Resources > Data Jam Sessions and Podcasts > ON-DEMAND WEBINAR: How Financial Services Institutions Can Drive Account Growth

ON-DEMAND WEBINAR: How Financial Services Institutions Can Drive Account Growth

April 28, 2022 by Segmint & Passerelle

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Learn how digital transformation drives new business, improves customer service, and responds to changing marketplace demands. Hear from Peter Love, Chief Digital Officer at Berkshire Bank, about Berkshire’s ongoing 5-year digital transformation project. With its digital transformation, Berkshire has achieved data independence – moving beyond the constraints of an external data warehouse and making data assets available to business users throughout the organization.

This video also shows how 3rd party and enriched 1st party datasets are easily accessible to organizations of any size with the Snowflake Data Marketplace. Lastly, see an overview of Data Rocket, an end-to-end acceleration architecture that modernizes data infrastructure and delivers critical business insights – securely and accessibly. Built with Talend’s Data Fabric and the Snowflake Data Cloud, Data Rocket™ spurs adoption through IP, integrations and blueprints. Data Rocket connects data to custom dashboards in PowerBI or Tableau, putting visual analytics and real-time reporting in the hands of decision-makers throughout an organization and supporting ML and AI applications.

Transcript

• [8:12] Digital Transformation at Berkshire Bank
• [29:50] Supercharging Your Data Cloud with [29:50] Equifax and [40:00] Segmint
• [48:45] Data Rocket
• [59:00] Q&A

0:16
my name is carolyn fernald i'm the marketing director at pastoral pastoral is a data systems integrator
0:22
and we're the developer of data rocket a modern data stack for financial services which we'll talk a little bit about
0:27
later um with me today i have bruce amano
0:34
the business director at passerelle eric tressler a senior vice president at equifax and greg spencer the senior
0:40
sales and solution engineer at segment most importantly we have peter love the
0:45
chief digital officer at berkshire bank who's helping to spearhead a five-year digital transformation at the bank and
0:51
is going to tell us all about what he and his team have learned um bruce and greg and eric and peter can
0:57
you turn your cameras on please thank you [Music] i'd like to thank our friends and
1:03
technology partners at talland for helping to sponsor this event attendees who registered with their corporate email addresses can look
1:10
forward to the wine or snack gifts you selected at registration and i'll get those in the mail tomorrow
1:16
i'm going to take the attendance report at the end of this webinar so please stick with us to the end if you'd like to receive your gift
1:22
also we'd like this event to be as interactive as possible so please submit your questions and we'll try to insert
1:28
them into the discussion throughout we're going to start off our presentation today with bruce atomano
1:34
pastoral's business director who'll help set the stage for why we're here and why we care about digital transformation in
1:40
the first place thanks carolyn nice to meet you everyone
1:45
as carolyn mentioned i'm bruce odomano i'm the business director for passorelle and if i were to put it in one sentence
1:52
today's webinar is about how to drive revenue and efficiencies by deeply knowing your customers
1:59
to best serve them so i want to i want to touch on three things here and describe
2:06
the challenges to build that customer picture
2:11
three things come to mind first of all covid19 has acted as a catalyst
2:16
there was already a shift taking place from customers coming to the traditional brick and mortar
2:22
branches and regional offices to conduct business folks were searching for new channels
2:29
and that shift to mobile online alternate channels it was across all generations
2:37
from baby boomer boomers myself to gen x to millennials
2:43
and the second point is this change is here to stay based on a recent survey
2:50
more than 30 percent will continue to use these alternate channels as the way they want to interact with you as a
2:56
financial institution and so behaviors for shopping online versus
3:02
showing up in person coming to a financial institution for advice to
3:07
discuss needs and select products and and using alternate payment methods
3:12
other than cash or checks that's going to continue on long beyond when covid19 starts fading away in the
3:19
rearview mirror and that's applying pressure it's applying pressure on financial
3:24
institutions because there's a need to deeply know your customer most
3:31
clients most customers have multiple financial institution relationships they have deposits in multiple banks they
3:38
maybe have a separate entity that's they're doing investment work with and those financial institutions
3:45
that work hard to most deeply know their customers are going to grow share
3:51
are going to grow their revenue at the expense of those organizations that don't work hard to deeply know their customers
4:00
and that needs to be enabled by digital banking carolyn next slide
4:06
digital banking is challenging it's not easy to do and today's outdated technologies are
4:14
not rising to the occasion there's four core components of building
4:19
building a digital banking platform first is assembling the customer picture
4:26
data about a customer is stuck in siloed systems on bruce i maybe have five
4:31
thousand dollars of deposits showing up in jack henry a core banking account and maybe i've taken a mortgage in
4:37
encompass and you know i have a hundred thousand dollar you know first mortgage and i show up there
4:43
but there's bits and pieces of me scattered throughout all the transactional systems and if i want to use that data it's
4:49
stuck in those silos and even if i could get it out of those silos and throw it in a lake throw the data in
4:56
one place to have it be usable has to be made trusted
5:02
is the bruce that has five thousand dollars deposits in jack henry the same bruce that took the hundred thousand
5:08
dollar mortgage or is it two bruces each bruce having one relationship with
5:13
the bank and to make data trusted it can't possibly be the subject matter
5:20
expert of every data set in a bank there needs to be the business involved
5:26
signing off as a data steward a business analyst that most
5:32
closest to the data knows the data know whether it's accurate or not and so it's business working with it to make data
5:38
trusted that's hard to do with today's tooling third if i can land all the data master
5:45
it make it shaped make it trusted i only know what i know based on my
5:50
interactions with my customers how do i know if bruce is a multi-millionaire or not
5:56
he has five thousand dollars in my deposit account that's all i know about him what's his net worth
6:02
who is bruce do i really know bruce or am i just getting a portion of his business because if i can know bruce
6:08
more deeply i can maybe better serve him and he's not showing up in person
6:14
so if he's not showing up in person i've got to use data to try to get to know bruce
6:19
and and so there's i need to enrich what i have about bruce with third party data
6:24
sets i want to know maybe bruce net worth i want to know bruce's credit score his
6:29
ability to pay uh maybe the value of his house whether he has liens against his house what his equity position is in
6:36
this house i i want to know how many loans are being sold in my footprint area last
6:41
month so i know whether my market share is growing or shrinking i need my data enriched and it's not easy
6:48
to assemble a picture using my own data make it trusted let alone add third party data in the mix
6:54
and finally if i do those things right how do i make money how do i monetize that how do i get insights
7:01
how do i know how where i'm over performing or underperforming and grabbing market share of first mortgages in my territory
7:10
on a monthly basis and see trends and know where the money is where am i only getting maybe one
7:16
percent market share for helocs and my competitors are getting 99 so i can have a focus campaign to go
7:23
after that how can i visually see that and then
7:28
activate segment uh a list to go after activate that list
7:34
push a marketing campaign and measure revenue lift 30 days from now
7:39
doing all of these things is critical to assemble that one picture
7:45
enrich that picture make that data trusted so i can then make money monetize that and hey i'm best able to
7:53
