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8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
1/25
Analytics Solutions for
Retail Banking
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
1
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
2/25
Marketelligent: Managing Risk & Reward across Retail Banking
Customer
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
2
CardCredit Card
Charge Card
Revolving
Installment
InvestmentsUnit Trust
S. Notes
Bonds
Equities
Insured
InsuranceCredit
General
Life
DepositTerm deposit
Unfixed
LoanRevolving
Installment
Secured
Portfolio Finance
CASACurrent Acct
Savings
MortgageRevolving
Installment
Lend InvestSpend Transact Protect
Customer Acquisitions Customer Segmentation Marketing Investment Optimization Cross-sell/One-sell
Branch location placement Growing profitable balances MIS
Risk Management Collections & Recoveries Flow of Funds Executive Dashboards
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Delinquency Scorecards
First pay Default Scorecard
4th or 5th c cle Risk Scorecard
Decide Loan pricing
and amount
Identify Customers most
likely to default so as to
take corrective action
Identify Customers most likely
to attrite so as to take
proactive actions for retention
And across the Customer Lifecycle
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
3
Approval Scorecards
Conversion Scorecards
Application Fraud
Revenue Scorecards
Profitability Scorecards
Pricing and
Loan Amount
Collection Scorecards
Self-cures
Re-Activation
Winback
Retention
Decision on who to approve
based on expected profitability
Maximize Collections
Efficiencies
Target Inactive Customers for
repeat loans
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Our Expertise in Risk & Marketing Analytics
Marketing Analytics
1. Profit-based Customer
Acquisition Strategy
1. Credit Delinquency Models
2. Other Delinquency Models; eg.
Credit Risk AnalyticsCredit Risk
Management &
Training1. To understand existing data /
reports and present a top-line
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
4
2. Revenue Models; eg. Total 180
days revenue
3. Campaign Management
4. Cross-sell
5. Retention & Activation
6. Loyalty and Winback
7. Pricing Analytics
5+ cycles bad
3. Customer Approval and
Conversion Models
4. Optimal Loan Amount, Pricing
and loan duration
5. Forecasting
6. Collections Analytics
7. Mortgage Portfolio Optimization8. Fraud Analytics
9. Basel II Analytics
"what additional analytics to
read"
2. Prepare and deliver the
additional analytics and
highlight key concerns on
policies and processes
3. Present credit policy
changes, collections strategies
and product program changesto deliver required
management deliverables
4. Credit Policy Training
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
5/25
New Accounts Acquired
Accounts Closed
Account Activation rate
Payment Rate
Total Ending Receivables
Interest
Bank P&L
Acquire New Customers
- Segments X Products X Channel- Mailbase Expansion- Pricing
Reduce Customer Attrition
- Voluntary / Involuntary- Retention Strategies
- Winback
Increasing activation rates- Deepening Engagement- Inactive Customer Treatment
Improve profitability ofAssets
- Balance Transfer- Credit Line Strategies
-
Marketelligent: A strong P&L discipline to all analyticsEg. Credit Cards
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
5
Net Interest Margin
Risk-based Fees
Interchange
Affinity Rebates
Cross-Sell
Annual Fees
Net Credit Losses
Net Credit Margin
Operating Expenses
Loan Loss reserve
Net Income
REVENUES
EXPEN
SES
Maximizing Interest Revenue- Product Pricing- Customer Behavior Revolvers, transactors, etc
Maximizing Fee Revenue- Over Credit limit
- Delinquency- Bad Check
Reduce Net CreditLosses
- Credit Line strategies- Pricing strategies
- Collections
Increasing Cross-sell Revenues- Revenue Enhancing Products- Breadth of relationships
Top-down approach
Analytics that impact all line items of the P&L
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
6/25
Marketing Analytics
Credit Risk Analytics
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
