This document presents a webinar outlining risk management concepts and techniques offered by Sageworks, focusing on the importance of distinguishing between information and actionable insights in data analysis. It discusses problems with current GAAP practices, introduces the concept of loss emergence periods, and explores various analytical techniques such as regression analysis and confidence intervals for better financial decision-making. The presenter, Brandon Russell, emphasizes the need for financial institutions to transition to data-driven approaches in order to navigate economic uncertainties.

1. Garver Moore
Risk Management Consultant
Sageworks Advisory Services
Forward-Looking ALLL:
Computing Qualitative Adjustments
August 24, 2016
P R E S E N T E D B Y
Brandon Russell
ALLL Specialist
Sageworks

2. About the Webinar.
2
• Ask questions throughout the session using the
GoToWebinar control panel
• We will answer as many questions as we can at
the end of the presentation

3. About Sageworks.
• Risk management thought leader for
institutions and examiners
• Regularly featured in national and trade
media
• Origination, Portfolio Administration and
Portfolio Risk Management Solutions
• More than 1,000 financial institution
clients
• Founded in 1998
3

4. Disclaimer.
This presentation may include statements that constitute “forward-looking statements” relative to publicly available
industry data. Forward-looking statements often contain words such as “believe,” “expect,” “plans,” “project,” “target,”
“anticipate,” “will,” “should,” “see,” “guidance,” “confident” and similar terms. There can be no assurance that any of the future
events discussed will occur as anticipated, if at all, or that actual results on the industry will be as expected. Sageworks is not
responsible for the accuracy or validity of this publicly available industry data, or the outcome of the use of this data relative
to business or investment decisions made by the recipients of this data. Sageworks disclaims all representations and
warranties, express or implied. Risks and uncertainties include risks related to the effect of economic conditions and
financial market conditions; fluctuation in commodity prices, interest rates and foreign currency exchange rates. No
Sageworks employee is authorized to make recommendations or give advice as to any course of action that should be made
as an outcome of this data. The forward-looking statements and data speak only as of the date of this presentation and we
undertake no obligation to update or revise this information as of a later date.
4

5. About Today’s Presenter.
5
Garver Moore
Risk Management Consultant
Sageworks Advisory Services
Brandon Russell
ALLL Specialist
Sageworks

6. Agenda.
• Information versus insight
• Problems in current GAAP
• Concept: Loss Emergence Period
• Techniques: Regression Analysis
• Techniques: Analysis of the Variance
• Concept: Confidence Intervals
• Objectivizing subjectivity
• Case study
• Product enablement

7. Poll Questions.

8. Transitioning to Data-Driven World.
• Global headwind (tailwind?) affecting all industries
• Each industry is creating its own interpretation of best practices and uses for information
• Large institutions are already taking advantage
• Alt-lending and emerging players are, too – niche players (for now)
• “Big data” isn’t meaningful information
• Data = Information: not just bits on a server
• Intelligence is *actionable* insight
Information Analysis Insights

9. Real World Example: Information vs. Insights.
9
35.786234 -78.662548 35.795732 -78.695490 20 2.1
35.785834 -78.662963 35.779972 -78.667196 30 0.6
35.784545 -78.699287 35.772312 -78.719604 65 2.1
35.779522 -78.668100 35.784545 -78.699287 35 1.7
35.795732 -78.695490 35.772312 -78.719604 60 2.4
35.772477 -78.722420 35.763571 -78.726986 35 0.7
35.763574 -78.727006 35.762506 -78.730763 20 0.3
Insight: Take a left on Pullen Road to reach your destination 2.65 minutes faster

10. Problems in Current GAAP.
• Convention dominating reason in low-loss period
• Benchmark reserves unsupportable by historical experience
• Reaching further and further back to pick up losses
• Net recoveries for shorter periods
• Directional Consistency traps
• No oracles
10

11. 11
Poll.