serve my customer if i can actually see them with all of that in mind it gives me
7:58
great pleasure uh today to introduce peter love chief digital officer berkshire bank we've worked with peter
8:04
for over a year now uh with our data rocket uh partnership and i turn over to carolyn and peter
8:11
thank you thank you for that overview bruce that's great um and now we're
8:16
really excited to spend this time talking with peter the chief digital officer at berkshire bank about his
8:21
experience leading a digital transformation peter thank you so much for being here thank you carolyn i'm looking forward to
8:28
the session great so peter can you tell us about your role and responsibilities at the bank
8:34
sure um as uh bruce uh fantastic introduction you hit on a number of really important points there that uh
8:41
that are important for all of us uh my role at berkshire bank i'm the chief digital officer
8:46
and really i can break my role up into three main categories uh
8:51
number one is the customer experience i'm responsible for making sure our team is
8:57
uh creating the most positive experience from our customers both internally and externally as we possibly can we put
9:03
this the customer in the center of every every process discussion we have at the bank uh secondly focus on the
9:11
consumption and availability of data uh we're sitting on a treasure trove of data from uh various
9:18
acquisitions and the large number of transactions that flow through our bank every day so making that data available
9:24
and getting it in the right person's hands to help customers as well as internal colleagues
9:30
and third is uh the integration and uh fintech partnership so a big part of what we're
9:36
doing at berkshire bank is creating the digital platform for the future
9:42
uh and making sure that systems can connect and speak to each other seamlessly is a
9:47
critical part so it's customer experience data and integration is really the main focus for us
9:54
um so you are in the second year of a five-year digital transformation project called best
10:00
uh what are the goals and visions of berkshire bank during this uh during this big undertaking
10:06
yeah i think uh i think bruce hit on a number of really important points right the uh the customer environment is
10:12
changing people are expecting different experiences from their banks uh from a strategic perspective at
10:18
berkshire um we are uh you know a socially responsible purpose-driven
10:24
bank serving the communities of our footprint uh we're hyper focused on participation and support of those
10:31
communities so from an overarching perspective uh everything we do at the bank obviously
10:37
is uh is to help shareholder value and customers um you know from a from a tech
10:42
perspective there are a number of goals and objectives that i have uh but we take a step back and and think
10:50
about how we can enable um the best plan so for us it really starts with the
10:55
executive vision um we're very fortunate to have uh a very strong focused
11:02
executive team uh early on we made a decision to uh basically brand our transformation
11:09
efforts uh and you mentioned you mentioned best earlier so for us
11:14
we're trying to be the best we can and that is berkshire's exciting strategic transformation
11:20
and what that does really is it enables us to have a common language a common vision
11:26
you know we have a dispersed uh footprint we've got 1500 over 1500 employees at the bank serving our
11:32
customers every day uh and really by branding the transformation effort you know from a
11:37
very complex technical effort to to something we can all relate to and rally
11:42
behind has been critical uh so best is the overarching and then from best while
11:48
there are multiple work streams and stakeholders and complexity we've really broken up the vision into three main
11:54
components so how do we digitize the bank how do we optimize the bank and how do we enhance the bank again all rolling
12:02
up the best so really that's been a big part of our uh of our initiation of the transformation
12:09
so how did you develop the digital transformation roadmap as you were
12:14
getting ready to undertake this transformation yeah it's uh it's been a journey uh like
12:20
like i said before it's it's a it's a very complex uh mission and goal that we
12:25
have uh collectively across the entire institution uh i do actually have a slide here carol
12:31
and it's i think it's called digital maturity if you could bring that up it might help a little bit um
12:37
so so this is a you know a high level overview we we started our plan
12:42
uh back in 2019 you know identified a five-year uh outlook and really focused on how are we
12:49
gonna mature ourselves as an institution from a digital perspective so as bruce mentioned
12:55
consumers expect new experiences you know covid accelerated a lot of the
13:00
transformations that are happening across the market and those things aren't going away we recognize the need to invest in our
13:08
technology and if you look at the upper right hand corner you'll see a lot of the business drivers for us and again back to your
13:14
original question you know everything is driven by being being best right so how do we
13:20
how do we create um you know a socially responsible omnichannel bank to allow customers to interact with us how they
13:26
see fit on their schedule uh for the and the contextual information that they need to help them with with whatever
13:32
their uh particular purpose is at the time you know and how are we removing barriers to to serve our communities and
13:38
participate in our communities and fund our communities um and really be active participants in
13:44
in in the communities we serve and of course we need to you know as a bank you know how are we improving our financial
13:50
performance for this new market and how we're gonna how we're gonna compete um
13:55
in the in this new space so all of those things drive us uh as a technology organization and of course the things
14:01
down on the on the lower right is is kind of how we started our plan all right do we know what our mission is
14:07
how are we going to do this we recognize the need again to move from legacy architecture to a more modern platform
14:12
uh and we'll talk a little bit about that today and a number a number of the partners that we were talking to today are are critical to that to that goal
14:20
um you know in today's day and age um you know the idea of having a single
14:26
source core provider in my opinion is something uh you know it's it's kind of a a an old an old idea right i mean to
14:33
compete in the new technology it takes a whole ecosystem of partners there's not one bank that i know of that can do it
14:39
all on their own even the big boys are partnering with fintechs and startups and data aggregators and
14:44
everything else so i think there is a fundamental shift that started years ago about leveraging the ecosystem
14:51
and it's a big part of our of our of our mission and of course to do that to to create the modern infrastructure to to
14:58
improve the customer experience you know for us it all it all relies around around data we've got mountains of data
15:04
we've got data and silos um how do we bring it all together and have one source of truth from a reporting
15:11
perspective but also from a know your customer perspective from a 360 percent of how are we sharing and aggregating
15:17
this data in a meaningful way for our internal and external customers and i think i think bruce touched on a couple of things in his intro as well you know
15:24
data governance well maybe not um not always considered to be super
15:30
important at the outset without it it's a you know you get yourself into a mess very quickly so data governance
15:35
oversight understanding data stewardship data owners uh is critical to to our current plan
15:42
and of course uh as mentioned you know a sole provider is not the answer
15:47
so from a technology perspective nor is it from a data perspective third-party partners are critical to everything we're doing in 2022 and beyond so uh a
15:55
long way of saying it i guess you starts with the mission again and then and then our role at the bank is really to
16:00
identify the partners and the systems that support the mission great and we have our first um our first
16:07
question from our audience here so um and i think it kind of touches on some
16:12
of what you were just speaking to um with with partnerships um but the question is what resources
16:19
technical monetary and personnel wise did you need to invest in to make this happen
16:27
