone will ask

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a chat bot what they think it should

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tell them, so we could then turn it on

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overnight and people were asking about

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their cards mostly in the late hours.

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So we don't need a full service call

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center in the middle of the night.

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We just need some help with cards.

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And that was actually a, really cool

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opportunity for us to understand,

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you know, what are our member needs?

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So there's been a lot

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of great opportunity.

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They really like to have the 24 7

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access and feel like they can do

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something and then really start

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exploring, like we do on the internet.

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We go to Google, we figure things out.

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They start with the chat bot, get most

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of the way there, and then when they need

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a person, they're able to get to one.

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The experts also looked into AI

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as an emerging business model in

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the FinTech environment, and how

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best to harness data and AI powered

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decisioning to deliver value.

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The LMS itself, they don't really do

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anything useful on the own, right?

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Yep.

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They have to kind of, they have

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to be used in with, infrastructure

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that makes them valuable.

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Yep.

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And, I think that's you know, almost

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as big a part of it if, not a bigger

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part of it is actually being able to

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really understand what the problem is.

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Yep.

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And, for us, we, which we're an upper

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enterprise in and upper mid market it's,

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complex workflows and a lot of different,

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you know, nuances and permutations.

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Yeah.

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And, you can't just like slap an LLM

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in there and then problem solved.

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Yeah.

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So you gotta have a really good

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understanding of the data and how

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to how to, like we discuss, remove

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biases and, noise from the data.

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Yeah.

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As well as how to operate and train

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and fine tune the LLMs and then put

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them into a, complex business workflow.

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Yeah.

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So I think all of that sort of

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still kind of constitutes mts.

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And, being a fast mover at that versus

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the incumbents, Lawrence Lin Murata

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co-founder and c e o of Slope, a B2B

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payments workflow company elaborated

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on which areas of FinTech could be most

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disrupted by artificial intelligence.

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These spaces where we do a lot of

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manual processes, I think they're

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very ripe for disruption by ai.

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I think especially when you look at

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payments and the back office of payments,

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there's still companies that have a

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large APR or ar team, or they have a

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large finance team operations trying to

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do reconciliation, order tracking, order

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management, and I feel like that space.

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It's gonna be highly automated by ai.

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Daniel Latimore, SVP of Banking at

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Celent, answer the question, will large

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language models change everything?

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You may notice this video is a little off.

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That's because it's from a still

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selfie supplied with a recorded voice.

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It's only going to get

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more convincing over time.

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So that's just one example of generative

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AI that was indeed a selfie taken of me.

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And like I said, it is going to get

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better, but there's more than just

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video and there's more than just

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large language models out there.

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There are huge opportunities, particularly

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as we tune this for financial services.

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In Morgan Stanley, for instance, is

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licensed with open ai, a proprietary

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system, and you can do the standard value

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trifecta of increasing cost reducing

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Reducing cost, increasing

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revenues, mitigating risks,

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but there are threats as well.

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If you give this stuff out in

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the open right now, you are

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giving away your information.

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So do not use PII right now.

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Think of AI or generative AI as this

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nosy neighbor over the back fence,

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really a know-it-all neighbor.

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I generated these images with another

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program for images saying for mid

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journey a know-it-all neighbor

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speaking to me over the back fence.

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You can get some useful information

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from them, but you've always gotta

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filter it and use your own judgment.

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Jas Randhawa managing partner at Strategy

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BRIX touched on the complexities of using

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AI as a financial crime compliance tool.

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The compliance costs have been

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rising over the last couple of years.

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They, the costs have risen to a

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point where it's become prohibitive

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for the growth teams to keep

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funding compliance businesses.

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For us to be more effective and

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more impactful in the larger realm

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of the financial services business,

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we have to bring the cost down and

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the immediate effect of using more

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AI and machine learning solutions

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is to be able to cut a lot of the

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operational volumes that allows us as

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compliance officers then go and focus on

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the higher risk customers that we have.

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So that's gonna be the one major

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impact in the next few years to come.

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Model validation explainability is gonna

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be a huge challenge for implementing

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these systems primarily because the

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regulators fundamentally have been

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very used to seeing rule-based systems,

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which are the conventional systems.

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And these new cutting edge technologies

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are are evolving fairly rapidly.

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So for them to gear up and put out

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some guidance in terms of how these

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systems can be evaluated and explained,

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I think that's a huge hurdle for

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for, us to process an industry.

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Clearly, FinTech is just at the

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beginning of understanding the

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potential of artificial intelligence

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and deciding where to deploy it to

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greatest effect.

{{00:09:41}}
To keep up with this and other

{{00:09:42}}
exciting areas within the FinTech

{{00:09:44}}
space, follow us on Streamly.

really important for those kind of future

employees and for our existing employees.

I have a friend actually who's working on

you know, creating a common sense database

actually have abundant data, they have the

and also private data that's not captured.

FinovateSpring

Expert Insight

Artificial Intelligence: friend or foe to financial services? Here's what the experts think - from how it will transform the labour workforce, to issues with diversity and inclusion, to which sectors of fintech and banking will be most disrupted or improved. 

Technology

Banking

Fintechs

Diversity

Inclusion

Talent management

Fintech

Digital banking

Banking innovation

Banking technology

Community banking

AI finance

Artificial intelligence finance

AI fintech

Artificial intelligence fintech

CX financial services

Customer experience financial services

CX fintech

Customer experience fintech

Fintech startup

Fintech start up

Future fintech

Open banking

Retail banking

Artificial Intelligence

Fintech Solution

Future

Talent

Diversity & Inclusion

Customer Experience

Diversity, Equality & Inclusion

Conversational AI

Chatbots

Talent Acquisition

Inclusivity

banks

Future jobs

Talent strategy, reskilling, upskilling

Diverse talent

Credit unions

ChatGPT

Generative AI

Talent Development

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Jas Randhawa 

Managing Partner

Greg Palmer

Vice President

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Malia Lazu

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Daniel Latimore

Chief Research Officer, Member of the Leadership Team

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Sarah Hinkfuss

Partner

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 Ben Maxim

Chief Digital Strategy & Innovation Officer

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Barb Maclean.jpg

Barb Maclean

SVP, Head of Technology Operations and Implementation

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Lawrence Lin Murata

CEO & Co-Founder

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Alexander Hagerup

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Rocio Wu

Principal

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Subject Snapshot | AI at FinovateSpring

Future of Finance