12. Concept: Loss Emergence Period.
12
Loss Rate
(%)
Balance Reserve
What most institutions think
they’re doing
What most institutions are
actually doing
Loss Rate
(%)
Balance Reserve
1

13. Concept: Loss Emergence Period.
13
1 yr Loss Emergence Factor:
Past Present Future
DO NOT
ENTER
Adverse
Event
Detection
Loss
Realized
Pre-Emergence period Loss Emergence Period

14. Concept: Loss Emergence Period.
14
Past Present Future
Adverse
Event
Detection
Loss
Estimated
Still “Incurred”

15. Advantages / Drawbacks.
Advantages:
Faithful estimate of incurred loss within the bounds of GAAP
Useful number to understand and calculate
Useful financial bridge to lifetime loss calculation
Don’t need to continuously compute
Disadvantages:
May be greater than one, may be less than one
Difficult to un-ring the bell
Significant measurement risk in low-loss environments
15

16. 16
Poll: Q Factor Reliance.

17. Peer Study I.

18. Peer Study II.

19. Problem with 3-year loss rate.
19

20. Techniques: Regression Analysis.
• “How does a change in unemployment impact my loss experience?”
• “What was the impact to my losses when I started writing C&I to a new segment?”
• “What is the lead time from an indicator change to a portfolio result?”
• “What was the impact of our new management team?”
• “How confident am I in my loss experience number?”
20
Information Analysis Insights

21. 21
“All Else Being Equal”.

22. Techniques: Analysis of the Variance (ANOVA).
22
• Quantify the impact of different “Eras”
• Quantify the impact of different
segmentations
• Test for significance

23. Thought Experiment: Rocket Bank.
• Rocket Bank has a single analysis and business segment: C&I
loans with NAICS code X212221
» Mining asteroids for gold
» Experimental technologies: about 10% of rockets will fail to
orbit (default)
» Secured by existing gold stocks and exotic insurance
products – about 15% of a loan is exposed to default risk
» Extraordinarily well capitalized; inexhaustible supply of
loans
• You enter this space: think of your portfolio loans as a “sample”
» What if you win 10 loans of their business? 50? 500?
• Knowing a priori the “platonic” default rate and LGD for these
kinds of loans, let us examine how your portfolio size changes
your certainty in calculating your own experience in X212221
lending

24. Concept: Confidence Intervals.
24
Documenting reliability in measurement
-4.00%
-2.00%
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
1 10 100 1000 10000
The reliability of a measurement (e.g., Loss Rates
or PD) scales with how that measurement is
conducted.

25. Confidence Intervals 101.
• There’s a huge difference between reserving $15,000,000 +/- $1,000,000 on a $1B portfolio and
$15,000,000 +/- $5,000,000 on the same portfolio
• 80, 90, 95% confidence intervals – an illustrative concept
• Key driver: sample size – number of credits, number of observations. Management should know,
understand, and use this information! (Arguably, shareholders, too)
• Consider co-performance of credits in a segment
• Uncertainty shows up in number of PLLL transactions, or “surprise” PLLL transactions,
reactivity

26. Tools.
• Excel Data AnalysisPak (Older versions)
• First-class feature in Excel ‘16
• www.r-project.org
• Anaconda (continuum.io)
26

27. Minimize Subjective Vulnerabilities.
A lesson from security risk management
concepts:
• Attack surface concept as applied to banking
risk management processes:
» Understand how much of your calculation
is vulnerable to criticism – Map your
attack surface to identify high-risk areas
of your examined practices
» Use information and documentation to
cover these subjective areas of your
calculations
» Defending your attack surface decreases
your compliance and model risk
Attack Surface

28. Case Study: Quantitative Analysis for
Qualitative Drivers.
• $500MM – $1 B in loans
• Consistent, conservative approach
• Active, growing CRE segment
• Two main regions of operation
• Consistent governance

29. Step 1: Apply Intuition.
29
• What are my correlates? What do I suspect might drive my loss experience?
• Certainly, regional macroeconomic indicators
• Internal indicators
• Indicators for boutique segments or regional exposure (snowfall for mountain
communities, spot prices for ag, etc.)