yeah uh again fortunate to have an executive team that supports the mission and is committed to the mission which
16:32
comes along with planning discussion uh an iteration of of both you know technical requirements
16:40
but also funding and and and human uh requirements so so uh you know my my
16:47
team is uh is an agile group um and we've got uh 10 10 resources that
16:54
that uh that focus on the three tenants i kind of talked about before we have a customer a customer team we've got a
17:00
data team and we've got an integration team um and and again we we are fairly light as far
17:08
as uh the fintech and digital space but we have partners that we rely on
17:14
that are really act as extensions of our group um but so so a lot of it for us at berkshire is all about business
17:20
justification uh asking for a resource doesn't you know
17:25
create a creative resources a business case for everything we do in an roi that needs to be defined and understood
17:31
in order to commit to the resource that's great peter thank you what challenges did berkshire bank have as
17:38
you approach the project and how did you overcome them yeah there are a number of things again it's a complex effort right and and it
17:45
takes a number of a number of different stakeholders from across the bank i think uh one of the things i've i've
17:50
seen um is really the idea that this is a technology effort and i would argue that it's not it's actually more of a
17:56
cultural transformation than a technical one um at the end of the day some of the
18:02
technical components uh end up being you know easier than than getting everybody to come to the table uh to understand
18:09
what the business functions are that are required to really uh digging in to understanding how all those pieces are
18:15
connected together so for us early on uh in addition to the branding of the effort
18:20
we also identified a transformation group we meet every two weeks we have leaders coming to our group from
18:26
uh every part of the business we have an active dialogue an active prioritization list uh
18:33
and an opportunity for people to come to the table that may not have had a voice in the past it's expected now that everybody is participating uh and and
18:40
one and wanting to participate because they're um they're seeing they're seeing the results of the investment
18:49
um so how is berkshire bank using data now and how do you plan to use data to achieve
18:56
your business goals yeah so we've been uh again we've been fortunate with support and and uh not
19:02
only internally but again from our partners so we're using data for many of the things that we talked about before
19:08
uh we've got a a very robust uh customer relationship management program we've got a robust um fintech partner network
19:17
we've got um a a trusted and um predictable data ingestion and
19:24
availability process so we're bringing those pieces together to get information back to
19:29
uh you know our first step is internal colleagues making sure people have the information they need to service their customers the best way they can making
19:36
sure that we've got context and an understanding of each customer from a 360 perspective and then also a big push
19:44
uh in in 2022 is extending that out to the digital space on the customer front
19:49
so again using many of the same assets and um and investments
19:55
to help with community investment uh you know appropriate uh product
20:00
placement and and packaging and uh and helping with guidance and support of our customers in their markets
20:07
um great so peter we have a follow-up question here um about about your point about the cultural
20:14
transformation at berkshire bank and the question is um what have been some of the best ways that you've been able
20:20
to drive change management in this regard and maybe this is a great time to talk about your transformation team and some of the success that you had with
20:26
your call with your call center um stakeholders yeah no that's a great
20:32
question and it's uh it's i i think all of us probably experience um
20:37
you know challenges when the businesses is working to support their customers
20:44
hit their targets identify needs and support and and we're trying to get people to
20:50
see uh new ways of doing things and recognizing that that maybe you know
20:56
technology could facilitate where an excel spreadsheet will do you know maybe there's a quicker way to
21:01
do something a better way to do something uh so so for us uh the transformation work group has
21:08
been incredibly important like i said we meet every other week we bring
21:13
discussions to the table we prioritize and identify and then actually score
21:21
efforts by business impact and technical complexity so it's a it's a true partnership between the business
21:27
and i t to say well this is really important i can say well it's technically not very hard to do
21:33
let's move that to the top of the list whereas something that may be on a fringe but require a larger technical
21:39
investment would fall down but i think the most important thing and the thing that's really gotten attraction is
21:45
the success stories and we're constantly looking for evangelists we're constantly looking for people the business that
21:52
want to work more with i.t that want to see some of the tools we have and then can take those back into their their
21:58
pods or into their business teams and really show their colleagues you know what they're doing and how they're doing their jobs differently
22:04
um carol mentioned you know a recent success was was in the call center where we've uh we've grown very quickly over a
22:11
number of years we we've been uh kind of an aggregation of a number of different sources and our call center had i had to
22:17
deal with that right they had seven different systems to look at customer would be on the phone
22:22
uh we we have been able to leverage a lot of the partnerships with with with with segment and with pastoral and
22:28
others uh to change to totally transform the call center experience so instead of
22:34
being on the hot seat and trying to do a swivel from chair to chair to figure out how to service the customer we've been
22:40
able to put one single pane of glass in front of the call center i've got some quotes and some um
22:46
testimonials from the call center managers themselves just uh extolling the the benefits of the system really i mean
22:52
it's helped them with turnover it's helped them with just morale in general i think you
22:57
know anything it does is is you know you kind of notch some wins but when the
23:04
when the feedback from the business shares how it's changing their lives and how
23:10
it's changing in the interaction with the customer that those are the ones that matter uh and and so we're constantly looking for in that in that
23:17
every other week session we bring we we actively look for people to bring their experiences forward and to kind of
23:24
showcase we do a show and tell on on how somebody's process may have changed based on some of the uh improvements
23:29
we've been able to to to deploy with their with their support it all starts with them if they're if they're interested and they want to invest the
23:36
time and getting it done uh we bring them back and and give them an opportunity to share with their with their peers you know how it changed
23:44
i think that's the most important thing for us absolutely um so
23:49
uh after we speak with you we're going to hear from um segment and equifax so i
23:54
was hoping you could share how berkshire bank envisions using solutions like segment and equifax and
24:01
um how critical do you think third-party data is to your decision process i'm i'm
24:06
folding in a q a so i don't want to catch you off guard there but uh the second component was something that came
24:12
in through q a yeah um yeah the the partnership with segment and um and passerell and and
24:19
talon and and snowflake and and i could go i could go on and on it's it's incredibly important we've got a lot of
24:26
data uh from our primary system like i said we uh we actually are building a better bank not a bigger bank but we for
24:33
a long time we were building a bigger bank we're we're we kind of grew up through a series of acquisitions so we
24:38
have tons of data um and we're we're working closely with
24:43
our partners to uh ingest all of that into one single source and to use that
24:49
as the source of truth as i mentioned earlier um and things like like the customer 360. uh instead of having to
24:57
pull together from seven different origination systems i can now go to one single source
