The session will outline the reasons for implementing a data analytics program to identify strengths, weaknesses, opportunities and threats. We will investigate the method used in Baker Hill Analytics to calculate profitability at each level of the institution.

1. James McHale, SVP/GM Analytics at Baker Hill
THE NEED FOR ANALYTICS
AND THE VALUE OF
UNDERSTANDING PROFIT
RISK

2. BIG DATA

3. According to Forbes, 87% of companies think Big Data
will make big changes to their industries before the end
of the decade. Even more think that not having a big
data strategy will cause their companies to fall behind.
“Only the most informed and profitable will survive and
prosper”

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The power of Big Data
• Volume - Financial institutions collect large amounts of data from a
variety of sources, including transaction, social media, and
information from sensor or machine-to-machine sources. In the
past, storage was a problem – but new technologies have greatly
eased this burden.
• Velocity - Data streams in at an unprecedented speed and needs to
be sorted and stored in a timely manner.
• Variety - Data comes in all types and formats – from structured
numeric data in traditional databases to unstructured text
documents, email, video, audio, and financial transactions.

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Common uses of Big Data
1. Fraud Detection
2. Compliance and
Regulatory
Requirements
3. Consumer
Segmentation
4. Personalized
Marketing
5. Risk Management

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Call to action
1. Get your integrated database
system up and running
2. Start to understand profitability
dynamics in detail
3. Evaluate your income statement
with a focus on achieving long-
term sustainability over short-
term triumphs

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What your institution will gain
• Better identify market opportunities
• Higher levels of acquisition, retention and protection of
market share
• Higher, irrefutable return on investment with respect to
revenue capture

8. PROFITABILITY
When you are able to marry the general ledger
to the core and other ancillary systems of
record we are able to create a comprehensive
profitability model.

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Building Profitability Analytics
Service
Branch
Region
Institution
Individual
Relationship
(Household)
Customer/
Member
Product
Group
Product
BH Analytics
Systems of
Record
General
Ledger
Allocation rules
Account Level

10. In this system, every product, account,
relationship, household, agent, branch and region
has its own unique income statement that ties to
the overall institution profitability

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Income and expanse allocations
1. Need transaction and statistical data to properly allocate
income and expenses across deposit, loan and service
product lines
2. Cost Center allocations
– Lending Departments
– Branch Operations
– Electronic Services
– Marketing, IT, Administration and other overhead

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Funds Transfer Pricing
1. Simple Pooled Method
2. Singular Yield Curve
3. Multiple Yield Curves
4. Multiple Yield Curves with complex duration estimations

13. HOW TO IDENTIFY AND MITIGATE
PROFIT RISK

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Profit Risk Management
Profit Risk: A risk management tool that focuses on
understanding concentrations within the income statement and
assessing the risk associated with those concentrations from a
net income perspective.
When profit risk is minimized, income volatility is mitigated
allowing income to grow and capital to be stabilized.

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Profit Risk Management
Top 10% Most Profitable
– 400% of net income
– Majority of deposits
– Largest portion of the loan
portfolio
– Cross-sell ratios
– High level of loyalty
– Age
Lowest 50%
– Unprofitable
– Low deposit balance
– Low loan balance
– Cross-sell ratios
– Rate chasers

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Profitability of all relationships
Percent
Number of
Relationships
Total
Profitability
Concentration
Average
Relationship
Profitability
Cross Sell
Services Ratio
10% 2,811 $10,571,269 478.11% $3,761 2.33
20% 2,811 $594,925 26.91% $212 1.74
30% 2,811 <$42,372> -1.92% <$15> 1.20
40% 2,811 <$273,572> -12.37% <$97> 1.29
50% 2,811 <$464,361> -21.00% <$165> 1.28
60% 2,811 <$578,142> -26.15% <$206> 1.09
70% 2,811 <$760,032> -34.37% <$270> 1.90
80% 2,811 <$1,032,057> -46.68% <$367> 2.20
90% 2,811 <$1,587,718> -71.81% <$565> 2.91
100% 2,811 <$4,216,901> -190.72% <$1,496> 3.44
Total 28,110 $2,211,039 100.00% $79 1.94

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Top 10% of relationships
Product/Service
Number of
Relationships
Total
Profitability
Concentration
1% 281 $6,135,006 277.47%
2% 281 $1,296,752 58.65%
3% 281 $813,830 36.81%
4% 281 $581,217 26.29%
5% 281 $451,285 20.41%
6% 281 $368,878 16.68%
7% 281 $302,031 13.66%
8% 281 $252,220 11.41%
9% 281 $203,199 9.19%
10% 281 $166,852 7.55%
Total Top 10% 2,811 $10,571,269 478.11%
Total 28,110 $2,211,039 100.00%