6
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
7/25
Profit-based AcquisitionAcquisition strategies that balance Risk & Reward
Approval Model
Acquisition
Objective
Implement a Customer-level profit-based Acquisition Strategy based on
segmentation, predictive models and joint scores
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
7
Conversion Model
First Pay Default Model
5+ cycle Default Model
180 day Revenues
Reactivation Model
Risk
Revenue
Flexible
Acquisition
Strategy
Individual Scores Strategy Matrix
Joint Scores
Illustrative
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Customer Segmentation
Segment Customers to better understand their needs & wants
Key Bureau Attributes
OverModerate High Moderate
HighAccess
ModerateAccess All
Very High utilizationof revolving credit
Lower access to
credit as a groupLowest FICO
Very high access tolimits
Very high balances
Above averageutilization and risk
Very high access tolimits
High balances, but
low utilizationLower risk
Defined as balance 50% utilized 78.0% 32.1% 23.5% 5.7% 5.1% 2.6% 0.5% 12.1%
FICO Score 684 712 725 702 764 782 772 751
Moderate limits
High balances andutilization
Increased risk
Moderate limits
Below averagebalances
Higher risk
Moderate limits
Low balances andutilization
Lowest risk segmentSegmentation using SAS PROC FASTCLUS
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Universe ManagementEligibility, Risk
Performance TrackingTesting discipline, MISUniverse
Building Profitable Assets
Balance transfer strategies to build profitable assets
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
9
Segmentation
OfferStrategy
Tracking
Offer StrategyPricing / Duration / Fees
Universe SegmentationCustomized Marketing
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Pricing Analytics
Customer-level pricing to build Deposits
TD Elasticity Curve
50000
100000
150000
200000
Change
Rate hunter
Moderate Mover
Term Deposits Pricing Sensitivity Curve
Retail Banking
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
10
-200000
-150000
-100000
-5000050403020100-10-20-30-40-50
deviation From market(bps)
Balan
ce Loyal depositor
Lazy Depositor
Pricing is one of the most sensitive lever to improve profitability. We can build tools to establish
the price sensitivity of various customer segments. Based on this, pricing strategies can be
developed for different segments to maximise profitability through better margins and/or better
volumes.
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Cross-selling
Deepen engagement with existing Customers
Installment
Loans
Mortgages- Which Customer to target
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
11
Existing
Retail Banking
Customer
HELOC/FRHEL
Credit Cards
Wealth
Management
- What Product to Offer
- Impact of new product on
existing Product Profitability
- Overall Profitability
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
12/25
alue
Retention
Activation
Retention & Activation
Manage Customers across their Lifecycle
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
12
Acquisition Usage & LoyaltyTime
RETENTION Identify Customers at Risk of Disengagement via
predictive modeling or activity-based segmentation
Take proactive actions via targeted offers
RETENTION Identify Customers at Risk of Disengagement via
predictive modeling or activity-based segmentation
Take proactive actions via targeted offers
ACTIVATION Segment Inactive Customers across various
dimensions
Implement targeted activation campaigns
ACTIVATION Segment Inactive Customers across various
dimensions
Implement targeted activation campaigns
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
13/25
Marketing Analytics
Credit Risk Analytics
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
13
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
14/25
Credit Risk Analytics
Predictive Scorecards to optimize Decisions
1. Approval ScorecardsCustomer-level score to decision on which
Customer to approve and which to decline for
New Products (loans, cards, etc) based on
information provided application data, bureau
data, etc.
