Launching Upstart’s AI Certification Course

WEBVTT

1
00:00:02.879 --> 00:00:07.320
You are listening to Leaders in Lending
from Upstart, a podcast dedicated to helping

2
00:00:07.360 --> 00:00:13.000
consumer lenders grow their programs and improve
their product offerings. Each week, here

3
00:00:13.039 --> 00:00:17.559
decision makers in the finance industry offer
insights into the future of the lending industry,

4
00:00:18.039 --> 00:00:22.800
best practices around digital transformation, and
more. Let's get into the show,

5
00:00:26.640 --> 00:00:31.039
all right, Welcome back Jeff as
a guest to the podcast. So

6
00:00:31.160 --> 00:00:36.560
Jeff and I are two of the
instructors and an exciting new AI certification course

7
00:00:36.640 --> 00:00:40.799
that Upstart is launching. Happy to
have you back on Leaders Lending, Jeff,

8
00:00:41.119 --> 00:00:44.200
Thank you. What's the saying?
Every does a long time listener,

9
00:00:44.240 --> 00:00:47.719
first time caller, I guess,
longtime host, first time guest. But

10
00:00:48.159 --> 00:00:50.679
it's fun to be back in front
of the microphone, so to speak.

11
00:00:51.359 --> 00:00:54.200
Well, great, Well, I'm
looking forward to talking about the AI certification.

12
00:00:54.280 --> 00:00:57.679
I know we've all been spending a
lot of time working on it internally

13
00:00:57.719 --> 00:01:00.399
and exciting to get it out out
kind of in the public, so,

14
00:01:02.520 --> 00:01:03.560
you know, for any of the
listening, Like, you know, can

15
00:01:03.599 --> 00:01:07.200
you give us some background and like
why did you decide to make this course,

16
00:01:07.319 --> 00:01:10.879
Like what was the what was the
intent ofment, and how did kind

17
00:01:10.879 --> 00:01:14.000
of how did it come about as
an idea? I think, you know,

18
00:01:14.040 --> 00:01:19.000
we kept talking to banks and credit
unions and various people in the industry.

19
00:01:19.000 --> 00:01:21.200
You said, look, the AI
thing is coming and I don't understand

20
00:01:21.239 --> 00:01:25.040
it that well. And it seemed
to us like there was so much educational

21
00:01:25.079 --> 00:01:29.159
content, but it tended to either
be at like fifty thousand feet or five

22
00:01:29.239 --> 00:01:32.319
hundred like either for people wanting to
build models and you quickly go, I

23
00:01:32.319 --> 00:01:36.519
don't understand what this means, or
there was content that was like very how

24
00:01:36.560 --> 00:01:41.599
to use chat GPT to write better
sales emails, and the idea of wanting

25
00:01:41.640 --> 00:01:45.319
to help people better understand at a
business level, at a functional level,

26
00:01:45.599 --> 00:01:48.799
how these things work. Not to
be a to be a developer, but

27
00:01:48.840 --> 00:01:51.760
to be a good consumer, a
good user, a good buyer, or

28
00:01:51.760 --> 00:01:56.000
a good overseer of the models felt
to us like a gap in the good

29
00:01:56.079 --> 00:01:59.079
educational content. That's what we were
hearing from from partners and customers, and

30
00:01:59.120 --> 00:02:00.840
we thought, well, I mean, it seems like something we could do,

31
00:02:00.920 --> 00:02:04.239
and maybe it'd be useful if we
just went out there and tried to

32
00:02:04.280 --> 00:02:07.359
help people better understand this space a
little bit. So that was really once

33
00:02:07.439 --> 00:02:08.879
it was my idea, I think
a number of people and I started,

34
00:02:08.879 --> 00:02:10.919
we're seeing this and said, hey, I wonder if we could do something

35
00:02:12.000 --> 00:02:15.199
valuable and contribute to the space and
help people understand a little bit better.

