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GROW, OPTIMIZE, PROTECT: USING
BUSINESS INTELLIGENCE AND
MARKETING TO GET A BIGGER SLICE
OF THE PIE
James McHale, SVP/GM Analytics at Baker Hill
Bryan Thomas, VP of Lending at On Tap CU
PROFIT RISK AND HOW TO
IDENTIFY AND MITIGATE IT
Confidential & Privileged Document
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 …”
Confidential & Privileged Document
Profit risk management
Profit Risk: concentration of income statement
vs. distribution and diversification of income
streams
When profit risk is minimized, income volatility
is mitigated and income and capital are
sustained and grow, and the financial institution
remains viable.
Confidential & Privileged Document
Five most common uses of big data
1. Fraud Detection
2. Compliance and
Regulatory Requirements
3. Customer Segmentation
4. Personalized Marketing
5. Risk Management
Confidential & Privileged Document
Your 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 based upon
achieving sustainability
Confidential & Privileged Document
Your call to action
4. Define acceptable “Profit Risk” concentration
levels
5. Set “Profit Risk” objectives and goals to
spread profitability over a greater spread of
customer/member relationships, products,
markets, branches and officers
Confidential & Privileged Document
Your call to action
6. Establish “Profit Risk” discipline
7. Develop “Profit Risk” strategies and tactical
plans
8. Define institutional success based upon
increased profitability, earnings and capital
growth
Confidential & Privileged Document
What your institution will gain
1. Improved identification of market
opportunities
2. Higher levels of acquisition, retention
and protection of market share
3. Higher, irrefutable return on
investment with respect to revenue
capture
Building our future – Strategy shift to On-Tap CU
10
• Perceived Exclusive Field of
Membership
• Aging Membership
• Strategic Directional Change from
Billion Dollar Brand
11
Organizational ScoreCard Elements:
• Millennial Wallet Share – Products
& Services
• Millennial Membership Growth
(Overall)
Building our future – Strategy shift to On-Tap CU
Marketing and growth initiative
12
• Opportunity: Target
Millennials
– Certificate of Deposit
• Cross sell to Millennial group without CD (3,873
Relationships)
– When a Millennial has a CD in relationship:
Average Profit per Relationship increases
1,290%
Cross-Sell Service Ratio increases 158%
Cross-Sell Account Ratio increases 278%
Confidential & Privileged Document
Marketing and growth initiative
• Deepen Indirect
Relationships
– New Interest
Rewards
Checking
– New Online
Banking
Solution (Q2)
13
Baker Hill Prosper 2017 - Grow, Optimize, Protect: Using Business Intelligence and Marketing to Get a Bigger Slice of the Pie

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Baker Hill Prosper 2017 - Grow, Optimize, Protect: Using Business Intelligence and Marketing to Get a Bigger Slice of the Pie

  • 1. GROW, OPTIMIZE, PROTECT: USING BUSINESS INTELLIGENCE AND MARKETING TO GET A BIGGER SLICE OF THE PIE James McHale, SVP/GM Analytics at Baker Hill Bryan Thomas, VP of Lending at On Tap CU
  • 2. PROFIT RISK AND HOW TO IDENTIFY AND MITIGATE IT
  • 3. Confidential & Privileged Document 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 …”
  • 4. Confidential & Privileged Document Profit risk management Profit Risk: concentration of income statement vs. distribution and diversification of income streams When profit risk is minimized, income volatility is mitigated and income and capital are sustained and grow, and the financial institution remains viable.
  • 5. Confidential & Privileged Document Five most common uses of big data 1. Fraud Detection 2. Compliance and Regulatory Requirements 3. Customer Segmentation 4. Personalized Marketing 5. Risk Management
  • 6. Confidential & Privileged Document Your 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 based upon achieving sustainability
  • 7. Confidential & Privileged Document Your call to action 4. Define acceptable “Profit Risk” concentration levels 5. Set “Profit Risk” objectives and goals to spread profitability over a greater spread of customer/member relationships, products, markets, branches and officers
  • 8. Confidential & Privileged Document Your call to action 6. Establish “Profit Risk” discipline 7. Develop “Profit Risk” strategies and tactical plans 8. Define institutional success based upon increased profitability, earnings and capital growth
  • 9. Confidential & Privileged Document What your institution will gain 1. Improved identification of market opportunities 2. Higher levels of acquisition, retention and protection of market share 3. Higher, irrefutable return on investment with respect to revenue capture
  • 10. Building our future – Strategy shift to On-Tap CU 10 • Perceived Exclusive Field of Membership • Aging Membership • Strategic Directional Change from Billion Dollar Brand
  • 11. 11 Organizational ScoreCard Elements: • Millennial Wallet Share – Products & Services • Millennial Membership Growth (Overall) Building our future – Strategy shift to On-Tap CU
  • 12. Marketing and growth initiative 12 • Opportunity: Target Millennials – Certificate of Deposit • Cross sell to Millennial group without CD (3,873 Relationships) – When a Millennial has a CD in relationship: Average Profit per Relationship increases 1,290% Cross-Sell Service Ratio increases 158% Cross-Sell Account Ratio increases 278%
  • 13. Confidential & Privileged Document Marketing and growth initiative • Deepen Indirect Relationships – New Interest Rewards Checking – New Online Banking Solution (Q2) 13

Notas do Editor

  1. Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is  to better understand their customers through segmentation. Big data enables them to  group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their  segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s  supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
  2. Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is  to better understand their customers through segmentation. Big data enables them to  group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their  segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s  supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
  3. Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is  to better understand their customers through segmentation. Big data enables them to  group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their  segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s  supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
  4. Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is  to better understand their customers through segmentation. Big data enables them to  group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their  segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s  supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
  5. Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is  to better understand their customers through segmentation. Big data enables them to  group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their  segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s  supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
  6. Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is  to better understand their customers through segmentation. Big data enables them to  group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their  segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s  supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.