70%
80%
90%
100%
Eg. Delinquency Scorecard
Rate
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
14
2. Delinquency ScorecardsCustomer-level score to decision on which
Customer is going to default on their loans so as
to enable the business to take proactive actions
to minimize losses
3. Collections ScorecardsCustomer-level score to decision on whichdelinquent Customer has a higher likelihood of
paying back balances; and which Customer is
likely to self-cure; so as to enable business to
optimize Collections activities
Predictive Models using SAS PROC LOGISTIC
0%
10%
20%
30%
40%
50%
0 1 2 3 4 5 6 7 8 9 10
Random
New Model
Existing ModelCumulativeDe
faul
Score deciles
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Model captures63% of First Pay
Defaulters in
40% of
Accounts
#
AccountsCuml % FPD
Marginal
rateCuml % Non-FPD
Marginal
rateCuml % KS
789 887 512 10% 368 72% 23% 144 28% 4% 28.03
756 788 518 20% 271 52% 39% 247 48% 11% 39.36
731 755 506 30% 209 41% 52% 297 59% 20% 41.32
710 730 493 40% 177 36% 63% 316 64% 29% 41.88
693 709 583 51% 170 29% 74% 413 71% 40% 39.74
680 692 480 60% 111 23% 81% 369 77% 51% 34.65
659 679 493 70% 103 21% 87% 390 79% 62% 28.33
615 658 512 80% 86 17% 92% 426 83% 74% 21.12
Score Range
High
Risk
Credit Risk Analytics
Eg. First Pay Default Scorecard
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
15
.
180 412 511 100% 59 12% 100% 452 88% 100% 0
. . 5129 . 1619 32% . 3510 68% . 41.88
Score # Customers # Bad Loans# Bad Loans in
past 30 days
# Inquiries in
past 60 days# Loans given
0 512 1.30 1.15 8.85 1.76
1 518 0.55 0.41 10.61 1.41
2 506 0.10 0.03 7.43 0.543 493 0.03 0.01 5.01 0.34
4 583 0.02 0.00 2.55 0.18
5 480 0.04 0.01 3.61 0.59
6 493 0.02 0.01 3.45 0.75
7 512 0.03 0.01 3.45 1.08
8 521 0.04 0.00 3.10 1.45
9 511 0.05 0.01 3.00 4.26
Grand Total 5129 0.22 0.17 5.09 1.23
High Risk
Customers havea significantly
higher # of loan
inquiries in the
past 60 days
High
Risk
Low
Risk
Low
Risk
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Behavioral ModelsRevenue and Cost
Drivers Optimal Line Determination Optimal Line Drivers
Balance
Model
Revenue
Credit Risk Analytics
Control Exposure with right appropriate Lines of Credit
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
16
RevolveModel
Risk Model
LOCOptimal LOC
LOC
Cost
LOC
Predicted V/s Actual Inactivity
0.00
50.00
100.00
150.00
200.00
250.00
300.00
0 50 100 150 200 250 300 350 400
Predicted Inactivity
Ideal
c ua
Predicted
Illustrative process for assigning
Optimal Line of Credit (LOC)
Other
Models
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
17/25
Collections Analytics
Prioritize Customers to action on to optimize Collections efforts
OBJECTIVE
Collect more $ efficiently thereby reducing cost/dollar collected
OBJECTIVE
Collect more $ efficiently thereby reducing cost/dollar collected
Unique strategies across various stages: early-stage; late-stage; charge-off/recovery
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
17
Mine Customer &Operational data
Create broad profiles and
segments
Profiling & Segmentation
Rank order accountson a dimension ofinterest
Event probabilities :self sure; charge-off,etc
Expected value ofCollections
Behavior Scorecards
Assess & create smallersegments acrossmultiple scores
Assess trade-offsbetween strategies
Multi-dimensionalAnalysis
Test and Evaluateactions underbusiness constraints
Typically black-box,heuristically drivenmodels
Selecting OptimalStrategies
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Mortgage Portfolio Optimization
PREDICT
PREDICT
OPTIMIZE
OPTIMIZE
AUTOMATE
AUTOMATE
OBJECTIVE
Optimal treatment for each Customer so as to maximize NPV givenbusiness constraints
OBJECTIVE
Optimal treatment for each Customer so as to maximize NPV givenbusiness constraints
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
18
Optimization analytics using
action-effect models to
select the best action foreach customer, given
business objectives and
constraints
NPV calculationsfor all possible
Outcomes