30. Step 2: Get the lay of the land (Correlation
Analysis).
30
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-0.50041 -0.50018 -0.48862 -0.48323 -0.602 -0.62397 -0.64019 -0.65083 -0.8175 -0.82012 -0.82289 -0.82693 0.196788 0.162078 0.133861 0.11387 0.095039 0.062188 0.013667 -0.0174 0.958306 0.982976 1 0.982976 -0.20931 -0.59229 -0.6262 -0.13397 -0.09774 -0.33579 -0.16807 -0.25063 0.06136 -0.23105 0.157141 0.252242 -0.18482 -0.55662 -0.15854 -0.33579 0.448025 0.391576 -0.3683 -0.29287 0.323084 -0.05298 -0.1653 -0.19957 -0.33673 -0.59587
-0.4927 -0.50041 -0.50018 -0.48862 -0.57671 -0.602 -0.62397 -0.64019 -0.81483 -0.8175 -0.82012 -0.82289 0.233426 0.196788 0.162078 0.133861 0.088966 0.095039 0.062188 0.013667 0.937242 0.958306 0.982976 1 -0.2138 -0.53624 -0.58865 -0.136 -0.07366 -0.3002 -0.14885 -0.27211 0.15187 -0.22609 0.173215 0.267913 -0.19378 -0.51893 -0.22302 -0.3002 0.447299 0.394731 -0.33067 -0.24902 0.42808 0.053204 -0.17013 -0.15222 -0.29132 -0.53875
0.191453 0.300818 0.335989 0.315151 0.054411 0.118011 0.124321 0.165865 -0.13247 -0.17062 -0.16274 -0.11639 0.050079 0.083111 0.109703 0.141063 0.062901 0.076176 -0.0983 -0.04427 -0.22582 -0.24141 -0.20931 -0.2138 1 0.148015 0.21173 0.001238 -0.0706 0.262057 -0.05116 0.061025 0.000932 0.013771 0.048028 0.010658 0.016496 0.148698 -0.04998 0.262057 0.043692 -0.02292 0.457046 0.223084 -0.05389 -0.05179 0.03368 0.003524 0.237467 0.165991
0.641347 0.606995 0.56676 0.541918 0.888768 0.930042 0.947471 0.933889 -0.64684 -0.53911 -0.40041 -0.24521 0.870451 0.921756 0.952653 0.963436 0.294515 0.375984 0.414408 0.473673 -0.6749 -0.64458 -0.59229 -0.53624 0.148015 1 0.349924 0.533191 0.402775 0.661859 0.150243 0.290351 0.200951 0.189116 -0.02818 -0.02593 0.551389 0.967644 0.226631 0.661859 -0.33534 -0.16707 0.460347 0.630926 -0.17005 0.081862 0.549282 0.257266 0.657393 0.888055
0.60658 0.648213 0.670999 0.641322 0.128859 0.216893 0.310015 0.410498 -0.55507 -0.53865 -0.55764 -0.52753 0.08067 0.16985 0.260254 0.353929 -0.12553 -0.06837 -0.04406 -0.06284 -0.60922 -0.61954 -0.6262 -0.58865 0.21173 0.349924 1 -0.07785 -0.07614 0.315164 0.207355 0.217026 -0.00936 0.209564 0.067433 -0.06188 -0.01301 0.366556 0.076585 0.315164 -0.17348 -0.28638 0.569001 0.29252 -0.2843 -0.09808 -0.04081 0.178714 0.327994 0.458549
0.065434 0.019086 -0.00643 -0.02242 0.597184 0.631828 0.603842 0.555106 -0.20181 -0.122 -0.01548 0.075513 0.622788 0.632012 0.625326 0.575988 0.101266 0.176538 0.241398 0.420934 -0.13697 -0.14961 -0.13397 -0.136 0.001238 0.533191 -0.07785 1 0.288187 0.516612 0.046755 0.301256 0.166679 0.118021 -0.07908 -0.04118 0.973082 0.490659 -0.03937 0.516612 -0.07195 -0.069 0.133219 0.535237 -0.0787 -0.06915 0.991817 0.287572 0.532854 0.397329
0.200392 0.075473 0.010984 0.011987 0.422468 0.404771 0.358253 0.379563 -0.14225 -0.08501 -0.06345 -0.03557 0.377521 0.406192 0.4155 0.40826 0.112446 0.156865 0.184899 0.111119 -0.17262 -0.18052 -0.09774 -0.07366 -0.0706 0.402775 -0.07614 0.288187 1 0.703381 -0.05123 0.121203 0.049908 0.157395 -0.07055 0.025952 0.288879 0.405475 0.074587 0.703381 -0.12814 -0.06618 0.157616 0.65903 -0.06535 0.024857 0.288547 0.1118 0.657617 0.455281
