The document summarizes a project to reduce underwriting resubmits at a bank. Key points: 1) Resubmits were found to be high at 55% due to unfavorable scores and lack of communication on expectations. A new process was implemented where underwriters call bankers after submission to discuss loans. 2) This led to a reduction in resubmits to 20% and cut cycle time by 13 hours and 4 hours per avoided resubmit. Bankers thanked the team for the helpful calls. 3) Further analysis showed many resubmits were due to unfavorable results at the end of the process that could have been caught earlier. Recategorizing data found a high percentage

1. Black Belt Project Storyboard
Reducing Underwriting Resubmits
Peter Tyson Simmons

2. Storyboard Checklist

3. Executive Summary
Key Take Away: A little bit of time upfront discussing the loan has made a clear
impact on resubmits, cycle time, and rework!
Business Case
Root Cause Analysis
What are the critical findings/root causes that were discovered?
Solutions Implemented
It was determined that many resubmits were do to unfavorable scores and
bankers unaware of what scores to expect. Many of these went through the
entire process and then would have to go through the entire process again.
We identified a correlation between communication (phone) and resubmits.
Graphical Display of Improvement
List key solutions that were implemented to address root causes
1. Created a phone queue that bankers are required to call right after
submission. This call is for the expert analysts to help bankers vet loans, level
set on expectations, and catch obvious resubmit causes early before fully
underwriting.
Insert a chart, graph illustrating before and after process improvement
(Control or Run Chart indicating the date improvements were made or
Box Plot comparing Before and After)
Executive Summary
Project Results
What is the importance of doing this project? (State in lost dollars,
productivity loss, customer dissatisfaction, cost avoidance, risk, etc.)
What are the measurable process improvements/wins?
Resubmits have dropped to 20%, reducing lead time by 13 hours and
cycle time by 4 for each resubmit avoided.
Bankers have thanked the team directly for the calls explaining and
walking them through the process and potential issues!
It takes anywhere from 6 to 16 hours to put together a loan underwriting
package for our commercial loan group; and 55% of these submissions have
to be resubmitted and reworked for one reason or another. Reducing the
number of resubmits will reduce the amount of unnecessary and repetitive
work, which will in turn reduce the amount of time and money it takes to
complete a loan, resulting in better CX and giving Synovus a competitive
advantage.

4. Define Phase

5. Project Charter
Key Take Away: Everyone is onboard and wants to process loans for our
customers faster, and avoid having to follow up and request more docs.
Phase Planned Actual
Define: 9/10-9/30
Measure: 10/1-10/31
Analyze: 11/1-11/16
Improve: 11/17-11/30
Control: 12/1-12/4
Process Start: Position Person
Process End: Team Lead Peter Simmons 20%
Sponsor Matt 10%
In: Team Member Robert 20%
Out: Team Member Underwriters 20%
Team Member
Project Charter
Problem Statement Business Case & Benefits
Reduce Underwriting Resubmits
Underwriting
Underwriting resubmits, underwriting process high-
level, front line actions and requirements, and
queueing systems and tools.
Scored loans, detailed underwriting process,
underwriting tools.
Time Commitment
Goal Statement Timeline
Decrease the Application Resubmit rate from 55% to 40% by
12/4/18
Scope In/Out Team Members
Front line submissions
Reduce the number of unnecessary resubmits by enhancing the
process and identifying solutions for the leading causes for
unnecessary resubmits.
It takes anywhere from 6 to 16 hours to put together a loan
underwriting package for our commercial loan group; and 55% of
these submissions have to be resubmitted and reworked for one
reason or another. Reducing the number of resubmits will reduce
the amount of unnecessary and repetitive work, which will in turn
reduce the amount of time and money it takes to complete a loan,
resulting in better CX and giving the Bank a competitive advantage.

