Alta Bering Retail Banking Solutions

Driving management technology

Retail Banking Solutions

Presentation Overview
retail banking
2 | 22

1. 2. 3. 4.
EPO EPO EPO Impact Solutions
The framework Methodology Corporate Returns Volume Targeting
The platform Growth Factors: Decision Analytics Workforce Allocation
correct target setting Incentive Compensation

5. 6.
How does EPO work? EPO
State objectives with Prescriptive analytics
data at work
Manage against
strategic goals

Alta Bering Management Technology Consultants Ltd. All rights reserved.

About Alta Bering
3 | 22

Alta Bering is a management technology and consulting house with
operations in North America and Europe since 1994. Levend Beriker
and Dr. Mahmut Karayel are Alta Bering’s founders and senior
partners.
Along with teams of developers, data scientists and consultants in
the US, Canada and Europe, Alta Bering has implemented cutting
edge management technology for benchmarking, targeting,
resource allocation and strategic planning.
Alta Bering’s clients are global retail banks, retail distribution
networks, mobile telecom, insurance and world leading FMCG
brands.
We serve our clients with a “rapid results” approach, using our
proprietary Enterprise Performance Optimization (EPO) platform.

Banking | Insurance | Retail | Distribution | FMCG | Telecom


1.1.EPO
the framework
4 | 22

EPO is a management framework that pushes the performance envelope with
its ability to simultaneously and transparently allocate resource based perfor-
mance targets across multiple processes and performance dimensions. The
primary goal of EPO is to enable rapid execution of strategy.
EPO is used to prescribe uniquely balanced action for hundreds or thousands
of managed units that are currently subject to the laws of averages.

EPO enhances Balanced Scorecard, Economic Profit and strategic portfolio
management methods, including the aging growth-share matrix.
With EPO, migration paths for members of any portfolio of “investments” can
be reset along multiple dimensions with any frequency: re-balancing growth,
market share, profitability, customer experience, customer segments, products
and risk for maximum return on capital.


1.2.EPO
the platform
5 | 22

EPO is also the name of our decision analytics
software platform that makes implementation of
the efficient frontier approach to targeting possible
and business complexity visibly manageable.
(http://www.altabering.com/alta-bering-epo.html)

The EPO platform has been used in retail banking to mine for performance
opportunities, exploit trade area potential, plan account manager/client sales
targets, optimize service workforce balance, distribution channels, rework credit
terms and many others.


2.1.EPO Methodology and Benefits
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Data
Infrastructur e
Setup

EPO Platform
Data Analysis
Prescriptions and • PO is a method that sets performance
E
Visualiza tion targets and allocates resources for greater
efficiency of any process or business unit
• PO works by treating performance
E
as a resource constrained production problem
and optimizes performance targets based on
peer benchmarks
• PO can help beat targeted efficiency
E
Modeling Segmenta tion by 10 - 30% in three performance cycles
• sing EPO benchmarking, management can
U
monitor true performance with any frequency

Model Input
Selection


Our Perception
2.2.
growth factors
7 | 22

be
on

nc
ti
ec

hm
set di r

ar k
Target Setting
Motivation
Effort

e

me
g
su

a
ur

oa
re
o u tc o m e s
n at

ls

nu In our experience, correct target setting is critical
rture to achieving potential output. It is often more
important than initiatives to better assess market
potential, incentivizing marginal effort and
Market, Organization deployment of physical assets.
Legal Environment


EPO Impact
3.
8 | 22

Impact on Corporate Returns
With EPO a retail bank would be able to retrieve hidden potential across
its network and distribution channels.
Typical two quarter improvement for branch banking is 10-15% on volume
and 30% on profitability.
This level of improvement is possible because EPO drives target achievement
rates toward 100% of potential throughout the organization by:
• ffectively allocating all enterprise resources for maximum return
E
• inding and fixing performance problems quickly
F
• aking performance-related compensation schemes more effective
M

Impact on Decision Analytics
EPO will save valuable analyst time as it helps:
• apidly model and analyse massive amounts of performance data
R
• nlock the hidden value in large business intelligence investments
U
• onvince corporate agents of the need for improvement through transparent,
C
peer based performance targets
• ompress the “strategy to planning” process from months to days
C


4.1.Solutions and Impact
volume at risk
9 | 22
Experienced Offerings
Gain Range
Managing to averages leaves a lot of money
on the table even before strategy meets real- Volume Targeting
8 - 11 %
life constraints. for Managers
Alta Bering’s team of Data Scientists, Busi-
ness Analysts, Consultants and two decades Workforce
of practice proven, innovative approach to 3-8% Allocation and
performance planning and resource alloca- Branch Staffing
tion, uncover years of pent up potential in
2-3 planning cycles. Maximizing
6 - 11 % to Trade Area
(www.altabering.com/alta-bering-epo.html) Overall Gain Potential
Overall gains of 10-30% are typically 10% - 30%
Branch
achieved, through a combination 3-6% Operations
of our offerings. Efficiency

