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Collections transformation – turning opportunities into results
Edward Stephens PECO
Luke Aull Experian
Cynthia Hatcher Experian
#vision2014
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Test and learn / adapt to changing circumstances
Internal
data
External
data
Automated
Manual Optimization
Customer-level
optimization
Accounts
Score
payers
Non payers
Modelling
Segmentation
and scoring
Data Scoring Decision systems Workflow Reporting
Strategic and
Operational
Account Level
Segmentation
Best practices in collections strategic decisioning and operational execution
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PECO opportunities
Edward Stephens
PECO
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Best-in-class collections performance for a northeastern urban utility is net charge-offs of 0.7% of revenue
Regulatory recovery for bad debt expense is a based upon 3-year actual net charge-offs history
Q1 Top Tier
Benchmark
Entirely different collection environments:
southern, western, & rural utilities
U.S. Panel
PECO Performance Path
Industry Average / Top
Regional Performer
2009
(1.84%)
2012
(1.3%)
2015
Aspiration (0.7%)
Q3
(0.9%)
PECO Target Gap: regulations,
demographics, systems, decision
tools and processes
Polaris benchmark – net charge-offs as a percentage of revenue
PECO opportunities
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Customer collections platform limited capability in flexibility and speed of response:
Significant limitations imposed by resource constraints and code conflict within the customer platform
Collections team was unable to implement changes in a timely manner, which greatly inhibited the businesses ability to be nimble in responding to opportunities to reduce cost and bad debt
Incremental improvements to the customer platform were very expensive and could not move the company to best-in-class performance
PECO opportunities
5
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PowerCurve™ Customer Management
Enabled improved collections through increased segmentation and risk assessment of customers based on collection teams control and maintenance of their scorecard models and business strategies
► Provided continuous testing and refinement of alternative treatment approaches
Marketswitch® Optimization
Determined optimal allocation of field collection resources based on business-derived goals and constraints
Business solution overview
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PowerCurve™
Customer Management
Cynthia Hatcher
Experian
Edward Stephens
PECO
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Process prior to solution implementation:
Collection treatments based on reserve risk scoring model
All customers within a determined risk segment received the same collection treatment
Changes to collection actions required opening a change request, which required time and cost estimates for implementation
PECO internal process
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New process using PowerCurve™ Customer Management:
PECO business users develop and modify collection paths for customer platform implementation
Champion / challenger collection scores used to determine risk segment
Collection treatments based on a champion / challenger risk segment approach
48 collection paths created (24 residential, 15 commercial, 4 final, 5 special handling)
Champion / challenger performance measured periodically
New collection paths provide consistent pre-termination collection actions which resulted in a positive impact on inbound call volume (volume reduction)
Leverage new data elements for collection path segmentation (low income, balance, deposit coverage, etc.)
PECO internal process
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Collections segmentation
Risk and behavioral based
Final bill for $550
Final bill reminder
Terminate for non-pay
Automated call
Eligible for termination
Bill for $400
Agency
Write off
Bill for $200
Disconnect Notice
1
29
34
35
44
50
83
57
91
147
Activity Day
10
Risk-based
Eligible for termination
Terminate for non-pay
Reminder letter
Disconnect notice
Bill for $600
Reminder letter
Final bill for $750
Final bill reminder
Write Off
Agency
Bill for $200
Bill for $400
1
34
41
66
67
68
86
79
93
121
142
184
Activity Day
37 days improvement
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Twenty-five challenger summer paths were implemented – 70% out performed champion paths
Low risk segment customers were more responsive to challenger path strategies (i.e., additional number of actions or timing of actions)
Next steps:
Eliminate challenger paths that resulted in negative results – high risk residential and low income high risk residential customers
Develop and implement new collection strategies for these segments
Develop and implement strategy for high risk customers using new commercial scoring
Champion / challenger benefits
11
Population Number of challenger paths Number of successful challengers
Low risk residential 8 5
High risk residential 5 3
Residential low income 3 3
Special handling 2 1
Small commercial 7 6
Total 25 17
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PECO business team controls and maintains collections strategies
Scorecards (PECO models and Experian’s Financial Stability Risk ScoreSM)
Customer segmentation (scores and business rules)
Champion / challenger and advanced decisioning (e.g., commercial disconnect notice, final proactive call, etc.)
Treatment rules definition (e.g., letter on day X, call on day Y, etc.)