NPV calculationsfor all possible
Outcomes
Optimal Treatmentfor each CustomerOptimal Treatmentfor each Customer Business Rules forDecisioningBusiness Rules forDecisioning
identify likely outcomes of
different actions for
different customerprofiles, and the overall
effect on the NPV of
portfolio
Build rules that can be
deployed through your
business rules managementsystem
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Fraud Analytics
Manage for Fraud while ensuring a positive Customer experience
More InformationResponsible use of data is a
powerful weapon
against fraud
Break ConventionsTraditional credit scoring
and underwriting
procedures do not identify
fraudulent applications
Dig DeeperOnline verification of
information beyond a
Social Security number is
needed
Look for InconsistenciesVerification processes
should check for
consistencies in address and
credit bureau information
OBJECTIVEMinimize Fraud-related Losses and Fraud-related expenses while ensuring a positive Customer experience
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
19
SSN
FRAUDFIRST
NAME
LASTNAME
DOB
ADDRESS
WORK
PHONE
HOME
PHONE
ID
NO MATCH
SAME
Rules-based
Neural Networks
Illustrative for Insurance Claims
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
20/25
A model was built to predict the charge-off rate in the US economy. It performs well in both
observation and validation windows except for two peaks that cannot be attributed to
macroeconomic factors
OVERALL USA CHARGE-OFF RATE (%)
5.00
Due to Post
9/11Due to change in
Bankru tc law
Independent
Variables
Sign
Total Consumer +
Forecasting
Eg. Portfolio-level Charge-off forecasting
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
20
Actual Model built Validation Forecast
0.00
1.00
2.00
3.00
.
1986Q4 1989Q4 1992Q4 1995Q4 1998Q4 2001Q4 2004Q4 2007Q4
Federal Rate +
Houses for Sale -
DisposablePersonalIncome
-
Average WeeklyEarnings-
FinancialObligations
+
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Pillar I
Minimum CapitalCredit Risk Market Risk Operations Risk
Our experience in Basel II
Basel II Analytics
Pillar 1 Credit Risk & Operations Risk
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
21
Standardised
IRB*- Foundation
IRB*- Advanced
Same approach as Basel I
Local, Small Banks
Internal-ratings based
PD inputs provided by bank, rest by Regulator
Multi-line National Banks
Internal-ratings based
PD, EAD, LGD based on inputs provided by bank
Large Global Banks
* IRB - Internal Ratings Based Approach
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
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Marketelligent: A strong P&L discipline to all analytics
Eg. Credit Cards
New Accounts Acquired
Accounts Closed
Account Activation rate
Payment Rate
Total Ending Receivables
Interest
Bank P&L
Acquire New Customers- Segments X Products X Channel
- Mailbase Expansion- Pricing
Reduce Customer Attrition- Voluntary / Involuntary
- Retention Strategies- Winback
Increasing activation rates- Deepening Engagement- Inactive Customer Treatment
Improve profitability ofAssets
- Balance Transfer- Credit Line Strategies
-
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com
24
Net Interest Margin
Risk-based Fees
Interchange
Affinity Rebates
Cross-Sell
Annual Fees
Net Credit Losses
Net Credit Margin
Operating Expenses
Loan Loss reserve
Net Income
REVENUE
S
EXPE
NSES
Maximizing Interest Revenue- Product Pricing- Customer Behavior Revolvers, transactors, etc
Maximizing Fee Revenue- Over Credit limit
- Delinquency- Bad Check
Reduce Net Credit
Losses- Credit Line strategies- Pricing strategies
- Collections
Increasing Cross-sell Revenues
- Revenue Enhancing Products- Breadth of relationships
Top-down approach
Analytics that impact all line items of the P&L
8/8/2019 Analytics Solutions for Retail Banking_Marketelligent
25/25
Thank You
ASHLEY MARKETELLIGENT PVT LTD
+91-80-26642802 (India)
1-408-834-8822 (USA)
Confidential & proprietary information. Property of Ashley Marketelligent Pvt Ltd.
www.marketelligent.com