6. Voice of the Customer
Key Take Away: These aren’t new to the team, but reducing resubmits would
help with all 3.
Customer Comment
(What Are They Saying?)
Identifying the Issue
(What's the Priority? -
Choose from Dropdown List)
Customer Requirement
(What's the Measurable Target?)
Voice of the Customer Translation Matrix
It takes to long to go through underwriting Timeliness
2 business days to complete underwriting
package
We have to keep submiting Accuracy Less than 40% resubmit rate
It's complicated to make sure we have
everything right
Ease of Use Less than 40% resubmit rate

7. SIPOC
Key Take Away: The main focus of this project is on loans that need to go
through this process multiple times
S I P O C
Suppliers Inputs Process Outputs Customers
Underwriters
Applicant Applications
Bankers
Application
Documents
Underwriters
Application from
bankers
Loan Approval
Reviewer
Underwriter’s score
of customer and
applications
Loan is denied, new
conditions are added,
or loan moves on to
due diligence stage
Applications and
required financial
information
SIPOC
Customer provides
the banker with
information for the
application
Banker sends the
application and
documents to the
underwriter
Underwriter uses
financial information
to create ratios and
risk scores for
customer loan
Loan is reviewed and
decision to move
forward or not is
made based on
underwriting score
Customer Requirements
financial analysis,
ratios, risk score, and
writeup
Approval, new
conditions, or denial
of the loan
Banker and Approval
Reviewer
Customer and Banker
Accurate
(Customer should be told what docs and forms they
need to complete/submit)
(Should only need to complete/submit once)
On-Time
(Underwriting Process should be completed in 2
business days)

8. “As Is” Detailed Map Segment
Key Take Away: It surprised the team how many ways loops and people made
decisions at the end of the process that went all the way back to the start.

9. Measure Phase

10. Data Collection Plan
Key Take Away: This grew from when we first created it, as we identified
additional measures through the analyze phase.
Measure Title
Data Type
(Continuous
or Discrete)
Operational Definition
Stratification
Factors
(By who/what/
where/when)
Sampling Notes
(Time Frame, etc.)
Who and How
(Person responsible and
method - Check Sheet?)
Resubmission
Rate
Percentage -
Continuous
Each loan request that is sent in for more than
one underwriting request (one loan can have
multiple resubmits)
By Analyst Use entire population
data set
Manager to pull from tracking
sheet
Number of
Resubmits
Discrete
Each loan request that is sent in for more than
one underwriting request (one loan can have
multiple resubmits)
By submitter
last 3 months entire
population
pull from tracking sheet
Cycle Time
time -
continuous
When request is accepted by analyst to when
request is marked complete
To process first time
To process a
resubmit
Sample all requests for
each analyst for a week -
time to complete for
original and resubmit.
Note: Volume fluctuates
based on time of month
etc but type and time
does not.
team member time tracker
Lead time
time -
continuous
When request is created to when request is
marked complete
To process first time
To process a
resubmit
Use entire population
data set from system -
minus cycle time
(calculated above)
manager to pull from system
(will be estimated since cycle
time is off a sample)
Resubmission
Reason
Categories -
Discrete
Reason loan was resubmitted none
going to use last 3
months because of
category changes and
procedure change
manager to pull from tracking
sheet
Analyst
Communication
time and
frequency
Count - Discrete
Time -
continuous
How often do they make contact with the
banker and how long
By email
By Phone
Survey the analysts Analyst survey
Data Collection Plan

11. Baseline – Project Y
Key Take Away: This chart clearly shows the process is running well above the
desired target of less than 40%. (Data before 2018 is omitted due to reliability)
Specification Limit

12. Baseline – Resubmit Categories
Key Take Away: Reviewing the categories there are clearly a select few to
focus on. This chart drove our MSA.

13. MSA Results
Key Take Away: Because every loan is different and the process can be done multiple ways,
resulting in a resubmit for one analyst and not another, and the amount of time it takes to
process a package, we did not conduct an MSA for resubmit yes or no. Instead we focused
our MSA on categorizing resubmits. 12 scenarios were printed on index cards and 2 analysts
were asked to categorize them to measure reproducibility. We then had them review the
same cards in a different order to measure repeatability.
Analyst A Review Order1 1 2 3 4 5 6 7 8 9 10 11 12
Analyst B Review Order1 3 4 7 6 11 1 10 8 2 9 12 5
Analyst A Review Order2 7 2 12 8 9 10 6 1 3 11 5 4
Analyst B Review Order2 1 2 3 4 5 6 7 8 9 10 11 12
Scenario1
Scenario2
Scenario3
Scenario4
Scenario5
Scenario6
Scenario7
Scenario8
Scenario9
Scenario10
Scenario11
Scenario12 Loan Amount Change
New Financials New Financials
Loan Amount Change Loan Amount Change
Interest Rate Change New Financials
Other
New Financials New Financials
Other Other
Other
Other Other
Interest Rate Change Interest Rate Change
New Financials
Loan Amount Change
New Financials
Loan Amount Change
Analyst A2
Other
Collateral Updated
Loan Amount Change
Analyst B2
Loan Amount Change Loan Amount Change
Collateral Updated Collateral Updated
Loan Amount Change
Analyst B1
Loan Amount Change
Collateral Updated
Other
Other
Interest Rate Change
Other
New Financials
Other
Collateral Updated
New Financials
Other
New Financials
Loan Amount Change
Interest Rate Change
Interest Rate Change
Analyst A1
Loan Amount Change
Collateral Updated
Other
Other
Only 1
discrepancy in
reproducibility
(8%)