0.437867 0.351816 0.311258 0.258549 0.582034 0.648407 0.650222 0.701535 -0.41795 -0.37028 -0.31438 -0.21725 0.581198 0.641813 0.680149 0.696716 0.148821 0.207463 0.171503 0.226504 -0.43024 -0.42542 -0.33579 -0.3002 0.262057 0.661859 0.315164 0.516612 0.703381 1 -0.01615 0.239901 0.093736 0.153684 -0.04974 -0.05399 0.524781 0.667166 0.023208 1 -0.19827 -0.17263 0.759586 0.959006 -0.20456 -0.04214 0.529745 0.28262 0.964729 0.726108
0.187977 0.196493 0.171565 0.235851 0.040537 0.056478 0.105062 0.159633 -0.23526 -0.19604 -0.13991 -0.14878 0.075849 0.099588 0.13084 0.16063 0.012448 -0.03673 0.162912 0.167632 -0.19031 -0.17272 -0.16807 -0.14885 -0.05116 0.150243 0.207355 0.046755 -0.05123 -0.01615 1 0.074883 0.085925 -0.0665 -0.01463 0.024096 0.061325 0.166699 -0.00305 -0.01615 -0.0412 -0.07362 -0.04247 -0.03918 -0.02458 -0.0271 0.053002 -0.07301 -0.03287 0.171064
0.321501 0.273804 0.217442 0.121635 0.384413 0.373963 0.356987 0.357562 -0.27756 -0.18169 -0.05118 0.006119 0.377194 0.398175 0.395167 0.376757 0.063109 0.032174 0.199524 0.361798 -0.22255 -0.1908 -0.25063 -0.27211 0.061025 0.290351 0.217026 0.301256 0.121203 0.239901 0.074883 1 0.09128 0.07703 0.003802 0.078545 0.51149 0.255998 0.324208 0.239901 -0.07193 -0.07708 0.089149 0.263848 -0.09256 -0.06254 0.418257 0.226953 0.277128 0.277065
0.182108 0.167911 0.251982 0.320713 0.327841 0.22551 0.102819 -0.00738 0.059737 0.161471 0.263595 0.35909 0.418163 0.32174 0.235485 0.161347 0.579972 0.655484 0.463507 0.268516 -0.14873 -0.0533 0.06136 0.15187 0.000932 0.200951 -0.00936 0.166679 0.049908 0.093736 0.085925 0.09128 1 0.294981 0.397914 0.573784 0.163699 0.054479 0.091618 0.093736 0.320912 0.362149 0.0275 0.131751 0.65057 0.243944 0.170662 0.070839 0.139586 -0.0044
0.227831 0.258348 0.268228 0.291989 0.246887 0.227636 0.163781 0.125623 -0.19368 -0.13253 -0.06475 -0.0514 0.146464 0.14596 0.168052 0.177353 0.181187 0.0176 -0.0227 0.054451 -0.2308 -0.20593 -0.23105 -0.22609 0.013771 0.189116 0.209564 0.118021 0.157395 0.153684 -0.0665 0.07703 0.294981 1 0.367182 0.264834 0.118992 0.127748 0.160971 0.153684 0.203973 0.167949 0.060111 0.141533 0.091191 -0.07576 0.122774 0.044562 0.17206 0.161998
0.02901 0.00122 0.012419 0.028783 0.026543 -0.03202 -0.08381 -0.1206 0.011653 0.044524 0.077075 0.135187 0.081488 0.032692 -0.00728 -0.03633 0.198184 0.193188 0.132935 0.077872 0.054274 0.123999 0.157141 0.173215 0.048028 -0.02818 0.067433 -0.07908 -0.07055 -0.04974 -0.01463 0.003802 0.397914 0.367182 1 0.363344 -0.07917 -0.04484 -0.09307 -0.04974 0.324161 0.929226 0.013034 0.019003 0.154993 0.051346 -0.07367 0.057465 0.017698 -0.04722
0.210586 0.117485 0.090269 0.076835 -0.016 -0.05032 -0.1113 -0.14796 0.246966 0.288272 0.379872 0.42667 0.081209 0.019241 -0.02988 -0.05618 0.195747 0.120619 0.023327 -0.05107 0.047518 0.179038 0.252242 0.267913 0.010658 -0.02593 -0.06188 -0.04118 0.025952 -0.05399 0.024096 0.078545 0.573784 0.264834 0.363344 1 -0.02382 -0.13212 0.198132 -0.05399 0.597761 0.348675 -0.09433 0.0126 0.510657 0.000322 -0.02877 0.08852 0.028813 -0.08666