36
00:02:15.080 --> 00:02:19.919
Sure, so, you know,
I definitely think there's no shortage of at

37
00:02:20.000 --> 00:02:23.560
least content of various levels of AI
out there. But who who's the who

38
00:02:23.639 --> 00:02:27.199
do you see as the ideal user
of this course? Like, what's the

39
00:02:27.319 --> 00:02:32.120
right persona of people who may really
get something out of taking this class from

40
00:02:32.159 --> 00:02:37.479
the team? Yeah, well so
I guess really, really anybody in financial

41
00:02:37.479 --> 00:02:39.719
services, you know, and really
focus on business people. I don't want

42
00:02:39.719 --> 00:02:42.840
to I don't want to start with
who the course isn't for. But we

43
00:02:42.879 --> 00:02:46.360
really didn't want to design a course
that's intendo like how to build a model,

44
00:02:46.439 --> 00:02:49.280
how to pick the right model form. We wanted to say for those

45
00:02:49.319 --> 00:02:52.599
of you who are maybe looking at
an internal team building a model and trying

46
00:02:52.599 --> 00:02:55.039
to understand can this be used in
a process I run or in a program

47
00:02:55.120 --> 00:03:00.520
I manage. Anybody in risk or
compliance or that runs a line of business

48
00:03:00.800 --> 00:03:05.560
within a financial institution or oversees some
functions and wants to be able to ask

49
00:03:05.599 --> 00:03:07.319
better questions understand the model. That's
really what it was for. So really

50
00:03:07.319 --> 00:03:13.080
targeting that community of bankers, of
credit union executives, anybody in the kind

51
00:03:13.080 --> 00:03:15.919
of business side of that who wants
to have a functional understanding of AI,

52
00:03:16.199 --> 00:03:20.400
that's really who we built it for. Not that it's limited to those people,

53
00:03:20.599 --> 00:03:22.759
but if you think about who is
the audience, it's people who are

54
00:03:22.759 --> 00:03:27.240
interfacing with AI models, with teams
building AI models, but aren't people actually

55
00:03:27.240 --> 00:03:30.879
building models themselves. And that was
who we wanted to really empower and educate

56
00:03:30.879 --> 00:03:34.199
through the course. That was our
kind of focus in terms of the audience.

57
00:03:34.960 --> 00:03:38.240
So really to help kind of the
non technical maybe business owners have a

58
00:03:38.240 --> 00:03:43.560
better grasp of the technical background of
what is happening with the AI models and

59
00:03:44.039 --> 00:03:47.479
thinking about how they could use them
to improve or enhance their business. Absolutely,

60
00:03:47.560 --> 00:03:51.080
And if you think about I mean, I hear some people in compliance

61
00:03:51.120 --> 00:03:53.439
that go these teams brought me an
AI model, and like, I don't

62
00:03:53.439 --> 00:03:55.199
know what they're They're using these words
to describe what it is, and they're

63
00:03:55.199 --> 00:03:59.800
not words that I'm familiar with,
or they're described things in different ways.

64
00:04:00.000 --> 00:04:03.360
How do I get a better grasp
on what questions should I be asking or

65
00:04:03.400 --> 00:04:08.039
how do I evaluate if this is
an appropriate model for this use that kind

66
00:04:08.080 --> 00:04:10.360
of thing. We thought, that's
that's the audience we want to empower.

67
00:04:10.400 --> 00:04:13.840
There's a lot of content if you're
building models that's out there, and if

68
00:04:13.840 --> 00:04:15.279
you're kind of a consumer level user
of models, I think there's a lot

69
00:04:15.279 --> 00:04:18.759
of content out there as well.
But at that kind of buyer, overseer,

70
00:04:19.319 --> 00:04:23.079
you know, manager of a function
that's using an AI model in some

71
00:04:23.160 --> 00:04:27.160
way or evaluating one, that's really
the audience we wanted to reach out and

72
00:04:27.439 --> 00:04:31.560
give some better structured content to sure, so kind of the decision maker really

73
00:04:31.600 --> 00:04:35.959
at the business who's going to be
kind of owning the business outputs of these

74
00:04:36.000 --> 00:04:39.000
things. So, you know,
can you give a little bit of an

75
00:04:39.040 --> 00:04:43.800
overview of the kind of maybe the
modules or kind of key learning objectives that

76
00:04:43.839 --> 00:04:47.240
are covered in the certification course.
Yeah, we can go through the modules,