14. Analyze Phase

15. Value-Add Analysis
Key Take Away: Our analysis showed that the value-add for resubmits is drastically lower
than first pass. We need to figure out what is causing them and reduce those resubmits!
Process Step
Step Label
(VA, NVA,
NVAr)
Value
Added Time
NVA & NVA-
Required
Work Time
NVA - Wait
Time
Submitter creates ticket NVA 2
Manager opens ticket and reviews for completeness NVA-r 15
Manager manually assigns ticket to analyst NVA 3
Ticket sits in queue NVA 400
Analyst opens ticket assigned NVA 1
Review documents (get feel for package and make sure
everything is there)
NVA 15
Reach out to submitter to let them know it has started VA 5
work on spreads and calculations VA 275
contact banker to give them progress update VA 5
complete spreads and calculations VA 275
create summary and risk score VA 20
attach to system ticket NVA 2
Manager review of package NVA-r 15
contact banker to let them know it is complete VA 5
Time % of total
602 58.00% 2076
36 3.47%
400 38.54%
1038 100.00%Total Cycle Time
Value-Added Flow Analysis - Underwriting First Pass
Total Value-Added Work Time
Total Non-Value-Added or NVA-r Work Time
NVA- Wait Time
Process Step
Step Label
(VA, NVA,
NVAr)
Value
Added Time
NVA & NVA-
Required
Work Time
NVA - Wait
Time
Submitter resends ticket back NVA 2
Manager opens ticket and reviews for completeness NVA-r 15
Manager manually assigns ticket to original analyst NVA 3
Ticket sits in queue NVA 540
Analyst opens ticket assigned NVA 1
Review documents (get feel for package and make sure
everything is there)
NVA 15
Reach out to submitter to let them know it has started VA 5
work on spreads and calculations VA 120
contact banker to give them progress update VA 5
complete spreads and calculations VA 120
create summary and risk score VA 20
attach to system ticket NVA 2
Manager review of package NVA-r 15
contact banker to let them know it is complete VA 5
Time % of total
292 33.64% 1736
36 4.15%
540 62.21%
868 100.00%Total Cycle Time
Value-Added Flow Analysis - Resubmit
Total Value-Added Work Time
Total Non-Value-Added or NVA-r Work Time
NVA- Wait Time
Value add
percent is 24%
less in a
resubmit!!

16. Y
Fishbone Diagram
missing, waived, or
partially completed
documentation ok'ed
Skip steps or avoid
communication to drive
productivity numbers
Analysts partically
incented for resubmits
Loans are manually queued
and assigned to after first pass
audit
Varying quality
and accuracy
All loans are unique and
requirements vary depending
unfavorable results often
require a resubmit loop
All loans are unique and process
can vary depending on user
Varying degree of submitter
knowledge and expertise
Lack of resubmit
reporting
Able to accidently
resubmit
Allowed to submit
without vetting
Systems Process Forms
Analyst or Manager
Error
Not communicating
enough
No recourse for high
resubmits
People Policies
Resubmits
Fishbone Diagram
Key Take Away: Our fishbone had a mix of solutions in disguise, symptoms, and ideas
for root cause. Affinity analysis lead us to narrow down our root causes to evaluate.
Represents 1 vote: Each participant
had up to 3 votes