25:02
and identify uh every account and every interaction that that customer has with the bank uh
25:09
on a flip side from an executive perspective i can i can bring in all my origination pipeline data and bring that
25:15
all together so our executive team have uh you know some leading indicators as to what's happening at the bank and use
25:21
data from from from our single source as um as a as a true kind of uh executive
25:28
dashboard with kpis and metrics kind of indicating where we're headed as an organization where where uh risks may exist and then and
25:36
then going in a step further with our customers um
25:41
in our our business lines i mean business like customers you know we have the source the single source but the
25:47
equifax data or the segment data enriching as bruce mentioned a lot of the transaction data i get a i get a
25:54
query string or you know you know data in not the most user-friendly format from a number of
26:00
systems and and partners uh somebody like segment is able to work with me to
26:05
really normalize that data and give it back to me in a way that i can share with our with our
26:10
business lines and our business lines can obviously uh react to that information with more
26:16
insight and um and with with offers or or support services that
26:22
can help that particular customer so there are a number of ways uh we're enriching our first party with third-party data and and it wouldn't be
26:28
possible without a lot of the modern tech back to that technology we're using and the and the partnerships we've established with with our with our with
26:35
our partners all right i hope that answered your question carolyn i think he had two in there yeah you answered a lot of
26:41
questions there so we are we're running we're running short of time on time so you're going to
26:46
have one more question here and then anyone has questions for peter um if you
26:52
can just you can go ahead and ask them and then we'll hold until the end of the presentation and we'll answer um all the questions then so thank you so much
26:58
peter just one more question and that is how do you measure success uh personally and as an organization
27:05
yeah that's a great question jen um we we measure success as an organization
27:11
clearly like i said we've identified the best objectives and we've got uh critical performance indicators for each
27:16
one of our pillars in each one of our work streams so we're we are uh always measuring uh to be a better performing
27:22
bank uh more invested bank with our communities uh a a mission driven purpose-driven
27:29
socially responsible bank so there are a number of ways that we're tracking and we do it every month if not
27:35
more than every month but i mean in in a in a corporate way uh we have uh you know uh sessions with
27:43
our ceo and with our executive team that outline exactly how we're tracking our success so it's a constant
27:49
uh mission for us and then and then on a personal note from the from the from the it perspective obviously we've got our
27:55
own kpis that we're driving to but a lot of it i think with a question before about that transformation group we
28:00
measure it by success stories and anecdotal uh information um you know and
28:06
if we're doing our job right all of that is translating into actual revenue and and um and performance uh for the bank
28:12
from a business perspective but we're our mission is to collaborate
28:18
to make data available and to surface it in a way that people care about it
28:23
um and that that comes with with with internal partnerships are critical for us and and constantly trying to get that
28:29
uh optimized i could talk forever so i apologize
28:34
thank you so much peter your thought leadership um in general is really wonderful to be
28:40
around and um listening to you speak today brings a lot of value to me i hope it brings value to everyone on this call
28:47
um and uh so thank you so much with without further ado and and please you guys uh
28:53
people who are on the webinar if you have questions for peter keep them rolling and then we will get
28:59
to those at the end of the webinar um but now we're going to spend some time with eric tressler and greg spencer
29:05
um hi eric how are you
29:10
good hi greg so we talked about berkshire banks plans that include equifax and segment and now
29:18
we're going to spend a couple of time a couple of minutes talking with you both um i'll first introduce eric a senior
29:24
vice president of equifax and greg and then uh eric handed off to greg who's the senior sales and solution
29:31
engineer at um at segment they're going to talk with us about their data solutions for financial services
29:38
before we hand it back to bruce he'll tell talk to us about data rocket and how data rocket ties all of this
29:44
together so um eric we will start with you perfect thank you so much carolyn and um
29:52
peter that was fantastic the story that you tell about berkshire and the leadership that
29:59
you're showcasing is is tremendous
30:04
really an extraordinary amount of progress and the vision is fantastic and frankly
30:10
i really enjoyed your recognition of the necessity of the broad
30:16
involvement that it takes to go on a on a transformational journey
30:21
it takes a team and you certainly have a plan and a vision for the berkshire team
30:27
and speaking of teams i am proud to be a part of the team that passer l data has
30:33
assembled um first rate best of the best across the board uh
30:40
companies but most importantly a commonality of solution and customer orientation
30:47
so i'm eric trussler uh with equifax and i have a host of responsibilities but
30:53
among them is the privilege of managing our relationship with snowflake with segment with talond and with passerelle
31:02
let's go to the next slide and so i i suspect most of you know
31:08
about equifax um the prism that we like to think of
31:13
ourselves through and the ideal is helping consumers live their financial best and you actually heard
31:20
just a touch of that with with peter at the end as he talked about um you know how he measures success and
31:27
some of the anecdotes right those anecdotes are the company doing well and servicing
31:33
um their clients both commercial and consumer and so on the right side of the screen you see
31:40
some ways in which we have measured ourselves sort of across the u.s or across the globe
31:47
but we're a company also that has gone through a transformation certainly a theme of peter that you shared
31:54
and to me transformation is is a deliberate choice to be something different
32:02
and when you're done you really quite frankly can't imagine what it was like or to go back
32:08
and and we have gone through a transformation as well and we are the first in a
32:14
fully cloud credit bureau and that fully cloud
32:21
notion frankly allows us to tie back to what bruce started us with as bruce described
32:28
how do i know bruce how do i know bruce the individual with our integrated data fabric in the
32:36
cloud we begin to see bruce the person bruce a member of a household
32:42
bruce a property owner and understand which some formats and some
32:48
understandings about what is that property perhaps even bruce the business owner or
32:53
business principal so that transformation is enabling us to move forward in ways that can help
32:59
um help berkshire and help uh financial institutions and frankly beyond financial institutions
33:05
carolyn let's move uh move to the next slide so if those outcomes that we just saw on
33:12
the right rail are are our goals um sort of how how do we get there
33:18
uh and and the way we do is through our customers and our partners quite frankly and and quite directly
33:25
um companies like berkshire able to use our data assets and our decisioning
33:30
tools across the value chain be that in marketing
33:35
as bruce ellicott eloquently described who are your best customers what capacity do they have
33:42
where and how can i find uh find them and more like them
33:47
all the way through account opening in each and every engagement you have with your with your
33:53
customers that identity authentication and fraud frankly those are the
33:59
cornerstones of a digital experience if you encounter someone who has
34:05
um an encounter that has suspicious activity then the appropriate amount of friction
34:11
for that engagement might be heavy friction but if you identify someone uh looking
34:18
to transact with you and they look as a friendly then it should be a light and friction
34:24