0.135496 0.079869 0.044528 0.009667 0.629897 0.661858 0.634699 0.590939 -0.25248 -0.15972 -0.03479 0.060014 0.649154 0.664049 0.658593 0.611261 0.09484 0.163573 0.262572 0.46425 -0.17964 -0.18509 -0.18482 -0.19378 0.016496 0.551389 -0.01301 0.973082 0.288879 0.524781 0.061325 0.51149 0.163699 0.118992 -0.07917 -0.02382 1 0.506873 0.045723 0.524781 -0.08817 -0.09038 0.144087 0.542906 -0.10775 -0.07636 0.993825 0.300076 0.544146 0.427306
0.595674 0.55381 0.505939 0.472465 0.840016 0.896425 0.934862 0.944725 -0.72805 -0.63822 -0.51414 -0.37159 0.799199 0.871157 0.92273 0.953551 0.180108 0.277735 0.332336 0.415955 -0.60427 -0.59178 -0.55662 -0.51893 0.148698 0.967644 0.366556 0.490659 0.405475 0.667166 0.166699 0.255998 0.054479 0.127748 -0.04484 -0.13212 0.506873 1 0.224512 0.667166 -0.37846 -0.18114 0.485863 0.621288 -0.28431 0.030788 0.504321 0.201565 0.64259 0.899129
0.229409 0.188914 0.24204 0.266611 0.277074 0.245142 0.225236 0.202342 -0.24164 -0.22721 -0.14045 -0.09817 0.150397 0.158465 0.173712 0.205347 0.106938 0.12821 0.029942 -0.00452 -0.18927 -0.16604 -0.15854 -0.22302 -0.04998 0.226631 0.076585 -0.03937 0.074587 0.023208 -0.00305 0.324208 0.091618 0.160971 -0.09307 0.198132 0.045723 0.224512 1 0.023208 -0.08874 -0.13902 -0.0262 0.001964 0.040453 0.060757 0.003326 -0.03525 0.017153 0.167271
0.437867 0.351816 0.311258 0.258549 0.582034 0.648407 0.650222 0.701535 -0.41795 -0.37028 -0.31438 -0.21725 0.581198 0.641813 0.680149 0.696716 0.148821 0.207463 0.171503 0.226504 -0.43024 -0.42542 -0.33579 -0.3002 0.262057 0.661859 0.315164 0.516612 0.703381 1 -0.01615 0.239901 0.093736 0.153684 -0.04974 -0.05399 0.524781 0.667166 0.023208 1 -0.19827 -0.17263 0.759586 0.959006 -0.20456 -0.04214 0.529745 0.28262 0.964729 0.726108
-0.15503 -0.16582 -0.17629 -0.19647 -0.29465 -0.32527 -0.35181 -0.36057 0.360378 0.368037 0.378801 0.336529 -0.22015 -0.26862 -0.29398 -0.3125 -0.05032 -0.09638 -0.21314 -0.21831 0.384513 0.432162 0.448025 0.447299 0.043692 -0.33534 -0.17348 -0.07195 -0.12814 -0.19827 -0.0412 -0.07193 0.320912 0.203973 0.324161 0.597761 -0.08817 -0.37846 -0.08874 -0.19827 1 0.353917 -0.17087 -0.18524 0.328812 -0.05244 -0.0768 -0.14667 -0.17985 -0.30865
-0.19875 -0.24409 -0.24162 -0.21869 -0.04777 -0.13251 -0.20632 -0.27089 0.218117 0.23762 0.267496 0.313991 0.035971 -0.04183 -0.11416 -0.17497 0.215353 0.213061 0.150166 0.0912 0.283211 0.353007 0.391576 0.394731 -0.02292 -0.16707 -0.28638 -0.069 -0.06618 -0.17263 -0.07362 -0.07708 0.362149 0.167949 0.929226 0.348675 -0.09038 -0.18114 -0.13902 -0.17263 0.353917 1 -0.18055 -0.09497 0.23577 0.0932 -0.0763 -0.00673 -0.11183 -0.22203
0.468846 0.457093 0.460886 0.387394 0.291041 0.394653 0.446778 0.528153 -0.42911 -0.44149 -0.42599 -0.33816 0.31505 0.380484 0.434722 0.487269 0.093964 0.121199 -0.00071 0.060347 -0.45465 -0.43752 -0.3683 -0.33067 0.457046 0.460347 0.569001 0.133219 0.157616 0.759586 -0.04247 0.089149 0.0275 0.060111 0.013034 -0.09433 0.144087 0.485863 -0.0262 0.759586 -0.17087 -0.18055 1 0.723564 -0.22787 -0.05231 0.149719 0.220315 0.733588 0.567253