17. Fishbone Analysis and 5 Whys
Key Take Away: We took our possible X’s and had to categorize and make them measurable. Our 5 Whys
analysis helped us reduce the number to review by identifying several x’s as symptoms of each other.
Possible X's (From Fishbone) Measurable X Evaluation Plan
Allowed to submit without vetting
What % of Resubmits are because of a
result banker didn’t like
Symptom (From 5 Why's)
Varying degree of submitter knowledge
and expertise
Are resubmits higher by user Hypothesis test
All loans are unique and process can
vary depending on user
Is there a difference between users and
resubmits
Hypothesis test
Unfavorable results often require a
resubmit loop
What % of Resubmits are because of a
result banker didn’t like
Stratified Pareto - vetting or not vetting
reasons
Not communicating enough Solution in Disguise Added to parking lot
No recourse for high resubmits Solution in Disguise Added to parking lot
missing, waived, or partially completed
documentation ok'ed
What % of Resubmits are because of a
result banker didn’t like
Symptom (From 5 Why's)
X's
Why? Because Why? Because Why? Because Why? Because Why? Because
Why are
resubmits so
high?
Because
bankers don’t
like the results
and send in
another request
Why don’t they
like the results?
Because the deal wasn’t
properly vetted or they
didn’t understand it and
didn’t spend enough
time or the correct
documentation
Why don’t they
understand
and/or not send
the correct info/
documentation
Because they
either didn’t do
their review or
are unfamiliar
with it
Why didn’t they
review or are
unfamiliar with
it?
Because it may have
belonged to another
banker before and/or
they just made
assumptions and
passed along
Why do they just
make
assumptions
and pass along?
Because it is
faster and easier
for them and
there is no
accountability
5 Whys
Why 1 Why 2 Why 3 Why 4 Why 5

18. Process Flow Analysis
Key Take Away: Our current state process flow analysis highlighted two
decision points at the very end that caused the whole process to repeat, how
many are getting here and can we stop it earlier?
Two decision points
at the end of the
process go all the way
back to the start; can
we identify this
earlier?!

19. Category Stratification
Key Take Away: To test the theory that many resubmits were because of unfavorable results
at the end, that could or should have been identified earlier, we recategorized and stratified
the data into two categories; and we saw there was a very high percentage of resubmits that
were because of unfavorable results that could of or should of been caught earlier.

20. Hypothesis Testing Plan
Key Take Away: The group was sure both of these were statistically significant root
causes! Glad we showed with testing before fixing the wrong problem! But what now?!
Possible X
(1 or 2 words)
Null Hypothesis
Alternative Hypothesis
(Your theory)
Hypothesis Test
(See Hypothesis Tree
on Next Tab)
P-Value or
R-Squared
Results
(Accept or
Reject
Null)
Analyst
There is no difference between analyst
resubmission rate
Submission rates are different by
analyst
Anova one way p = .233 Accept Null
Submitter
There is no difference between
submitters
There is a difference between
submitters
Chi Square p = .148 Accept Null
Hypothesis Testing Plan
If its not the Analyst
or the Banker then
we need to look
deeper at the
process!

21. Communication
Key Take Away: Since it wasn’t the bankers or the analysts, we decided to revisit the
fishbone and look at communication. We surveyed the analysts and we saw there
looked to be a correlation between communication and resubmits. Time to test!
HowManytimesdoyoureachouttobankerduring
1stunderwriting
Howmantimesdoyoucontactbankerviaphone
Howoftenareyousuccessfulreachingthem
Howlongareyouonthephonewiththebanker
Howmantimesdoyoucontactbankerviaemail
Howlongareyouworkignonyouremail
D 3 1 0.5 6 2 5
J 3 2 0.5 2 2 3
E 3 1 0.4 5 2 5
A 3 2 0.5 5 1 3
H 3 3 0.4 5 1 5
B 3 3 0.45 7 0 5
C 3 3 0.6 10 2 2

22. Regression Analysis
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.682727741
R Square 0.466117169
Adjusted R Square 0.359340603
Standard Error 1.944978458
Observations 7
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 15.08313132 4.543972464 3.319371197 0.021022778 3.402478239 26.76378439 3.402478239 26.76378439
Key Take Away: Although we only had 7 data points from the survey, we were
able to clearly see there was a statistically significant correlation between
Communication Time and Resubmit Rate!
Possible X
(1 or 2 words)
Null Hypothesis
Alternative Hypothesis
(Your theory)
Hypothesis Test
(See Hypothesis Tree
on Next Tab)
P-Value or
R-Squared
Results
(Accept or
Reject
Null)
Communication
Time
There is no direct correlation between
communication time and resubmit rate
There is a correlation between
communication time and resubmit rate
Regression p = .021 Reject Null
Hypothesis Testing Plan