uh light experience maybe even a predictive experience one that acts as
34:30
if we know something about the customer and perhaps what what they might be interested in
34:36
through as as was described earlier the analytics that help you understand where markets are going
34:41
where sub-markets are going where geographies where growth is occurring and even into collections
34:48
and we do that across industry certainly today we're focusing in on financial institutions and credit unions and i'll
34:55
talk a few examples of that but as you move across from auto to mortgage into
35:00
telco and even retail and healthcare equifax participates along that value
35:06
chain so let's hit the next slide
35:11
so our our relationship with passorelle and the data rocket and ultimately
35:18
with with the clients um is in part underpinned by just a
35:24
fantastic technology um called snowflake so i mentioned that we had we had moved
35:30
fully to the cloud and and snowflake is a technology that allows for lightning
35:36
fast secure private shares to be able to light up
35:41
um insights against your customer base and prospects
35:47
and we have put some of our most powerful tools on snowflake enabling it to be easily
35:54
accessed and frankly configured to reflect the trade area to reflect the
36:00
geography the scope and scale of what you need not u.s wide but perhaps a state or two or
36:08
four and so here are a handful let me tell you just a bit about them
36:15
so our b2b connect file is is frankly the richest set of
36:20
business firmographics in the united states and i say that with confidence it has over 5 million more
36:27
business locations than the next closest and perhaps more well-known competitor
36:34
full corporate hierarchies all verified data nothing self-reported and so customers use this
36:41
data to create commercial profiles for their best customers
36:47
it includes business failure and absolute absolute probability of default
36:53
predictions so recently a multi-state regional bank was launching a commercial product they
37:00
needed some high quality leads they looked to us with this b2b connect data
37:06
conducted market segmentation infused some additional contact information on top of their first party
37:12
data and found 67 000 new prospects and in six weeks generated an 8x roi
37:21
we also have our economic insights so this is the data that bruce talked about
37:26
when you think about the person the household um most
37:32
very important is an accurate understanding of the financial well-being the financial durability the
37:39
wealth the income the credit the ability to pay this is used in both
37:47
you're lighting up your first party data and finding those that look like your best customers
37:54
um we we have an example recently um where we had a client that wanted to
38:01
understand prepay and so they they looked at their uh prepay history and then
38:07
appended income 360 and then determined that certain income levels were driving
38:13
a higher proclivity to prepay and were able to segment their customers that way
38:18
so whether it's whether it's targeting prospecting cross-sell upsell this is the most accurate insight against the
38:25
consumer that there is property data um this this property data
38:31
is is nationwide uh allows you to find
38:36
from ltv to cltv the the first lien amount the interest rates
38:42
um assessed value last sale price all the things that you would think about that are attendant with
38:47
each and every property and our credit trends and analytic data set both are about the markets
38:55
where so these are data sets based on the entirety of the u.s
39:00
credit file anonymized made available and able to be configured just to what you need so it's
39:08
not only the uh the fed or the largest of the banks that that
39:14
want access to this kind of insight it's it's it's all financial institutions
39:19
and we're able to because of the power of snowflake and because of the partnership with pastoral data bring the types of
39:26
insights where are he locks growing as bruce talked about geographically where where are your
39:33
customers and what are your peer groups how are they performing to show you the strategic areas of growth
39:40
much more to talk about um but i do want to make sure that we spend some time with segment um my my
39:47
good friend greg spencer uh with a great company segment um you're gonna enjoy
39:52
what they are able to do with your your transactional data well thank you very much eric that was
39:59
uh uh very well done and uh let me just echo some of uh eric's earlier comments
40:04
as well and say that uh i appreciate asda segment the opportunity to uh to be here today um and uh participate with
40:11
our partners at pasorel and equifax and of course our mutual friends uh you know peter and others of berkshire
40:17
uh so so just a bit of background about me before we dive into segment and i will be participating in berkshire's
40:22
journey prior to joining segment three months ago i spent the previous 13 years at metro credit union a two and a half
40:29
billion in assets credit union based in massachusetts where in my most recent role i was senior vice president
40:34
strategic intelligence overseeing metro's data analytics framework and go forward strategy data integration
40:40
business intelligence efforts and the like um and along those lines i was an advocate and champion for bringing
40:45
segment solutions uh into metro's arsenal uh and with metro having just completed a multi-year technology
40:52
transformation project that included replacing its core online banking providers remotely during the pandemic
40:57
nonetheless i have an acute appreciation and admiration for the path that peter and his teams are on a berkshire uh clearly
41:04
they have put in uh a ton of careful effort thought and planning into their road map and and and personally i'm
41:11
incredibly excited uh to watch their execution on it and assist along the way and and for for peter and for uh uh the
41:18
attendees here that's my that's my long-winded way of saying uh just how jealous i am um of what you have uh in
41:23
operations right now because i can tell you just how firsthand i can tell you firsthand just how impressive it is
41:29
so uh you know with that uh let's dive right into segment and what segment does uh how it does it and how it sets itself
41:35
apart from others in the market founded 14 years ago at its heart
41:40
segment is a data company with an intense focus uh on cleansing and categorizing the never ending variations
41:47
of transaction strings that enter the walls of a financial institution at any given time thus making this rich source
41:54
of data and insights on their account holders easily accessible for them contextually
41:59
valuable and most importantly actionable and carolyn if you want to jump to the next one
42:05
um so so when you look at the core offerings um that segment provides you're going to find that these themes
42:10
of accessibility and actionability resonate throughout all of them starting on the left-hand side here and
42:16
specifically uh on our on our merchandise cleansing our mpc and customer insights driven by key
42:22
lifestyle indicators or klis when talking about these solutions i like to call them different sides of the same
42:27
coin each of them rides on the rails of the cleansing and categorization framework that we have built and that
42:33
i'll get into more details momentarily the difference between the two though is that the focus on mpc and its output is
42:38
the transaction and merchant definition itself while the klis are enriched data tags that focus on the customer or
42:44
member or account holder now before getting into the weeds here though you're also going to see that we
42:49
have a growing portfolio of ai predictive models that leverage these rich kli attributes um on fi's customers
42:57
and last but certainly not least uh is our marketing automation platform that allows fis an easy to use interface to
43:04
build audiences off of these enriched kli's and deploy highly targeted highly personalized multi-channel campaigns
43:10
through an ever-growing list of channel integrations we have built with the major core online banking and other
43:16
ancillary digital providers in fact just uh a couple of weeks ago we launched we
43:21
released um a press release announcing our our new integration with cost to contact for email so believe it or not but we do all
43:28
of that in terms of our integrations and the ingesting of of core and transaction data and third-party data without pii
43:36
so thank you carolyn and uh so so what i just described you can you can probably
