vision 2014: big data for business lending
DESCRIPTION
According to IBM, 2.5 quintillion bytes of data are created every day (enough to fill more than 531 million DVDs). Most bankers have no idea where to start when it comes to understanding their commercial portfolio in terms of Big Data. Sure, it’s easy to get information from the core, but what about all the valuable information that’s in spreadsheets, disparate systems and lenders’ file drawers? Learn how a top-performing bank is dealing with the need for customer-centric data for improved sales, underwriting and employee engagements.TRANSCRIPT
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Big Data for business lending
Sharry Ditzler Washington Trust Bank
Connie Miller Washington Trust Bank
#vision2014
Didi Frohardt Experian
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Big Data definition
Top-3 business lending strategies
Washington Trust Bank story
Getting started
Agenda
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Technical definition
Business lending definition
Big Data definition
The definition of Big Data refers to groups of data that are so large and
unwieldy that regular database management tools have difficulty
capturing, storing, sharing and managing the information “ ” – Yourdictionary.com
Data locked in silos and the lack of common customer identifier that
could link accounts and services “ ” – Wall Street Journal
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Loan growth Internal and external
1:
Top-3 business lending strategies
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Risk management Relationships and exposure
Regulatory compliance and
“suggestion”
► Stress testing
► Concentration reporting
2:
Top-3 business lending strategies
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Top-3 business lending strategies
Efficiency Disparate systems
Redundant data entry
3:
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Commercial trends
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
Bil
lio
ns
Commercial and industrial loans
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Commercial trends
1,020
1,030
1,040
1,050
1,060
1,070
1,080
1,090
1,100
1,110
1,120
Bil
lio
ns
Commercial real estate loans
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Commercial trends
0
100
200
300
400
500
600
Bil
lio
ns
Construction loans
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Commercial trends
56.63
65.56
59.68
62.19
70.82
72.79
73
72.26
80.69
87.25
0 20 40 60 80 100
>1T
100 - 999 B
50 - 99 B
5 - 49 B
1 - 4.9 B
500 - 999 M
250 - 499 M
200 - 249 M
50 - 99 M
0 - 49 M
Efficiency ratio (as of 12/31/2013)
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Washington Trust Bank
So, how can you
do it in real life? Q:
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$4.37 billion in assets (as of 12/31/2013)
112 years old, privately held, commercial bank
Serving the following primary markets:
► Washington, Idaho, Oregon
$3.0 billion total loan portfolio
► 8-9% loan growth FYE2013 – expected again for FYE2014
Washington Trust Bank Spokane, WA
C&I Agriculture CRE/C&D Residential Consumer
$835 M $208 M $1.2 B $611 M $101 M
28% 7% 42% 20% 3%
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Core system conversion
► Based on specific bank goals
Disparate systems converted or integrated into new platform
► Third party relationship
● Credit card
● Trust
● Cash management
● Investments
● Online banking
● CDARS
● Corporate contribution system
● Merchant
Washington Trust Bank Disparate systems
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Construction loans
Flooring – unit pricing
Many access databases and spreadsheets
► Auditing
► OREO
► SAD
► HLC
► Loan review
► Commercial incentive
► CRA tracking
► Market research – MCIF
Large data repository
Washington Trust Bank Disparate systems
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In house data warehouse
► Core to data warehouse balancing in place
Provides a more comprehensive and accurate data source
Data Integration to advisor platform
Everyone uses the same data points
► Consistency in reporting
► Same version of the truth
► Data naming standards/data use standards
Standard reporting package driven from senior management down through organization
Consistently deploy reports from one portal
Reduces custom report requests
Washington Trust Bank Data warehouse
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Converted access databases and spreadsheets now in advisor/originations
► Cash management
► Commercial incentive
► OREO
► Special assets
► Home loan center
► Compliance
● CRA
● SBA 504 reporting
► Loan review
► Market research – MCIF
Washington Trust Bank Experian solutions – effected
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Data consistency with Jack Henry
Custom report requirements
► Data at user fingertips – data queries on the fly
► Scheduled reports for historical – retention purposes
Relationship groups
► SBLF reporting
► Relationship and exposure reporting
Washington Trust Bank Experian solutions – effected
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Complete picture of client from prospect to special assets/payoff
Portfolio risk management
► Complete picture of borrower when trigger fires
► Run triggers across the bank portfolio – all consumer loans
► Small business loans
Washington Trust Bank Experian solutions – effected
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Continuing to bring data together in one place…
2014 and beyond
► Balance advisor platform to data warehouse
► Advisor data to data warehouse – for data not in Jack Henry
► Credit memo – with analysis – ability to pull key points out of credit memo
● FTE
● Revenue
► Stress testing data
► Appraisal data
► Pricing – current in house developed system
► ALLL
Washington Trust Bank What is left to do?
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The results!
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The results…
59.02
64.57
65.84
75.48
63.82
67.58 68.1 71.12
50
55
60
65
70
75
80
2011Q1
2011Q2
2011Q3
2011Q4
2012Q1
2012Q2
2012Q3
2012Q4
2013Q1
2013Q2
2013Q3
2013Q4
Efficiency ratio
Washington Trust Bank Peers
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The results…
2.65 2.72 2.71 2.64 2.68 2.84 2.9 2.9 2.94
3.08 3.16 3.18
0
0.5
1
1.5
2
2.5
3
3.5
11Q1 11Q2 11Q3 11Q4 12Q1 12Q2 12Q3 12Q4 13Q1 13Q2 13Q3 13Q4
Total outstanding loans
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The results…
79.2
56.7 54.2
56.8
43.5 39
35.8 39.3
36.6 33.8 34.5
31.6
0
10
20
30
40
50
60
70
80
90
11Q1 11Q2 11Q3 11Q4 12Q1 12Q2 12Q3 12Q4 13Q1 13Q2 13Q3 13Q4
Total non-performing loans
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Strategies
Determine future state/vision
► Senior management buy-in
Disparate system data review
► Diagram/inventory of architecture of all systems/applications
● Understanding where data is residing and interfacing with key data stores
► Consolidate and/or eliminate systems/spreadsheets/databases that aren’t relevant
Getting started!
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Strategies
Prioritize data required to support business processes/vision
► Determine the data repository to hold the data
Integrate information
► All customer data in one system
Q&A
Getting started!
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