23. Improve Phase

24. Selected Solutions
Key Take Away: The team brainstormed ideas and then scored them. We
decided to pilot the only one that landed in the upper left corner.
Easy Hard
Low Impact
Impact Effort Matrix
High Impact
Solution
Estimated Effort/ Risk/
Time to Implement
Estimated Benefit/
Impact
Do nothing 0 0
Internally Vet Docs to guess
result banker wants and will get
and send back 2 1
Require more talking time and
communication along the way 2 1.5
Change process to require call
upfront before submitting to
discuss loan and give analyst
opinion and score guess 2.5 3.5
Create automated system for
banker to plug in minimal info
and get estimated score 5 3.5
Impact Effort Matrix
Time to Pilot a
required call
at the
beginning of
the process!

25. Pre Call Pilot
Key Take Away: The Pilot Checklist really helped all stakeholders get on the
same page and organized.
Yes/No Detail
Yes 2 weeks
Yes This will be limited to a single market, small to medium sized
Yes 3 analyst will be assigned to answer a new queue
No This will be normal intake and not tied to any specific loan types
Yes Market specific call and communications
Yes
3 analysts have been brief and trained on how to cover queue. Other analysts have been made
aware to ensure loans that should be going through pilot don’t by pass to them
Yes On call with market leader to show benefits
No Process is same after call
No Process is same after call
Yes Resubmit rate of less than 40%
Yes 3 analysts will track loans and 2 weeks after pilot will review to see if any were resubmitted
Yes
Resubmits will be tracked and then categorized (MSA) and then stratified to determine if
preventable due to results
Yes The 3 Analysts will track how long they are on the phone to review each loan.
Yes 3 check points each of first 3 days to ensure process is working then Friday, Wednesday, Monday
Yes Stratified Pareto Chart comparison from analyze phase as well as overall % comparison
Yes 3 check points each of first 3 days to ensure process is working then Friday, Wednesday, Monday
Have check sheets or other methods of data collection been created?
Has plan for final measurement and noise been established?
Will the pilot be restricted to a particular customer segment?
Resubmit Pre Call Pilot Checklist
Pilot Strategy
Has the time frame for the pilot been established?
Has a future state map been created and shared?
Have any new forms been created and shared?
Have new Standard Operating Procedures been documented and
shared?
Measurement Plan
Have the measures of success been agreed upon?
Will the pilot involve specific analysts?
Will the pilot involve a specific unit or application?
Training Preparation
Have process participants been briefed and prepared?
Has a walk-through or talk-through of the new process been planned?
Adjustment Plan
Are feedback mechanisms in place?
Is there a plan for pilot data display?
Are plans in place to accommodate adjustment to the solutions?
Has plan for measuring for productivity been established?

26. Implementation Plan
Key Take Away: This was important to make sure all dates, roles, and
expectations were aligned with all responsible parties.
Action Item
(List steps required to implement solutions)
Responsible
(List person(s) responsible
for action steps)
Due Date
(Indicate when action items
must be completed)
Work with pilot Market Leaders to ensure buy-in and evaluate potential
objections and exceptions
Manager, Market Leader 2-Nov
Work with telecom to build out simple queue for pilot Telecom 11/2
Work with manager and market leader to determine staffing model and
expectations for phone queue for pilot
Manager, Market Leader 11/2
Train the 3 Analysts how to handle queue and log each call, and others
analysts on what to look for
Manager, Analysts 11/2
Run pre phone call pilot Bankers, Analysts 11/16
Make adjustments to pilot as needed Manager, Analysts 11/16
Compile pilot results and make adjustments as needed Self 11/30
Work with all Market Leaders to ensure buy-in and evaluate potential
objections and exceptions
Manager, Market
Leaders
12/3
Take new process to change control for approval
Manager, Change
Control Team
12/3
Work with telecom to build out official queue for process Telecom 12/28
Work with manager to determine staffing model and expectations for phone
queue
Manager 12/21
Develop timeline for rollout
Manager, Market
Leaders
12/3
Develop communication plan for frontline
Manager, Market
Leaders
12/10
Train Analysts how to handle queue Manager 12/21
Update procedures Manager 12/21
Roll out new process
Manager, Market
Leaders, Frontline,
1/7
New Required Pre Call Phone Discussion - Implementation Plan