Credit Risk
3-5%
Management

Quality
10 - 15 %
Management


4.2. Retail Banking Solutions
10 | 22

Workforce allocation
Offering Volume Targeting for Managers Maximizing Trade Area Potential
and Branch Staffing
Branches are often requesting
Over/under-targeting has put While market share is sliding in
additional teller support to improve
overall balance sheet volume some regions, healthy sales growth
their customer experience
and profit goals at risk is expected for others
Why and meet their targets
What are the right sales targets Should the bank reallocate What should be the new sales
in order to secure the maximum resources or review service level targets so that bank can reach
volume and profitability? parameters and/or both? its true market potential?
Optimize budget allocation and Determine optimal number Identify realistic branch sales
What gain maximum return in volume of branch staff based on branch targets through aligning branch
and profitability profile and its SLAs profile and its trade area potential
Waiting time per customer
Deposit amount per employee
Number of transactions per
Credit amount per employee
employee Market share per branch
KPIs Commissions per customer
Ticket amount per employee Spending amount per household
Customer numbers per portfolio
Customer satisfaction improve-
Number of Products per Customer
ment
Improve market share of each
Decrease cost of sales Decrease cost of service delivery
branch
Impact Increase product volume Optimize internal SLA benchmark
Increase customer share of wallet
Reallocate insufficient resources Reallocate branch staff
Increase new customer acquisition


4.3. Retail Banking Solutions
11 | 22

Offering Branch Operations Efficiency Credit Risk Management Incentive Compensation
Poor sales performance is a direct With large numbers of creditors When reward systems are aligned
result of unsatisfactory customer sliding into delinquency it is clear with strategic goals across the
service and inefficient branch and that preventive maintenance of organization, growth potential is
Why operations center processes credit terms is required. more easily achieved
Which bank processes should be What part of the bonus pool should
What are the prescriptions for tailor
eliminated, optimized and be earmarked for branch network,
made credit risk restructuring?
automated? regional and HQ employees?
Reveal delinquent credits and set
Maximize branch transaction Improve motivation, stem loss of
What tailor made credit collection pre-
efficiency and effectiveness valued managers to competitors
scriptions
Credit volume per portfolio
Delinquent credit amount per cus-
Transaction count Target achievement rates
KPIs tomer
Transaction time Account manager churn rates
Collection amount per customer
Credit limit per customer
Reduce transaction time.
Sustained record profitability
Increase total number Increase collection recoveries
Impact and growth
of transactions Decrease credit risk
Improved sales motivation
Reallocate resources


4.4.Volume Targeting
for account managers
12 | 22

Business Problem Project Objectives and Scope Results Delivered
Target setting for 50 primary Design a system to allocate Account managers meeting
banking products and 150 KPIs, the retail, commercial, and SME volume and profitability targets
across 900 branches, 2,500 customer portfolio across account doubled, (climbed from 35%
account managers is proving managers and products, such that to 72%) within three quarters.
to be a major challenge. at least 70% of managed
Only one third of the branches portfolios’ growth and profit
demonstrate target achievement targets fall within 90% to 110%
rates between 80% to 120% of percent of target within two
their targets resulting in misal- planning periods.
location of resources and missed Monitor target achievement
earnings expectations. and facilitate optimal adjustments
Over/under-targeting has put to targets every quarter.
overall balance sheet volume
and profit targets at risk.


4.5.Workforce Allocation
and branch staffing
13 | 22

Branch operations are receiving Adjust service level parameters 8% of total full time resources,
requests for additional tellers or re-allocate resources for cost 5% of all part time resources were
from branch managers. reductions while improving non- applied in different branches,
Time-to-service is too long for bank customer service experience. freeing up 17% of full time and
non-bank customers and almost Define a segmentation model 25% of part time. Wait times for
too short for high priority custom- for all branches such that service non-bank customers were reduced
ers. How should the bank allo- levels are driven by service by 40%.
cate the full time and part-time demand patterns at each branch,
employees for best customer determine the optimum number
experience? of full time and part-time tellers.


4.6.Maximizing Trade Area Potential
14 | 22

Sales targets are not aligned Design appropriate trade area High granularity sales targets
to a branch’s trade area potential; for each branch using density, by product type for distinct cus-
they are set based on a branch’s gravity and drive time modeling tomer segments, for branches,
relative performance to other techniques utilizing current year by trade area, across 4 segments,
branches. postal code level customer and 2,250 branches for 6% gain in
This has resulted in over 30% market data. volume in one quarter.
of the branches not meeting their Align customer sales growth Bank branches were able to focus
sales objective. Employees are dis- targets for each branch with their their sales and marketing efforts
satisfied that they are not making corresponding trade area market by product line to appropriately
their bonuses because of external potential. Update sales targets to address customer potential in
market factors. reflect dynamic market character- each trade area.
istics.