77
00:04:47.240 --> 00:04:49.720
but if I think at a higher
level about what we wanted people to

78
00:04:49.720 --> 00:04:55.040
walk away with, it's really an
understanding of how these models work, how

79
00:04:55.040 --> 00:05:00.680
they're built, how they function internally, how to assess the suitability of a

80
00:05:00.759 --> 00:05:03.720
model for a given purpose? Right, So, not so much so I

81
00:05:03.800 --> 00:05:06.319
use an XG boost model or a
neural in that model. But hey,

82
00:05:06.360 --> 00:05:09.959
given this model, like does it
have the right kinds of inputs, does

83
00:05:09.959 --> 00:05:13.519
it have the right kinds of outputs
of the accuracy metrics on par with what

84
00:05:13.560 --> 00:05:16.079
I might need in this context?
And how do I think about how to

85
00:05:16.199 --> 00:05:18.920
use that model in my world?
What kind of guardrails might I might put

86
00:05:18.959 --> 00:05:23.279
on? So really starting with how
how do the models work? How do

87
00:05:23.360 --> 00:05:27.519
I assess the appropriateness of a model? How do we manage and oversee there's

88
00:05:27.560 --> 00:05:31.079
a whole section with any our chief
compliance officer talking about governance and oversight and

89
00:05:31.160 --> 00:05:35.959
model risk management and all those regulatory
concerns, And then there's there's a little

90
00:05:35.959 --> 00:05:39.199
section at the end where we kind
of get into, like i'll calm brain

91
00:05:39.240 --> 00:05:43.720
ticklers on how is THEI being used
in financial services? What are ideas for

92
00:05:43.759 --> 00:05:46.920
where this might be applied? And
also what can I be doing to help

93
00:05:46.959 --> 00:05:50.920
my organization get ready for an aipower
future? How do I build the foundation?

94
00:05:51.040 --> 00:05:54.519
So kind of running the spectrum from
a little bit. There's a little

95
00:05:54.519 --> 00:05:58.160
bit of technical content in there,
and so we wanted that to be available,

96
00:05:58.240 --> 00:06:00.480
But then there's a lot that builds
on that in terms of how you

97
00:06:00.560 --> 00:06:03.639
manage or oversee or evaluate and assess
a model, and then how's it can

98
00:06:03.720 --> 00:06:08.199
impact financial services? And where do
I think about getting started and building an

99
00:06:08.240 --> 00:06:14.720
organizational capacity to leverage these technologies moving
forward? Hey there, former host Jeff

100
00:06:14.759 --> 00:06:17.959
Kelner here to let you know about
an exciting opportunity to strengthen your understanding of

101
00:06:18.079 --> 00:06:23.759
artificial intelligence and financial services. If
you want to better understand the fundamentals of

102
00:06:23.800 --> 00:06:28.040
how AI models work and how they
will impact the financial services industry, your

103
00:06:28.040 --> 00:06:31.319
in luck. Upstart is launched an
online course and certification designed to do just

104
00:06:31.480 --> 00:06:35.160
that. This course will give you
the knowledge you need to lead the conversation

105
00:06:35.199 --> 00:06:41.519
about how your organization can best leverage
and manage this revolutionary technology. If that

106
00:06:41.600 --> 00:06:45.519
sounds interesting, check out the course
as it's currently free for a limited time.

107
00:06:45.839 --> 00:06:48.839
You can learn more at upstart dot
com slash AI Certification. Again,

108
00:06:48.879 --> 00:06:54.879
that's upstart dot com slash AI Certification. Thanks, and now back to the

109
00:06:54.879 --> 00:06:59.920
show. I definitely think that a
lot of the content really kind of demissed

110
00:07:00.079 --> 00:07:03.759
find some of the areas. So
I think there's a lot of great explanation

111
00:07:03.959 --> 00:07:08.120
of various areas of creating a model
using it and as you said, real

112
00:07:08.279 --> 00:07:11.680
like practical tools. What can you
do with this? How can you use

113
00:07:11.720 --> 00:07:15.879
these these AI models to potentially drive
your business forward or create new opportunities?