27. Risk Management
Key Take Away: Getting a hold of bankers was an issue lifted up through the surveys, so we
wanted to make sure we had enough people available when they called; and we wanted to
make sure the time to complete this process didn’t offset potential savings from avoiding
resubmits.
Process
Step/Input
Potential
Failure Mode
Potential
Failure Effects
Potential
Causes
Current
Controls
Action
Recommended
Resp. Actions Taken
Adding a required
phone call before
loan package is
assigned
Could add more
time to process
because of
required
communication
Underwriting
decision is
delayed and
ultimately the loan
is delayed
8
Not enough
analysts to handle
the phone calls
and/or calls taking
too long
8
None
10 640
Call management
system for both
staffing predictions
and real time
dashboards
Supervisor and
Manager
Created staffing
models with back
ups and real time
marquee
8 6 2 96
DETECTION(1-10)
RPN
What is the
process step,
change or feature
under investigation?
In what ways
could the step,
change or
feature go
wrong?
What is the
impact on the
customer if this
failure is not
prevented or
corrected?
What causes the
step, change or
feature to go
wrong? (how
could it occur?)
What controls
exist that either
prevent or detect
the failure?
What are the
recommended
actions for reducing
the occurrence of
the cause or
improving
detection?
Who is
responsible for
making sure the
actions are
completed?
What actions were
completed (and
when) with respect
to the RPN?
SEVERITY(1-10)
OCCURRENCE(1-10)
DETECTION(1-10)
RPN
SEVERITY(1-10)
OCCURRENCE(1-10)
FMEA Form

28. To Be Map Segment
Key Take Away: We now have a catch at the beginning at the process to avoid
completing all steps, before identifying that it doesn’t meet expectations.

29. Proof of Improvement
Key Take Away: There was a clear drop in resubmit rate from September compared to the pilot*
and it’s below our target goal of 40%!! [Pilot dates are weeks not months and were bumped 10%
higher to account for resubmits that may come in later from pilot period]
Target Rate

30. Control Phase

31. Monitoring & Response Plan
Key Take Away: The Monitoring Plan helped a lot by increasing the frequency
of resubmit data and reviews to weekly, compared to monthly, and it put a
target and response plan in place when there wasn’t one before.
Name of the Measure
Input,
Process
or
Output?
What is the
Target?
Method of Data
Capture
Checking
Frequency
Person
Responsible
Upper/Lower
Trigger Point
Who Will
Respond?
Reaction Plan
Resubmit Rate O Less than 40% Tracker Sheets Weekly
Manager,
Analysts
more than 45% Manager
Review loans and make sure people are
not by passing new process somehow.
Review call data to ensure they are not
being rushed, and/or are bankers are
avoiding due diligence, assuming this call
will catch it. Check for an increase in a
type of loan or category getting
resubmitted and verify that our analysts
understand it and are trained on it.
Monitoring Plan Response Plan

32. X & MR Control Chart of Project Y
Key Take Away: The team has never used a control chart to monitor their process before, and
the frequency is moving to weekly so that they are able to act quicker and have more data
points [The above charts are simulated because timeline is short of the goal of 20 data points].

33. Do's and Don'ts for Future Efforts Positive Impacts on External Customer
Yes / No
Yes / No
Yes / No
I would never have thought this was the root cause issue and I'm excited
for our new control chart! Thank you so much for all your help! - Robert
We have elimated 13 hours of lead time and 4 hours of cycle time for
20% of our loans, and those savings are being applied to produce more
loan packages faster.
Make sure to dig into problems (5 why's)
Has been informed of process changes:
Agrees to continued monitoring of new process:
Has received new process documentation:
Final Calculations of Savings or Gains
Resubmits are down more than 20%
Overtime has dropped by 40 hours per month. Banker and Analyst satisfaction has increased
Hard Savings/Profit Increase Soft Savings - Cost or Time
Sign-off From Project SponsorProcess Owner Hand-off
Lessons Learned Customer Impact
Project Closure
Remember to involve everyone early and clearly establish roles and
commitments
Focus on getting good data, and if it isnt good or doesn't exist, find a
way to measure it.
Utilize hypothesis testing to make sure a root cause is a root cause
Bankers have thanked us directly on the calls for explaining and walking
them through the process and potential issues!
Project Closure
Key Take Away: Resubmits are down and the team can now produce more
higher value-add first run loan packages faster!