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Product & service profitability
Percent
Number of
Accounts
Total Profitability Concentration
Business Checking 1,889 $2,939,840 132.96%
Business Loans/Lines 1,076 $2,780,340 125.75%
Mortgages 1,592 $1,468,889 66.43%
Retail Money Market 2,054 $385,766 17.45%
Business Money Market 1,178 <$2,861> -0.13%
Cash Management 902 <$42,356> -1.92%
Trust 787 <$50,993> -2.31%
Retirement 2,462 <$64,169> -2.90%
Credit Cards 3,278 <$105,223> -4.76%
Investments 2,042 <$261,919> -11.85%
Certificates of Deposit 5,796 <$296,668> -13.42%
Consumer Loans 4,629 <$821,776> -37.17%
Retail Checking 15,894 <$949,438> -42.94%
Savings 11,590 <$1,051,458> -47.55%
Electronic Services 13,524 <$1,716,935> -77.65%
Total 68,693 $2,211,039 100.00%

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Business vs Retail market profitability
Market
Number of
Relationships
Total
Profitability
Concentration
Business 1,990 $6,023,790 272.44%
Mixed 126 $1,161,611 52.54%
Retail 25,994 <$4,974,362> -224.98%
Total 28,110 $2,211,039 100.00%

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Generational market profitability
Generation
Number of
Relationships
Total
Profitability
Concentration
Gen Y 1,906 <$591,624> -26.76%
Gen X 8,620 <$4,394,110> -198.74%
Boomer 10,811 $661,725 29.93%
Greatest 6,773 $6,535,048 295.56%
Total 28,110 $2,211,039 100.00%

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Branch profitability
Branch
Number of
Relationships
Total
Profitability
Concentration
Main 1,049 $1,844,132 83.41%
Downtown 2,113 $1,785,162 80.74%
Broadway 1,247 $96,965 4.39%
Old Town 2,251 $47,470 2.15%
South 2,277 <$20,688> -0.94%
Park 4,012 <$23,641> -1.07%
Industrial 487 <$38,951> -1.76%
River 1,191 <$110,403> -4.99%
Westside 924 <$115,535> -5.23%
Hill 3,173 <$174,401> -7.89%
Eastside 1,423 <$192,979> -8.73%
Garden 936 <$222,511> -10.06%
Central 2,019 <$240,360> -10.87%
Mall 5,008 <$423,221> -19.15%
Total 28,110 $2,211,039 100.00%

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Officer profitability
Officer
Number of
Relationships
Total
Profitability
Concentration
Leanna 1,370 $1,902,080 86.03%
Charles 1,456 $1,796,041 81.23%
Spencer 1,098 $395,524 17.89%
Javier 706 $165,375 7.48%
Mac 895 $132,672 6.00%
Stephanie 751 $91,509 4.14%
Kevin 933 $16,629 0.75%
Robbie 919 $10,821 0.49%
Ernest 1,034 $8,395 0.38%
Terry 1,331 $5,715 0.26%
Les 1,306 $4,501 0.20%
All Others (25 Officers) 16,311 <$2,318,223> -104.85%
Total 28,110 $2,211,039 100.00%

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The hard reality of a sales culture
Comprehensive data analytics and profitability analysis
reveals that
• Most Customers/Members
• Most Products
• Most Branches
• Most Frontline Staff …
are unprofitable and consistently put the institution at risk.

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Profit risk strategy
1. Set Profit Risk objectives and goals to spread
profitability over a broader number of accounts,
relationships, products, markets, branches and officers
2. Develop strategies and tactical plans to offset profit risk
3. Define institutional success based upon increased
profitability, earnings and capital growth

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Action plan
1. Understand who your break-even customers/members are
2. Go to market with a purposeful plan based upon what you now
know
3. Onboard and welcome new customers/members with a concise
message and call to action
4. Cross-sell products which improve stickiness, profitability, at the
times your customers/members are in the market for them

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What Do You Do Next?
• See me afterwards to discuss any questions I was not able to
address in this session
• Talk amongst your peers about how they are addressing
analytics in their institutions
• Inquire with your Account Executive if you’d like to learn more
or see a product demo of our analytics and marketing
solutions
• If you are looking for some literature or case studies visit
BakerHill.com

27. Questions