43:42
term as being like a high level uh overview what you're looking at right now though is very much in the weeds and
43:47
this is just a tiny sample of what we like to call the dirty strings of transactions that can appear in fi's
43:53
data if you scan the screen you'll likely notice a number of different iterations for the same merchant such as
43:59
wells or chase and while some of these may seem self-explanatory for what they are the reality is that many are not and
44:05
without an extraordinary understanding and significant resources dedicated to this craft efforts to wrestle this for
44:12
institutions of any size will ultimately likely fall short due to no fault of their own
44:18
transactions and other important data points will be left behind inherently in using your typical uh string searches or
44:25
wildcard searches and so forth and carolyn if you want to jump to the next thank you and here's the reality
44:32
you know this slide that you're looking at gets more outdated every day if i'm not mistaken uh as it as it stands today
44:39
we we have over 170 million transaction variants defined in our library of which
44:45
individually there are hundreds of thousands of permutations for providers like wells chase and amazon in the
44:51
instance of wells some may have wells some may have fargo some may have wf and
44:56
then there are others that don't even have any of those multiply those scenarios across industries payment
45:02
networks merchants and recognizing that it will never stop you hopefully begin to understand the issues of scale for
45:09
being accurate here on your own and that is where segment comes in with our processing cleansing and identification
45:15
framework driven by the library i mentioned as well as ai and machine learning rule engines
45:20
for capturing new entries we also have a team of dedicated library research scientists providing the necessary human
45:25
supervised approach this allows us to provide continuous relevancy and accuracy for new
45:31
transaction types and merchants that will never stop there will always be the next new service like disney plus there
45:36
will always be now new crypto players new buy now pay later offerings that we
45:42
react quickly to and add to our taxonomy in real life terms uh what you're
45:48
looking at now is an example of how this works the transaction string that you see on the left that starts with wdw is
45:55
what we receive and while you may be able to decipher that it's walt disney world you are unlikely to know based on
46:01
that transaction string itself unless you researched it that it's a walt disney world vacation club purchase so
46:07
on the mpc side what you would get back as appended data to the transaction is the middle call the merchant name logo
46:13
and two levels of categorization on the other hand if this was the kli output and based on the customer you
46:20
would get similar data but instead you'd get the tags that indicate that the that the customer is it both a traveler and a
46:25
vacation so bringing this back home and how berkshire can or may use these these
46:32
data sets in their new snowflake environment as someone who recently came from the fi side with a dedicated focus
46:37
on data data analytics and strategies as i mentioned i'm incredibly excited about what berkshire will be able to do with
46:44
them specifically in the use cases for competitive win back squad analysis understanding total product outflows to
46:50
competitive uh to competitors and trend shifts over time capturing new entries or new challengers in those categories
46:57
identifying recurring subscription or mobile app payments such as coffee shop mobile apps amazon prime etc that could
47:04
be flipped from their current payment rail to a debit interchange rail effectively turning what was a cost into
47:10
a revenue line item uh with justin possibly a little enticement you know to the to the customer uh for swapping out
47:17
their ach payment uh credentials for the debit card how powerful these can be for
47:22
berkshire and for and for those you know able to grasp the depth and the richness of the
47:28
the the enriched data transaction and the customer insights that we're able to provide so you know moreover you know combining
47:35
all of this data as peter showed with their other data assets and snowflake whether it becomes a star schema that
47:41
pastoral builds are layered across multiple dimensions there are literally untold opportunities for competitive
47:46
advancement advancements ahead of them just really really super cool stuff so last but not least
47:52
given the overall discussion here and our relationship with snowflake it also bears mentioning that segment is
47:58
committed to further innovation in the cloud and in particular snowflake along those lines early last month we
48:03
announced an exciting brand new partnership with them whereby we were able to now offer our mpc solution
48:08
embedded in their environment without the data ever leaving the customer snowflake instance and they can rapidly
48:13
retrieve cleanse transactions and clinch transactions in an entirely secure fashion segment and snowflake are both
48:19
incredibly excited about this innovation we recently conducted a data jam session with them uh that is viewable on our
48:25
youtube account and our vice president of enterprise architecture lance cuthbert uh we're presenting on it at the snowflake summit in june
48:32
so with that uh that's it for me thank you again uh for having us participate happy to answer uh questions later on so
48:38
back to you carol
48:44
thank you so much greg and eric those were great presentations and really just the tip of the iceberg as far as the
48:50
opportunities that are available for enriched first party and third-party data but to get started on this journey
48:56
financial services need to trust their their data bruce is back to tell us how data rocket for financial services
49:02
establishes a well-governed data lake that is scalable and future ready are you ready bruce i am thank you carolyn
49:11
we built data rocket uh if i were to summarize in four words our
49:16
product which is powered by snowflake and talent allows
49:22
a financial institution to assemble data enrich data make data trusted
49:27
and let you act on that data in an accelerated way it's a set of code and blueprints
49:35
frameworks that run on core technology i was born in 1962
49:42
a bit of a nerd as a kid marvel comics fan i look at what we've done is assemble
49:48
the avengers powerful each on their own
49:53
brought together as a team can achieve incredible things
49:58
data rocket under the hood consists of snowflake first and foremost cloud platform
50:05
the powers are when you need it easy scale up auto scale out and on a pay-per-use basis they
50:12
have a unique way to do data sharing allowing our friends at segment and equifax to have their assets made
50:19
available and shared instantly and securely in your warehouse your instance of snowflake
50:26
and so it's now part of your know your customer pattern and platform
50:31
and finally data is a dial tone snowflake has eliminated the old active active active
50:36
passive log shipping mirroring all that stuff that went along with legacy databases
50:41
all that's gone data is now available as a dial tone through snowflake
50:47
we went all in five years ago as one of snowflake's first system integrators and resellers and a data marketplace partner
50:54
and a powered by snowflake application data rocket second is talon
50:59
it's great to have a cloud platform but there's some capabilities you need
51:05
so that's not a swamp you don't want to just land data in a lake and and let it be
51:11
we went all in with talon five years ago as well we were talon's first u.s var
51:17
and first one of their first u.s resellers talon manages mo data movement in
51:23
batcher real time we've yet to meet a system we can't connect to and some of these finance systems
51:29
phi surf dna fis jack henry there's eclectic sets of systems out
51:37
there that are hosted or on-premise that uh are tricky to connect with we've yet
51:43
to meet a system we can't connect with and move data into snowflake
51:48
once it's there we want to process it talent alone is a gardener leader for data quality
51:53
again assembling that picture so we have a master golden record making it trusted
52:00
for fuzzy matching de-duping data masking all of that can be done with talent as a gartner leader
52:07
business and i t as i described before i t can't possibly be the subject matter
52:13