34. Appendix

35. Key Words
• Analyst – The underwriter who is reviewing the loan and documents and
producing a risk rating and scorecard.
• Approver – The person who determines, largely based on the risk rating
and scorecard, whether the loan is good to move forward or not.
• Banker – The person who is trying to get the loan for the customer. They
are the go between and responsible for getting all the documents and
information from the customer.
• Resubmit – When a loan is assigned to the underwriting team in the system
and goes through the underwriting process, but then later needs to be sent
to the underwriting team again via the system.
• Underwrite – Evaluating a customers cash flows, profitability, and risk, to
assign a risk rating, spreads, and scores based on multiple financial
documents.

36. AD Normality Test For Analyst
Resubmits
Key Take Away: Needed to determine if data was normal so we could
determine what hypothesis test we needed to conduct.

37. Analysts Are Not The Reason!
Key Take Away: The team thought this was a root cause, but a P value of .23
said we could not reject the null!
Anova: Single Factor
SUMMARY
Groups Count Sum Average Variance
Row 1 9 5.238087 0.58201 0.03084
Row 2 9 4.540678 0.50452 0.150748
Row 3 9 4.000626 0.444514 0.067811
Row 4 9 6.716443 0.746271 0.045135
Row 5 9 5.387681 0.598631 0.103066
Row 6 9 4.934772 0.548308 0.017826
Row 7 9 6.223305 0.691478 0.074361
ANOVA
Source of Variation SS df MS F P-value F crit
Between Groups 0.585352 6 0.097559 1.394303 0.233094 2.265567
Within Groups 3.918292 56 0.06997
Total 4.503644 62
January February March April May June July August September AVG
A 47% 52% 44% 60% 63% 93% 79% 44% 42% 58%
B 14% 33% 28% 80% 53% 26% 50% 140% 29% 50%
C 13% 25% 24% 50% 33% 78% 64% 29% 86% 44%
D 84% 61% 90% 100% 81% 76% 46% 40% 94% 75%
E 125% 55% 67% 38% 73% 25% 53% 82% 21% 60%
H 48% 58% 80% 58% 43% 65% 46% 59% 35% 55%
J 40% 65% 53% 71% 29% 120% 88% 83% 75% 69%

38. Bankers Are Not The Reason!
Key Take Away: The Analysts were sure the bankers were the root cause, but
our Chi SQ test said otherwise, with a P value of .15!
Resubmits Expected Value
Hillyer 1 0.557143
White 0
Scali 2
Smith 0
Benson 2
Rook 0
Malcom 0
Barrett 2
Kincaid 0
Reed 1
Holmgreen 0 Chi P value 0.148414
Capri 0
Browy 0
Collins 0
Tuck 0
Martin 0
Tebeau 0
Neeley 1

39. Sample Plan Resubmit Cycle Time
Key Take Away: Lead time was readily available in the system but the team didn’t know how long the
actual cycle time was to process for first pass and resubmits; so we decided to take a sample and get
an idea of average time to complete. We based the std deviation on analysts estimates and had a wide
margin of error because of the large variation in time and because every loan is different.
Resubmit Sample and Mean Cycle Time
Sample Size Calculator: https://mathcracker.com/minimum-sample-size-for-mean.php?#results
A 10/15/2018 9:18 7217076 0.1
A 10/15/2018 10:04 6995924 6.1
B 10/15/2018 10:31 7177368 0.5
F 10/15/2018 11:02 7144720 1.5
C 10/15/2018 11:57 6728697 3.2
D 10/15/2018 12:43 6770998 4.2
B 10/15/2018 13:09 7144720 0.4
B 10/15/2018 13:32 6766642 17.8
E 10/15/2018 15:03 7177368 1.5
C 10/15/2018 15:57 7150888 7.6
F 10/15/2018 16:01 7226800 7.5
G 10/15/2018 16:02 7223433 14.6
H 10/15/2018 16:07 7226975 0.2
A 10/15/2018 16:39 7228332 8.5
H 10/15/2018 16:46 7101193 8.8
D 10/15/2018 17:09 7229353 6.3
E 10/15/2018 17:40 7229337 5.9
E 10/16/2018 9:29 7172362 1.1
A 10/16/2018 10:18 7232700 3.5
C 10/16/2018 10:21 7182773 5.0
E 10/16/2018 11:03 7234073 0.6
F 10/16/2018 11:11 7233773 0.9
H 10/16/2018 11:22 7234456 0.3
E 10/16/2018 11:47 7156302 2.4
D 10/16/2018 12:17 6444524 2.9
H 10/16/2018 12:25 7236478 13.0
A 10/16/2018 14:17 7240670 1.2
E 10/16/2018 14:32 7021224 10.6
E 10/17/2018 9:51 6044369 4.1
B 10/17/2018 10:25 7144720 6.7
C 10/17/2018 11:20 7253610 2.8
F 10/17/2018 11:21 7248034 0.4
D 10/17/2018 12:50 7156302 0.6
H 10/17/2018 13:35 5424016 10.8
G 10/17/2018 14:04 7221481 1.4
C 10/17/2018 14:16 7260831 0.5
G 10/17/2018 16:07 7265418 0.2
G 10/17/2018 16:54 7267450 6.6
D 10/17/2018 19:27 7269055 4.5
A 10/18/2018 9:01 7269642 0.1
4.4