Access to external collections data
Benefits of collections transformation
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Embedded strategy consulting and support throughout engagement lifecycle
Performance monitoring and benchmarking
Test-and-learn strategy enhancement
Benefits of collections transformation
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Marketswitch
Optimization®
Luke Aull
Experian
Edward Stephens
PECO
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PECO to improve its collection activities by:
Decreasing annual write-off amounts
Reduce the overall cost of field collections activities
Field collections optimization project Business requirements
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Deploy into the current daily field collections processes
Daily selection and creation of the service terminations list
► PECO to control selection and fielding of terminations
► Flexibility to make changes as business needs change – change objective function, constraints or rules
► Flexibility to change optimization process depending upon resource availability and seasonal regulatory restrictions
Field collections optimization project Business requirements
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Process prior to implementation
Derive a list of all past due accounts eligible for termination that cut out collection orders issued
Volume was approximately 15,000 accounts per day
Cuts were prioritized and selected for termination by the field vendor
Field collections optimization project Solution
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Implement Marketswitch Optimization®
Marketswitch Optimization® processes the daily list of all PECO accounts with the last collection action eligible to cut and CNP pending
Daily volume 1,500 to 3,000 accounts
Marketswitch Optimization® selections based on the most valuable to cut accounts based on a business defined objective function
Daily optimized cut list sent to the field vendor accounts to be fielded the next day
Field collections optimization project Solution
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Business objective function
Primary business objective function
► Reduce past due AR > 60 days
Additional objective functions
► Maximize successful cuts
► Maximize $ collected in the next 30 days
► Maximize expected recovery past due balance
► Minimize new billings that go bad
Field collections optimization project Design and structure – objective function
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Business and operational constraints
Limits on available field collections resources
► Skill set (bucket, meter, or AMI) and geographic availably
► Differentiate accounts by bucket truck, meter hand and AMI
► ZIP Codes™ used to group potential accounts to be assigned to resources
Field collections optimization project Design and structure – constraints
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Grouping accounts using the building or premise identification
Gain efficiency by applying a rule that if optimization selects an account and there are other accounts eligible for termination
Business rules to ensure that certain accounts are selected daily based on account balance and status
► Accounts with unpaid balances greater than $5.0K
► Low income accounts with balances > $1.0K
Field collections optimization project Design and structure – constraints
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Two decisions made in separate optimization stages
Specific accounts to be cut by territory
► Territories defined set of contiguous ZIP Codes™ and by the type of field resource required to make the service cut
► Refined over time to reflect prior field collections experience
► Territories grouped together by the different field resources; meter hands, bucket crews and AMI (Automated Meter Infrastructure)
Field collections optimization project Design and structure – decisions
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Two decisions made in separate optimization stages
Assign each account to a specific field resource
► Individual field resources may be assigned to more than one territory, subject to an adjacency constraint
► Each field resource also has a schedule of availability for specific territories by date
► Rules based on grouping of territories are used to assign selected accounts
Field collections optimization project Design and structure – decisions
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Highest balances
Age of delinquent balances
Number of days in the eligible to cut window
Returned checks
Last payment made (date)
Defaulted payment plan
Meter location (inside vs. outside)
Resource capabilities/limitations
LiHEAP recipients
Recently removed protection
Regulatory constraints (seasonal limitations)
Field collections optimization project Design and structure – data
Different scenarios / business goals can now be run against the accounts entering the field for termination
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Field collections optimization project Benefits from optimized cut list benefits
2013 Annual and Monthly Field Collections Results
-30% -20% -10% 0%10%
20%30%
40%50%
60%
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
2013
14%
21%
35%
21%
22%
16%
7%
1%
-8%
-2%
-5%
12%
22%
40%
56%
12%
8%
9%
-24%
-17%
4%
20%
6%
11%
% Improvement Avg. $ Value per Cut
% Change Avg. $ Value Available Work
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PECO
Collection Transformation
Benefits
Cynthia Hatcher
Experian
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Exelon business users have control of collections strategies
Scorecards (PECO models and Experian’s Financial Stability Risk ScoreSM)
Customer segmentation (scores and business rules)
Champion / challenger and advanced decisioning (e.g., commercial disconnect notice, final proactive call, etc.)
Treatment rules definition (e.g. letter on Day X, call on Day Y, etc.)
Access to external collections data
Collections transformation benefits
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Flexibility to change optimized field collections strategies
Business control of field collections
Replaced manual build cut list with new automated process
Leveraged analytics built on historical field collections performance
Opportunity to develop additional analytics to drive better collections results
Collections transformation benefits
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Q&A
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