expert for every data set across a bank talent has two has multiple personas one
52:19
of them is for a business a data steward to play a role in that data is an it it and business
52:26
working data is an it sport as a team sport working together
52:31
so it has a persona business has a persona they work together as one to
52:36
make data trusted and finally data catalog they have a data catalog product that is
52:43
already integrated with the transformations so to look at glossary dictionary definition of what is a
52:48
branch what is alone that capability can be lit up in in and
52:53
quickly integrated as part of this platform so you now have a well-managed well-governed lake warehouse
52:59
architecture to assemble make trusted enrich and get value out of
53:06
the other partners are key you've heard from our friend eric and greg at equifax and segment
53:13
the power that third party data and your own enriched first party data
53:18
can bring to the table so you now have a wide view of who your customer is beyond just what
53:26
you know about them on how they're doing business with you you now have
53:31
many many many columns of attributes about your customers that you can do some decisioning on
53:37
maybe some pattern matching and detection on which is where data iq comes in
53:43
data aiku is our partner for doing machine learning so if you hire a data scientist or have a data scientist team
53:50
that want to mine this trusted data to detect patterns predict who's going to leave your bank next month based on
53:57
who left last quarter data coup allows you to add in enrich data and
54:03
finally the final mile how do we get insights and make money so we go with the gartner leaders for
54:09
tableau or power bi for visual analytics that said if you have a a standard
54:14
visual analytics tool it can plug in and use the data that's been assembled
54:20
enriched and made trusted but we lean on in on tableau and power bi
54:26
because they're the two clear gardener leaders for people to make aha get the aha moments and cognitive connections
54:34
on decisioning where do i want to launch a marketing campaign to grow my heloc sales
54:40
and finally flywheel they're another powered by snowflake application that we're also a reseller
54:46
of because they allow you to segment the data
54:52
i want all customers that have five thousand dollars in deposits or more that have a net worth of this or more
54:58
that have a heloc of this size or more in this zip code area i want to segment the data fast i want
55:06
to push it out to a marketing campaign salesforce twitter youtube facebook
55:12
launch that campaign i wanted 30 days later measure
55:17
whether that campaign was successful so i can do more of those campaigns so
55:22
flywheel allows you to segment activate launch a campaign and measure revenue lift
55:28
allowing you to monetize the data and all the effort you put into shaping the data and making it trusted
55:35
we build on top of this stack with our data rocket software carolyn next slide
55:42
so data rocket has software it's a set of framework and code
55:49
that allows you to assemble make the data trusted enrich it and then take action
55:54
on the assembly side we have a a well-governed assembly framework
56:01
dynamic data ingestion to land the data with change data
56:06
capture following rules of sdlc so data is landed into the lake structure in snowflake
56:13
and is properly positioned for use with an audit trail and pulls the
56:18
changes so that lake is always current and and data you can trust it's going to
56:24
be there when you need it we also have our enterprise blueprints your users double-click on a dashboard
56:31
to make cognitive connections we have role-based access control from dashboard back to the warehouse
56:38
for trust we have a mastering data framework you can master data with snowflake and talon without having to
56:44
buy a million dollar master data management solution is the bruce that has a five thousand
56:50
dollar deposit account in jack henry the same bruce that has that hundred thousand dollar heloc
56:56
in encompass we have a mastering framework that allows you to master the data to have a golden record you can trust
57:03
we have an operational dashboard that looks at snowflake for capacity planning
57:08
looks at the virtual warehouses and helps you predict and project the warehouse capability you're going to
57:14
need so it also tracks data movement
57:19
from talon how many rows of data were moved last night did everything go successfully
57:25
are there any errors of concern we need to quickly troubleshoot our operational dashboards give you
57:31
insights to keep the environment healthy we have a data quality watch it's not just keeping date making data
57:37
trusted but keeping it trusted so our quality watch product make sure
57:42
the data stays trusted for enriching we have a machine learning framework
57:48
so when you build a machine model we want to call it on a scheduled basis feed it data and take the latest
57:55
predictive insights and put it in snowflake so they can be p p u be used
58:00
when you need the data it's there in the dashboard for you our friends at segment and equifax we
58:06
know their data dictionaries we have written talon jobs to be able to
58:12
have that data be part of your warehouse so again it's a know your customer picture that's
58:18
been enriched leveraging snowflake and data marketplace and finally act
58:25
uh like you've heard uh earlier at the end of the day you want to empower the business
58:31
consumer banking commercial banking to have them be able to make
58:36
it make decisions using data with the smart dynamic dashboard and then based on decisions what product
58:44
offers do they want to make to what people at what time be able to then make those offers with
58:49
flywheel and drive revenue for the bank so carolyn um that's all i wanted to say
58:57
regarding data rocket back to you and thank you everyone for sticking with
59:02
us so far i know it's the end of uh of the of the day for some people um who
59:07
are tuning in from east east the east coast uh but we do have a couple questions um peter you're going to be
59:14
back in the hot seat for a minute if you don't mind and the question is how do you ensure your executive team
59:21
understands the impact your work has on the overall business objective
59:27
yeah great question uh and just before i answer i just wanna i just want to thank these guys again bruce greg eric i mean
59:34
i think you know some of my presentation was about the importance of partnership and
59:39
and and that we're not doing this alone anymore as an institution right we got we got people we really trust and rely
59:45
on for thought leadership and i think you guys just did a fantastic job and uh look forward to continuing to to work
59:51
with you guys so thank you for for for that um you know
59:57
it's always an important piece right we're investing a lot of money and time and effort into these new technologies
1:00:02
that are that are literally transforming the bank uh we're just we're just uh hyper active in communicating our
1:00:09
successes really uh there are a couple ways of doing it we have uh we have a structure at berkshire bank it's
1:00:14
something called the tech steering committee where i present every month to uh executive leadership
1:00:20
um about you know we have a very clear plan and we march to it and i have to report back on it all the time the the
1:00:28
other thing that we have is i mentioned the transformation group that meets every two weeks uh that that that that
1:00:34
group i also uh we have we have an output from that directly to what we call our digital
1:00:40
transformation group which is which is the most senior people in the organization and uh and we meet with them
1:00:47
every month as well so we have a couple of different channels we also have a robust communication plan we've got an
1:00:52
internet site we've got i've got an incredibly talented group of people you know on our team as well as business
1:00:58
line partners that that are willing to participate in videos in webinars in uh
1:01:04
in in in short stories or case studies so we have our own communication channel
1:01:10
that we're publishing to on a regular basis so we become uh basically a live feed across the bank so
1:01:16
people get a taste for what's happening in in the digital transformation space
1:01:22
okay great um peter i have another question for you uh what group is the hardest or was the hardest to get on
1:01:29
board and how did you get them on board with your plan
1:01:34