40. Sample Plan First Run Cycle Time
Key Take Away: Lead time was readily available in the system but the team didn’t know how long the
actual cycle time was to process for first pass and resubmits; so we decided to take a sample and get
an idea of average time to complete. We based the std deviation on analysts estimates and had a wide
margin of error because of the large variation in time and because every loan is different.
Analyst Start Time Ticket Number Time to finish Hours
C 11/1/2018 11:33 7351066 3.7
B 11/1/2018 15:49 7091748 7.9
A 11/1/2018 17:08 7039541 8.8
E 11/1/2018 17:15 7156121 8.3
C 11/1/2018 17:20 7410856 6.2
F 11/1/2018 17:57 7371333 10.7
B 11/2/2018 10:18 7370816 19.1
G 11/2/2018 10:20 7373167 10.2
D 11/2/2018 10:29 7298939 13.5
A 11/2/2018 11:08 7307356 4.5
C 11/2/2018 15:32 7283492 11.7
E 11/2/2018 16:48 7411012 11.8
A 11/2/2018 17:50 7282205 10.9
G 11/5/2018 10:15 5926482 9.3
D 11/5/2018 10:18 7309912 8.2
AVG 9.65
First Run Sample and Mean Cycle Time
Sample Size Calculator: https://mathcracker.com/minimum-sample-size-for-mean.php?#results

41. Stakeholder Analysis
Key Take Away: This was great to build and consider especially at the beginning of the process. Helped
with communication and support.
Stakeholder/
Stakeholder
Group
Impact Level Level of Support
Reason for
Resistance or Support
Action(s) to Address
This Stakeholder Group
Contact
Manager and
Supervisor
Decision Authority Supporter
Process is not scalable and
SLA's are difficult to handle
due to do amount of rework
Keep engaged to keep
supporter status and
momentum
Robert / Alex
Analysts Impacts Outcome Supporter
Process is not scalable and
SLA's are difficult to handle
due to do amount of rework
Show them the benefits,
keep engaged and involved
to maintain supporter status
Charles
Banker Impacts Outcome Resister
Looks at change as more
work for them
Show them whats in it for
them by proving that less
rework means less work for
them and better experience
for the customer
Many
Approver Decision Authority Neutral
Wants to support bankers
and do whats best for the
customer
Show them whats in it for
them by proving that less
rework means less work for
the bankers and better
experience for the customer
Many
Stakeholder Analysis (Advanced)

42. Resubmit and Category Data From
Tracking Sheets
Key Take Away: This data was great but there was a lot of noise in it. The previous Manager did not track
to this detail or measure the same way. We limited our info to 2018 for that reason and the last 3 months
for resubmit types because of process changes and tracking changes that were recently implemented.
Summary Info
Detailed Log

43. Lead Time Data From System
Key Take Away: We were able to get what we needed from the tracking sheets and the system data, but
there is definitely room to improve on what reporting is available in the system. Going through this project
has allowed us to provide additional enhancements and suggestions for the system and its reporting.

44. Note For Graders
Some control data has been simulated based off
pilot performance. Actual implementation wont be
live until 2Q 2019 and will be grouped together with
other changes.