114
00:07:16.720 --> 00:07:21.959
So I know where we were doing
the recording and putting the material together.

115
00:07:24.120 --> 00:07:29.560
We had a studio set up in
our office and had a team in uh

116
00:07:29.600 --> 00:07:35.399
recording each of us kind of talking
through our various topics. What was your

117
00:07:35.639 --> 00:07:40.439
experience as an instructor in the course, Like, what did you uh uh,

118
00:07:40.759 --> 00:07:43.560
what did you find interesting about it? Well, I answer, but

119
00:07:43.560 --> 00:07:46.240
I want to hear your answer because
you're you're instructor in this course too.

120
00:07:46.680 --> 00:07:48.439
I mean I got to see the
whole thing, soup tons, which is

121
00:07:48.439 --> 00:07:51.319
I was really involved in structuring a
lot of the content, what are the

122
00:07:51.360 --> 00:07:55.000
things we want to cover, what
should the modules look like? And then

123
00:07:55.040 --> 00:07:58.800
writing a lot of the words.
And it was always surprising to me.

124
00:07:58.920 --> 00:08:01.279
I think it's too funny to if
it's one like reading your own words and

125
00:08:01.279 --> 00:08:03.399
hearing them out loud. The number
of times I got in there and went,

126
00:08:03.439 --> 00:08:07.040
oh my god, that doesn't sound
the way I thought, or the

127
00:08:07.079 --> 00:08:09.680
producers would go, can you give
us another take? Would sound more podcasting

128
00:08:09.800 --> 00:08:13.639
and less professory and I got,
I don't know what that means. I

129
00:08:13.680 --> 00:08:16.920
don't really know how to voice act
in that way. So that was a

130
00:08:18.000 --> 00:08:22.319
really kind of odd experience to be
in there. And then the second really

131
00:08:22.360 --> 00:08:24.399
funny one, and I felt bad
for some of our our Upstart team members

132
00:08:24.399 --> 00:08:26.439
because you know, there was hair
and makeup. You guys got hair and

133
00:08:26.480 --> 00:08:30.079
makeup for the ladies. But the
guys they just brought in a little bit

134
00:08:30.079 --> 00:08:33.159
of foundation for us and there was
no one to apply it. And the

135
00:08:33.519 --> 00:08:35.279
ladies that were looked at me and
go, do you know how to put

136
00:08:35.320 --> 00:08:41.000
makeup on? I said, I
said no. So these poor these poor

137
00:08:41.000 --> 00:08:43.200
people were like a coming in putting
foundation on my face. And they weren't

138
00:08:43.200 --> 00:08:46.480
producers Upstart. You know, Ana
was there, and so they were trying

139
00:08:46.480 --> 00:08:48.799
to get my face to not shine
so much, which I guess I'll have

140
00:08:48.799 --> 00:08:52.120
a problem with. So that was
kind of a funny moment. But I'm

141
00:08:52.120 --> 00:08:56.679
curious what your experience was because you
more got content that had been written,

142
00:08:56.679 --> 00:08:58.720
so you were both reading to some
extent someone else's words, although I'm sure

143
00:08:58.759 --> 00:09:03.080
slightly edited, and then you had
your own experience in studio. Definitely,

144
00:09:03.360 --> 00:09:07.240
I think the you know, it
was interesting reading the scripts, and I

145
00:09:07.279 --> 00:09:11.039
think one of the things that I
learned the most is what sounds and sounds

146
00:09:11.080 --> 00:09:16.200
logical and makes sense on paper.
Things like bullet points are numbered items.

147
00:09:16.600 --> 00:09:20.600
You have to say that a lot
differently as you're talking about it. You

148
00:09:20.639 --> 00:09:24.840
can't just read through it or referring
back to the previous section. That doesn't

149
00:09:24.879 --> 00:09:30.559
work in audio, And so going
through that and you know, rewording things.