yeah that's a tricky one uh everybody's got their own uh their own uh quirks i
1:01:40
guess you know honestly uh there hasn't been a tough group to get
1:01:47
on uh once we get them kind of in the door right if the hook is set properly we're able to show some benefits
1:01:54
i think just the opposite happens so you could argue that maybe you know operations team may be a little tough i
1:02:00
think they're used to maybe doing things a certain way or or maybe comfortable with with manual process and and and i
1:02:07
think historically there may have been uh an interest in kind of augmenting that with more staff
1:02:13
you know to kind of sure up things but but but i think we're living in a new world and i think everybody's
1:02:18
experiencing outside of the bank you know in their personal lives people understand things are changing and expecting different different ways of
1:02:25
doing things and i think um the the the kind of customer experience again colleague experience is just as
1:02:32
important as an end customer experience so just allowing me to see data in a different way and interact with data in
1:02:38
a dynamic way and i think i think once they get a taste um you know our backlog is pretty long at the moment
1:02:45
um that's great so uh eric i have a question for you what is equifax doing to make it easier
1:02:52
for regional banks to get access to your data yeah that's a that's a great question
1:02:59
and um part of it is our partnership with
1:03:05
snowflake and and other cloud providers which allows the cloud to cloud
1:03:12
sharing of data part of it is the linking that we're now doing with our within our own four walls
1:03:19
so that instead of having our own data silos that you have to suffer through
1:03:26
uh instead we begin to link inside of our four walls to provide the complete
1:03:31
picture of an individual an example of making data
1:03:36
more accessible is that analytic data set that i mentioned so that is 28 billion rows
1:03:45
it takes us two weeks to provide that to the federal reserve
1:03:50
um of just pure data movement in snowflake we can do it in about 10
1:03:57
seconds and we don't have to give the whole us we can give two states or 50 zip codes
1:04:03
so cloud cloud-based fully linked unlocks the data that you need and only
1:04:11
the data you need great and then greg i have a question
1:04:17
for you as well what is the most memorable use of master payment cleansing
1:04:26
sure so that's uh that's a that's another tricky one as well and i think you'd probably get different answers on that uh depending on who you asked at
1:04:32
segment so um let me let me start with uh you know
1:04:37
something that i didn't necessarily uh go over in the details then when i
1:04:42
was showing the the use case slide is that um with the return of the categorizations
1:04:48
of the transaction type and the type of merchant it is with the logos an institution in theory could
1:04:54
build with their own technology resources their own pfm tool right so at the end of the day a budgeting
1:05:01
application could be built with the right technology purely by an institution itself without
1:05:07
having to go and create and have to buy it off the shelf if they wanted to um so
1:05:12
there there's there's certainly an extension there for the user experience in providing that logo that cleanse
1:05:18
transaction being able to aggregate their their their spends um across different categories with different
1:05:24
merchants for me um you know what what i am jealous of as i mentioned for what
1:05:31
berkshire and and others can do with the raw data itself coming from the from the from the
1:05:37
banking side is being able to aggregate and trend um the outflows of uh
1:05:42
competitive payments right and being able to identify uh emerging players those who are growing faster
1:05:50
versus those that are you know large because they're simply large right so like wells fargo and chase may be the
1:05:56
largest competitors for a particular product um and it can be you know established relatively easy for at the
1:06:02
transaction level by having the the actual dollar amount to see what those are but to take it a step further and
1:06:08
look at it as those what challengers what other competing um you know neo uh fintech and or you know
1:06:15
whether it's chime or robin hood which ones are actually starting to grow and that's what berkshire will be able to do
1:06:20
with the raw data um in snowflake with pasorel's help is be able to start to trend uh some of those you know uh
1:06:27
changes in in consumer behavior and and competitive uh the competitive nature in
1:06:32
terms of what their current customers are doing that's great thank you greg and um it
1:06:39
looks like we're we have about five minutes left and we have a question for you bruce and i think this is a
1:06:44
great question um because it kind of speaks to what peter was talking about
1:06:49
about the importance of showing value to business lines um for the power of adoption
1:06:55
and um and um so the question is how do you develop a
1:07:02
game plan for a customer so that you can show that value thanks carolyn
1:07:08
our approach is to listen so it starts with a phone call to understand what what are your goals what are you
1:07:14
trying to achieve where are you struggling where are your challenges and by understanding what your goals and
1:07:21
initiatives are we're able to formulate a game plan our product data rocket was built with
1:07:28
customers over the years we our roots were a system integrator experts at talent and snowflake and tableau
1:07:35
and we've built a product based on hearing from our customers what they need to go fast we want to accelerate we
1:07:43
don't want to spend a lot of time money and effort um in in operational areas that can be
1:07:50
tackled with a product to let us go fast our employees are valuable we want to focus them on higher value
1:07:56
items for the bank so it starts with understanding where are you at in your data journey what challenges you facing
1:08:04
and in starting relationships from there we can uh
1:08:10
we will coordinate in um the right resources to formulate the best solution for you to help you go
1:08:18
where you need to go with data rocket if it's uh you know diving in deep on the segment data set to add in the merchant
1:08:25
cleanse data to learn about cash flowing out of the bank and you know see patterns there and and
1:08:30
drive revenue grabbing market share knowing you know 20 million is leaving the bank every month um for competitive student
1:08:37
loans we want to grab some of that with our own again we will help we will facilitate lead coordinating discussion
1:08:44
with segments same with equifax you know you want to take your core banking customers add the net worth understand
1:08:50
you know who are they who are your top 10 percent of your customers that are the most affluent to maybe target for wealth
1:08:57
management or drive cash inflows from i will coordinate in meetings with our friends at equifax
1:09:03
and again we'll we're resellers of snowflake resellers of talon we're strategic contractual partners
1:09:10
with equifax and segment so we will be one throat to choke to shape one
1:09:15
solution with a budget to address whatever your needs are but it starts with a call to talk about what are your
1:09:20
needs and how can we help
1:09:26
great thanks bruce so unless there are any more questions which i don't see any more coming in i
1:09:33
am going to just take this opportunity one more time to thank you peter for your time and your energy and sharing
1:09:39
your story at berkshire bank um you have such a great story to tell we i think i
1:09:44
speak for everyone on this phone call and our partners at talend and at snowflake that we are so happy to be
1:09:50
part of your journey and we can't wait to see what you are going to accomplish in the next uh three years
1:09:56
and um we're very happy to be your partner and um we appreciate your time
1:10:02
yeah the feeling is mutual you know like i said we couldn't do without you guys uh so
1:10:07
we we really appreciate all of you thank you so um so i think there was a
1:10:13
a lot of great conversation today about the power of partnership and the power of great data i will be following up
1:10:19
with people um on this call with more information about data rocket and about our technology partners um that are part
1:10:26
of data rocket and that we're on this call today and please let us know if you would like to talk about your digital
1:10:32
transformation and how we can help thank you everyone for attending i really appreciate it
1:10:47
you