0.459909 0.372515 0.303647 0.224133 0.572484 0.622425 0.613645 0.658483 -0.37779 -0.31302 -0.24144 -0.12667 0.601877 0.649486 0.674865 0.677887 0.202835 0.200666 0.201131 0.257559 -0.3918 -0.37232 -0.29287 -0.24902 0.223084 0.630926 0.29252 0.535237 0.65903 0.959006 -0.03918 0.263848 0.131751 0.141533 0.019003 0.0126 0.542906 0.621288 0.001964 0.959006 -0.18524 -0.09497 0.723564 1 -0.09681 -0.04313 0.549638 0.524172 0.995774 0.714566
-0.00728 -0.00881 0.020517 0.014502 -0.03701 -0.174 -0.28986 -0.37505 0.348384 0.400076 0.456101 0.504298 0.041404 -0.06123 -0.1455 -0.21049 0.42913 0.4028 0.15521 -0.08521 0.176728 0.24783 0.323084 0.42808 -0.05389 -0.17005 -0.2843 -0.0787 -0.06535 -0.20456 -0.02458 -0.09256 0.65057 0.091191 0.154993 0.510657 -0.10775 -0.28431 0.040453 -0.20456 0.328812 0.23577 -0.22787 -0.09681 1 0.102135 -0.08831 0.226845 -0.09747 -0.24308
-0.03821 -0.04841 -0.04349 0.118294 0.2489 0.210807 0.099313 0.001812 0.055139 0.125602 0.083424 0.094029 0.254357 0.18352 0.116622 0.064695 0.227432 0.438279 0.720353 0.197958 -0.02775 -0.08794 -0.05298 0.053204 -0.05179 0.081862 -0.09808 -0.06915 0.024857 -0.04214 -0.0271 -0.06254 0.243944 -0.07576 0.051346 0.000322 -0.07636 0.030788 0.060757 -0.04214 -0.05244 0.0932 -0.05231 -0.04313 0.102135 1 -0.07526 -0.0614 -0.05131 -0.01086
0.10876 0.061104 0.030347 0.002166 0.620152 0.653365 0.624655 0.57932 -0.23153 -0.144 -0.02539 0.069875 0.643502 0.655824 0.649717 0.601095 0.106211 0.174236 0.253453 0.446881 -0.16492 -0.17322 -0.1653 -0.17013 0.03368 0.549282 -0.04081 0.991817 0.288547 0.529745 0.053002 0.418257 0.170662 0.122774 -0.07367 -0.02877 0.993825 0.504321 0.003326 0.529745 -0.0768 -0.0763 0.149719 0.549638 -0.08831 -0.07526 1 0.303503 0.549444 0.419422
0.349638 0.331331 0.224263 0.117908 0.230071 0.22788 0.226972 0.260635 -0.13661 -0.0616 0.015732 0.096839 0.295848 0.30261 0.298861 0.278993 0.173014 -0.01595 0.116087 0.171984 -0.21227 -0.17903 -0.19957 -0.15222 0.003524 0.257266 0.178714 0.287572 0.1118 0.28262 -0.07301 0.226953 0.070839 0.044562 0.057465 0.08852 0.300076 0.201565 -0.03525 0.28262 -0.14667 -0.00673 0.220315 0.524172 0.226845 -0.0614 0.303503 1 0.518237 0.339195
0.49266 0.40601 0.341099 0.266358 0.581151 0.636651 0.633716 0.685594 -0.39871 -0.3337 -0.25867 -0.1468 0.603375 0.655154 0.685089 0.692681 0.192962 0.193185 0.189419 0.247878 -0.43656 -0.41584 -0.33673 -0.29132 0.237467 0.657393 0.327994 0.532854 0.657617 0.964729 -0.03287 0.277128 0.139586 0.17206 0.017698 0.028813 0.544146 0.64259 0.017153 0.964729 -0.17985 -0.11183 0.733588 0.995774 -0.09747 -0.05131 0.549444 0.518237 1 0.737494
0.763975 0.690165 0.597636 0.499053 0.70312 0.775245 0.822844 0.880542 -0.75716 -0.68294 -0.58158 -0.45284 0.706454 0.790653 0.862987 0.915347 0.197668 0.211462 0.256277 0.297594 -0.67066 -0.64433 -0.59587 -0.53875 0.165991 0.888055 0.458549 0.397329 0.455281 0.726108 0.171064 0.277065 -0.0044 0.161998 -0.04722 -0.08666 0.427306 0.899129 0.167271 0.726108 -0.30865 -0.22203 0.567253 0.714566 -0.24308 -0.01086 0.419422 0.339195 0.737494 1