150
00:09:30.639 --> 00:09:33.799
And then as you said, the
producers put more inflection on this,

151
00:09:33.039 --> 00:09:37.399
have a little bit more excitement here. And I told them, I'm like,

152
00:09:37.440 --> 00:09:41.399
well, you know, we're all
kind of probably relatively type A in

153
00:09:41.399 --> 00:09:43.600
some ways, we can only be
so exciting. You know, we're not

154
00:09:43.559 --> 00:09:50.159
actors, and the material is pretty
pretty serious. But I think my probably

155
00:09:50.240 --> 00:09:54.879
my favorite one that I think if
you take the course, you'll see me

156
00:09:54.639 --> 00:09:58.639
probably laugh a little bit as I'm
reading it, was it was obviously a

157
00:09:58.679 --> 00:10:03.360
clear Jeff wrote this section of the
script. There's a whole section on a

158
00:10:03.399 --> 00:10:07.399
cal Tech and a fish study done
and and the different i think patterns of

159
00:10:07.759 --> 00:10:11.679
fish migration. As I'm reading this, I'm thinking, I definitely didn't write

160
00:10:11.720 --> 00:10:16.039
this, but I know who wrote
this. Uh, Materials issue of the

161
00:10:16.080 --> 00:10:18.960
cal Tech that gave me away that
I have. Yeah, it was a

162
00:10:18.000 --> 00:10:20.639
little bit of both. And so
I think when I watched the video back,

163
00:10:20.679 --> 00:10:24.799
I see myself kind of laugh as
I'm talking about fish and cal Tech

164
00:10:24.840 --> 00:10:26.519
and like, this is great story. But it was a great analogy,

165
00:10:26.639 --> 00:10:31.840
but definitely not one that that came
to my mind. And you know,

166
00:10:31.879 --> 00:10:37.000
I do think Anna was very excited
and very happy to be there and produce,

167
00:10:37.080 --> 00:10:39.360
so it was it was. It
was a fun time as well as

168
00:10:39.519 --> 00:10:43.679
is just getting really a lot of
really great content out there that I think

169
00:10:43.720 --> 00:10:46.879
will be really, really valuable.
I was surprised how different. I mean,

170
00:10:46.879 --> 00:10:50.000
I've done a lot of presentations in
my day, but usually a lot

171
00:10:50.120 --> 00:10:54.399
and so there's there's no retakes,
there's no hey, you stumbled over these

172
00:10:54.440 --> 00:10:56.159
words? Have you slurred a little
bit? Here? Let's go. And

173
00:10:56.240 --> 00:10:58.960
I was a little i won't say
taken aback, but I was a little

174
00:11:00.200 --> 00:11:03.000
surprise at how often the priestser goes
that was that was all right, but

175
00:11:03.080 --> 00:11:05.120
let's uh, let's try that again. And I'm just not I'm used to

176
00:11:05.120 --> 00:11:09.840
having to deliver once and just live
with the results and being confident with that

177
00:11:09.919 --> 00:11:13.399
delivery, and then having the once
they stop me a few times to go

178
00:11:13.440 --> 00:11:15.720
back and try something again. Then
it got in my head like, man,

179
00:11:15.759 --> 00:11:18.720
you gotta stop doing these stupid things, and then it would happen more

180
00:11:18.759 --> 00:11:20.600
and they go, well, you
know, I think you can do better,

181
00:11:20.759 --> 00:11:22.320
said okay, okay. That was
an interesting It's just a very different

182
00:11:22.320 --> 00:11:26.919
experience than being on a live call
or doing a webinar or speaking at a

183
00:11:26.960 --> 00:11:30.320
conference, where you it just it's
going to be your delivery, is your

184
00:11:30.360 --> 00:11:31.399
delivery, and then it is what
it is, and here they're like,

185
00:11:31.519 --> 00:11:33.360
you know, we can take it
again and do it better with a little

186
00:11:33.360 --> 00:11:39.039
different voice exactly now. And I
think we spent a lot of time sitting

187
00:11:39.080 --> 00:11:43.759
in front of the camera and working
through it. And I think during during

188
00:11:43.799 --> 00:11:46.519
a number of my sessions, there
were we think it was either planes or

189
00:11:46.559 --> 00:11:50.840
construction that kept kept making noise,
and so I'd be talking and then they'd

190
00:11:50.879 --> 00:11:54.120
say hold on and they'd put the
hand up and we'd pause, and we'd

191
00:11:54.120 --> 00:11:58.639
wait about ten minutes until until something
came else came out and h and then

192
00:11:58.679 --> 00:12:03.960
reached art. So definitely takes a
lot longer to get through through something like

193
00:12:05.000 --> 00:12:09.200
that than a just kind of a
live live presentation. But I do think.