4.7.Branch Operations Efficiency
15 | 22

It is clear that some of the numer- Analysis of all recent branch Eight processes selected and
ous bank processes that are operations activity in response to prioritized for automation in a
handled by the bank’s operations requests from branches, an invest- fraction of the budgeted time. In
centers are inefficient and need to ment brokerage subsidiary and other cases, process step and work
be automated. Service deficiencies three contact centers. reduction was indicated in detail.
in certain processes hinder branchCollect and analyze process
sales efforts. information easily from multi-
Due to the large investments at ple systems and determine the
stake, branch operations decision top ten high priority and high
support teams have to spent more frequency processes that will be
than two months conducting automated.
in-depth analysis.


4.8.Credit Risk Management
16 | 22

With large numbers of creditors Design a model that will bench- Mortgages heading toward delin-
sliding into delinquency it is clear mark mortgage borrowers and quency in the next three months
that preventive maintenance of help recommend principal reduc- were identified and regrouped
credit terms is required. Behavior tion and other restructuring by next steps of action. Expected
based risk scores are not sufficient targets case by case for 22,000 NPV was used to decide whether
for credit restructuring needs mostly non-performing residential to foreclose, restructure or do
resulting from housing downturn. mortgages across the USA. nothing. 15% of the assets were
Formulation of credit rework marked for restructuring, most
offers, based on current balance involving principal reduction.
sheet and targeted behavior, using
EPO score as the main ingredient
in a logistic probability of default
model.


4.9.Enterprise Incentive Compensation
rewardable performance range
17 | 22

Incentive compensation is too Distribute bonus funds among Bonus distribution process is com-
18,000 HQ staff and branch
little, too late and causes discord. pleted within days not months.
The primary issue is that in a network employees. Build a risk Three times as many account
multi-factor performance-reward adjusted enterprise bonus system officers qualify for bonus as bank
system, the rewardable KPI ranges based on branch and account profits set a record.
are difficult to set correctly and manager performance.
poorly set targets encourage
gaming.
Headquarters staff reward system
is not linked to branch network
performance. Account managers
are compensated sporadically for
“campaign” performance.


5.1.How does EPO work?
1. 2. 3.
18 | 22

EPO treats performance Units are segmented Analysis of data in indi- Slack re-allocated to the
as a resource constrained using clustering vidual segments using efficient units to opti-
production problem and methods based on key EPO Analysis to deter- mize volume and profit-
optimizes performance performance variables, mine the most efficient ability.
targets based on peer which ensures we are units (on the efficient Inputs: # of Staff

benchmarks on resource, comparing “like-for-like” frontier) which are # of Customers
wage and output levels. in performance evalua- subsequently used as Cost
tion. benchmarks to gauge
the relative efficiency Outputs: Loans
(and slack or potential Deposits
performance improve-
ment) of the other
units. Total Improvement
20.36% 20.36%
21.00%

Efficient frontier 18.00%

Output
15.00%

12.00%

9.00%

6.00%

3.00%
-11.59% -10.84% -9.10%
0.00%
Cluster 1
-3.00%
Cluster 2
-6.00%
Cluster 3
-9.00%

-12.00%
# of Staff # of Cust. Cost Loan Vol Deposits
Input


5.2. Enabling Power Analysts
1. 2.
19 | 22

Classify data Segment for
optimization

3. State
4.
Benchmark
objectives against
using data objectives
fields


5.3. Enabling Enterprise Performance
5. 6.
20 | 22

Discover Analyze
potential sources of
improvement performance
lift

7.
Generate unit
8.
Explain recom-
specific recom- mendations
mendations


EPO
6.
prescriptive analytics at work
21 | 22

visualization
Performance Warehouse optimizer
6.
1. 2. 3.

5. olap cube

EPO approach delivers
cross functional analytics
for long-range strategies, 4.
short-range plans, and
annual tactical initia-
tives. Internal data sources EPO results are inte-
Data sources can include are typically refreshed grated into the enter-
PL, Operational Data, monthly and weekly, prise BI platform.
syndicated data and external data sources as
more. they become available.


C
ontact Us
22 | 22

Levend Beriker, Managing Partner
levendberiker@altabering.com
Mahmut Karayel, Partner – Chief Scientist
mahmutkarayel@altabering.com
Michelle Fernandes, Director Business Development
michellefernandes@altabering.com
Onur Bilgili, Senior Consultant
onurbilgili@altabering.com

Vancouver | Berkeley | Toronto | İstanbul
www.altabering.com

Thank You.

Alta Bering Retail Banking Solutions

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