31. Step 3: Regression Analysis.
31

32. Step 4: Refinement.
32

33. Step 5: Summary & Application.
33

34. Step 5: Summary & Application.
34

35. Product Enablement.

36. Poll Questions.

37. Takeaways.
• Use of “advanced” analysis can uncover useful insight and levers in current and future GAAP
• Use of Loss Emergence Period can be supported by application data or these techniques, but may not be
right for every bank
• Consider the reliability and weaknesses of your analysis and defend judgment within those bounds
• Monitor our release notes at web.sageworks.com/enhancements for continuous updates to the application
37

38. 2016 Risk Management Summit.
38
• Topics include:
» CECL
» Current ALLL best practices
» Stress Testing
• Speakers from CliftonLarsonAllen,
Grant Thornton, Sageworks and more
• sageworks.com/summit

39. Q&A, Contact Information.
39
GARVER MOORE
Risk Management Consultant
Garver.Moore@sageworks.com
919.851.7474 ext. 2720
BRANDON RUSSELL
ALLL Specialist
Brandon.Russell@sageworks.com
919.851.7474 ext. 2537
Thought leader to help
you navigate changing
regulatory landscape
Responsive service
& support from
product experts
Insight into the best
practices & templates
used at 1,000+ financial
institutions
Eliminate data entry with
the Electronic Tax Return
Reader, core integrations &
credit bureau debt
Integrated platform for the
customer lifecycle
Exclusive benchmarks &
risk models to support
decision-making

40. Sageworks Advisory Services.
Use Sageworks as a partner and an extension of your team. Leverage industry expertise and market experience for various projects that
arise within your institution.
Services include:
• CECL Transition Assistance
• Analytics Support
• Data Auditing
• Peer Analysis
• Segmentation Analysis
• Qualitative Component Analysis
• Policy and Process Review
• Concentration Reporting
• Stress Testing Board Reports
• Management Reporting
• Staff Enablement
• Board Training
“Sageworks is unlike many of the other financial software providers out
there, who are represented by individuals terrific at navigating through
their products, but have little depth of subject matter expertise beyond that.
Sageworks offers consultants that are truly experts in not only the
intricacies of their products, but also in the associated and underlying
standards, accounting guidance and regulatory requirements. These
consultants have been and continue to be a tremendous resource every step
of the way – from initial product implementation and training to ongoing
support.”
Franklin Synergy Bank

41. Additional Resources.
• ALLL.com – Everything ALLL, including news articles, whitepapers, and peer discussions
• ALLL Forum for Bankers – LinkedIn group for ALLL news & discussion
• FASB’s CECL Prep Kit - complimentary toolkit, to help you better prepare
• Interested in talking with a specialist?
» Email us now: sales@sageworks.com or consulting@sageworks.com
41

42. Sageworks ALLL.
Sageworks ALLL gives banks and credit unions a consistent and
defensible allowance for loan and lease losses methodology,
proven to satisfy auditors, examiners and the board.
• Spend 80% less time on your ALLL each quarter
• Partner with the industry leader for CECL
• Reduce manual errors and examiner criticism
• View more solution information
42
THE MOST TRUSTED ALLL SOLUTION IN BANKING
“Previously with Excel, if we
wanted to look at a monthly
interim calculation, we would
have to run the core reports and
manually input them. With
Sageworks, the numbers are
inside the software and
available with just a few clicks of
a button – giving us significant
quarterly time-savings.“
Lugie Brown
Senior Vice President
First American National Bank