194
00:12:09.240 --> 00:12:13.399
I think the content's great, very
excited for it. I think,

195
00:12:13.559 --> 00:12:18.360
are what are you most hoping that
students who take the course, like,

196
00:12:18.720 --> 00:12:22.120
what would you like to see people
take away from it that where they really

197
00:12:22.159 --> 00:12:26.360
feel it adds value? Yeah,
it's I really want people who take the

198
00:12:26.399 --> 00:12:33.120
course to come away feeling empowered to
not just engage intelligently in the conversation about

199
00:12:33.159 --> 00:12:35.679
how and where to use AI and
what the risks are and what the upsides

200
00:12:35.679 --> 00:12:39.600
are, but to really feel empowered
to lead those conversations. I remember when

201
00:12:39.600 --> 00:12:43.480
I first got into AI stuff.
I'd be sitting in the room going,

202
00:12:43.519 --> 00:12:46.440
I don't don't understand what they're saying, and I didn't feel able to contribute

203
00:12:46.480 --> 00:12:48.159
or question. Or I might but
that didn't make sense to me. But

204
00:12:48.440 --> 00:12:52.919
I feel like I don't have enough
background to question what is being said about

205
00:12:52.919 --> 00:12:54.519
this, Or they say this risk
metrics okay, and I go, I

206
00:12:54.559 --> 00:12:58.840
don't see why. But I also
didn't feel comfortable saying saying that in the

207
00:12:58.919 --> 00:13:01.080
room, And so my real goal
is that people walk away going, hey,

208
00:13:01.080 --> 00:13:05.679
I feel informed enough on these topics. When the executive team is discussing

209
00:13:05.679 --> 00:13:09.559
this, or we're debating if this
fraud model is working effectively or not,

210
00:13:09.759 --> 00:13:13.480
or what the risks might be that
I'm informed enough to go and have an

211
00:13:13.519 --> 00:13:16.519
opinion, to ask a smart question, to call in to question something maybe

212
00:13:16.639 --> 00:13:20.879
a technical team is saying. And
really, I mean it feels to me

213
00:13:20.960 --> 00:13:24.039
like an inflection moment in the usage
of AI. And so I want people

214
00:13:24.039 --> 00:13:26.039
to feel empowered to help lead the
charge and how and where to use AI

215
00:13:26.120 --> 00:13:30.480
effectively in financial services. And I
hope that's what they come away from this

216
00:13:30.559 --> 00:13:35.279
course with absolutely so, and I'm
glad we can be part of empowering hopefully

217
00:13:35.399 --> 00:13:39.360
a large audience of people to feel
that and to learn more about AI and

218
00:13:39.919 --> 00:13:43.039
how it can benefit them. So, you know, for anyone who's listening,

219
00:13:43.600 --> 00:13:48.039
where can they go if they want
to find more resources and then enroll

220
00:13:48.120 --> 00:13:50.759
in the course, where can they
go to get that information? Yeah,

221
00:13:50.759 --> 00:13:54.480
So the course just give the real
basics. The course is online video based.

222
00:13:54.480 --> 00:13:56.039
It's a couple of hours long,
I think four or five total hours

223
00:13:56.039 --> 00:13:58.879
of content, but it's broken up
into pretty short videos on the order of

224
00:14:00.039 --> 00:14:03.039
I have the ten minutes that are
very topical, so our goal was digestible,

225
00:14:03.759 --> 00:14:07.559
and then there's a PDF takeaway with
a lot of the key points that

226
00:14:07.639 --> 00:14:11.159
I really push the team to think
of as a job aid, something that

227
00:14:11.200 --> 00:14:15.080
you would have and go, hey, I learned these things. But now

228
00:14:15.320 --> 00:14:16.600
I'm in the moment, I'm in
the meeting. I'm prepping for this meeting

229
00:14:16.600 --> 00:14:20.960
about an AI model, Like what
was that framework for evaluating appropriateness or for

230
00:14:22.120 --> 00:14:24.879
what were those accuracy metrics? And
how to think about it. I want

231
00:14:24.879 --> 00:14:28.399
to have that on my desk to
be ready to really engage in the conversation.

232
00:14:28.519 --> 00:14:31.360
And so a couple of short you
know, got the videos that are

233
00:14:31.759 --> 00:14:35.840
digestible, link the pdf, and
then there's an online community that people have

234
00:14:35.919 --> 00:14:37.320
as well. Will be a LinkedIn
group that you can engage that. We

235
00:14:37.679 --> 00:14:41.080
will have instructors available to ask questions
of if you want to dive deeper or

236
00:14:41.120 --> 00:14:45.919
to understand something. And then our
goal is really community of practice that people

237
00:14:45.960 --> 00:14:48.440
who take the course and are doing
this in the field and running it.

238
00:14:48.519 --> 00:14:50.879
Hey, here's how we talk to
our compliance officer about this. Maybe that'll

239
00:14:50.919 --> 00:14:56.399
work for you, or hey,
i'm struggling with getting a certain stakeholder on

240
00:14:56.440 --> 00:14:58.600
board. Has anybody else seen that? And so we're hoping to really support

241
00:14:58.600 --> 00:15:03.759
that communit. You can find out
about the course at upstart dot com slash

242
00:15:03.840 --> 00:15:07.279
AI certification so you can see the
information register for the course. It's free

243
00:15:07.320 --> 00:15:11.879
for a limited time, so I
recommend if people are interested or find this

244
00:15:11.960 --> 00:15:16.559
topic interesting or useful for themselves,
it's a great time to check it out

245
00:15:16.559 --> 00:15:18.360
because it won't be free forever,
but it is for now. Great Well,

246
00:15:18.399 --> 00:15:24.399
thanks Jeff for joining us today.
I think we're definitely excited for all

247
00:15:24.440 --> 00:15:28.960
of you listening to register and to
learn more about AI alongside our instructors.

248
00:15:30.600 --> 00:15:33.159
Absolutely, it's been a lot of
fun making it, but I think the

249
00:15:33.200 --> 00:15:35.919
real fun starts once it gets out
into the world and we get to start

250
00:15:35.960 --> 00:15:39.039
hearing from actual learners and students and
interacting with the community. So we're very

251
00:15:39.120 --> 00:15:41.759
much looking forward to phase two because
Phase one has been a lot of work

252
00:15:41.960 --> 00:15:43.799
and a lot of fun, but
I think Phase two is going to be

253
00:15:43.799 --> 00:15:46.240
a lot more fun. So we're
looking forward to talking. Everybody wants a

254
00:15:46.279 --> 00:15:50.120
good chance to see all the content. Upstart partners with banks and credit unions

255
00:15:50.120 --> 00:15:54.600
to grow households and expand consumer lending. Through its leading AI lending platform.

256
00:15:56.159 --> 00:16:00.360
Upstart powered banks and credit unions leverage
AI to offer higher prooval rates and experience

257
00:16:00.480 --> 00:16:07.440
lower loss rates while simultaneously delivering the
exceptional digital first lending experience that consumers demand.

258
00:16:07.960 --> 00:16:11.159
Whether you're looking to grow and enhance
your existing personal and auto lending programs,

259
00:16:11.279 --> 00:16:15.919
or you're just getting started, upstart
can help. Upstart offers an end

260
00:16:15.919 --> 00:16:21.080
to end solution that can help you
find more credit worthy borrowers within your risk

261
00:16:21.120 --> 00:16:26.240
profile. With all digital underwriting,
verification, loan closing, and servicing,

262
00:16:26.679 --> 00:16:30.960
It's all possible with Upstart in your
corner. Learn more about finding new borrowers,

263
00:16:30.240 --> 00:16:34.879
enhancing your credit decisioning process, and
growing your business by visiting upstart dot

264
00:16:34.919 --> 00:16:40.399
com slash Lenders. That's upstart dot
com slash Lenders