Alta Bering Retail Banking Solutions

Driving management technology

Retail Banking Solutions

Alta Bering Management Technology Consultants Ltd. All rights reserved.

2 | 22

Presentation Overview retail banking

1.

5. 6.

2. 3. 4.EPOThe frameworkThe platform

How does EPO work?State objectives with dataManage against strategic goals

EPO Prescriptive analytics at work

EPO MethodologyGrowth Factors: correct target setting

EPO ImpactCorporate ReturnsDecision Analytics

SolutionsVolume TargetingWorkforce AllocationIncentive Compensation


3 | 22

About Alta Bering

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


4 | 22

1.1. EPO the framework

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.


5 | 22

1.2. EPO the platform

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.


6 | 22

2.1. EPO Methodology and Benefits

DataInfrastructur e

Setup

Data Analysisand

Visualiza tion

Segmenta tion

Model InputSelection

Modeling

Prescriptions

EPO Platform • EPO is a method that sets performance

targets and allocates resources for greater efficiency of any process or business unit

• EPO works by treating performance as a resource constrained production problem and optimizes performance targets based on peer benchmarks

• EPO can help beat targeted efficiency by 10 - 30% in three performance cycles

• Using EPO benchmarking, management can monitor true performance with any frequency


7 | 22

2.2. Our Perception growth factors

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

Motivation & Effort

Market, Organization & Legal Environment

Target Setting

na

tu

r e go

al s

set

dir

ectio

n benchmark

measure outcomes

n u r t u r e


8 | 22

3. EPO Impact 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:• Effectively allocating all enterprise resources for maximum return • Finding and fixing performance problems quickly • Making performance-related compensation schemes more effective

Impact on Decision Analytics EPO will save valuable analyst time as it helps:• Rapidly model and analyse massive amounts of performance data • Unlock the hidden value in large business intelligence investments• Convince corporate agents of the need for improvement through transparent,

peer based performance targets• Compress the “strategy to planning” process from months to days


9 | 22

4.1. Solutions and Impact volume at risk

Managing to averages leaves a lot of money on the table even before strategy meets real-life constraints. Alta Bering’s team of Data Scientists, Busi-ness Analysts, Consultants and two decades of practice proven, innovative approach to performance planning and resource alloca-tion, uncover years of pent up potential in 2-3 planning cycles.(www.altabering.com/alta-bering-epo.html)Overall gains of 10-30% are typically achieved, through a combination of our offerings.

Overall Gain10% - 30%

Volume Targeting for Managers

Workforce Allocation and Branch Staffing

Maximizing to Trade Area

Potential

Branch Operations Efficiency

Credit Risk Management

Quality Management

8 - 11 %

3 - 8 %

6 - 11 %

3 - 6 %

3 - 5 %

10 - 15 %

Experienced Gain Range

Offerings


10 | 22

4.2. Retail Banking Solutions offering Volume Targeting for Managers Workforce allocation

and Branch Staffing Maximizing Trade Area Potential

Why

Over/under-targeting has put overall balance sheet volume and profit goals at risk

Branches are often requesting additional teller support to improve their customer experience and meet their targets

While market share is sliding in some regions, healthy sales growth is expected for others

What are the right sales targets in order to secure the maximum volume and profitability?

Should the bank reallocate resources or review service level parameters and/or both?

What should be the new sales targets so that bank can reach its true market potential?

WhatOptimize budget allocation and gain maximum return in volume and profitability

Determine optimal number of branch staff based on branch profile and its SLAs

Identify realistic branch sales targets through aligning branch profile and its trade area potential

kPis

Deposit amount per employeeCredit amount per employeeCommissions per customerCustomer numbers per portfolioNumber of Products per Customer

Waiting time per customerNumber of transactions per employeeTicket amount per employeeCustomer satisfaction improve-ment

Market share per branchSpending amount per household

impactDecrease cost of salesIncrease product volumeReallocate insufficient resources

Decrease cost of service deliveryOptimize internal SLA benchmarkReallocate branch staff

Improve market share of each branchIncrease customer share of walletIncrease new customer acquisition


11 | 22

offering Branch Operations Efficiency Credit Risk Management Incentive Compensation

Why

Poor sales performance is a direct result of unsatisfactory customer service and inefficient branch and operations center processes

With large numbers of creditors sliding into delinquency it is clear that preventive maintenance of credit terms is required.

When reward systems are aligned with strategic goals across the organization, growth potential is more easily achieved

Which bank processes should be eliminated, optimized and automated?

What are the prescriptions for tailor made credit risk restructuring?

What part of the bonus pool should be earmarked for branch network, regional and HQ employees?

WhatMaximize branch transaction efficiency and effectiveness

Reveal delinquent credits and set tailor made credit collection pre-scriptions

Improve motivation, stem loss of valued managers to competitors

kPisTransaction countTransaction time

Credit volume per portfolioDelinquent credit amount per cus-tomerCollection amount per customerCredit limit per customer

Target achievement ratesAccount manager churn rates

impact

Reduce transaction time.Increase total number of transactionsReallocate resources

Increase collection recoveriesDecrease credit risk

Sustained record profitability and growthImproved sales motivation

4.3. Retail Banking Solutions


12 | 22

4.4. Volume Targeting for account managers

Business ProblemTarget setting for 50 primary banking products and 150 KPIs, across 900 branches, 2,500 account managers is proving to be a major challenge.Only one third of the branches demonstrate target achievement rates between 80% to 120% of their targets resulting in misal-location of resources and missed earnings expectations.Over/under-targeting has put overall balance sheet volume and profit targets at risk.

Project Objectives and Scope Design a system to allocate the retail, commercial, and SME customer portfolio across account managers and products, such that at least 70% of managed portfolios’ growth and profit targets fall within 90% to 110% percent of target within two planning periods. Monitor target achievement and facilitate optimal adjustments to targets every quarter.

Results DeliveredAccount managers meeting volume and profitability targets doubled, (climbed from 35% to 72%) within three quarters.


13 | 22

4.5. Workforce Allocation and branch staffing

Business ProblemBranch operations are receiving requests for additional tellers from branch managers.Time-to-service is too long for non-bank customers and almost too short for high priority custom-ers. How should the bank allo-cate the full time and part-time employees for best customer experience?

Project Objectives and Scope Adjust service level parameters or re-allocate resources for cost reductions while improving non-bank customer service experience. Define a segmentation model for all branches such that service levels are driven by service demand patterns at each branch, determine the optimum number of full time and part-time tellers.

Results Delivered8% of total full time resources, 5% of all part time resources were applied in different branches, freeing up 17% of full time and 25% of part time. Wait times for non-bank customers were reduced by 40%.


14 | 22

4.6. Maximizing Trade Area Potential Business ProblemSales targets are not aligned to a branch’s trade area potential; they are set based on a branch’s relative performance to other branches. This has resulted in over 30% of the branches not meeting their sales objective. Employees are dis-satisfied that they are not making their bonuses because of external market factors.

Project Objectives and Scope Design appropriate trade area for each branch using density, gravity and drive time modeling techniques utilizing current year postal code level customer and market data. Align customer sales growth targets for each branch with their corresponding trade area market potential. Update sales targets to reflect dynamic market character-istics.

Results DeliveredHigh granularity sales targets by product type for distinct cus-tomer segments, for branches, by trade area, across 4 segments, 2,250 branches for 6% gain in volume in one quarter. Bank branches were able to focus their sales and marketing efforts by product line to appropriately address customer potential in each trade area.


15 | 22

4.7. Branch Operations Efficiency Business ProblemIt is clear that some of the numer-ous bank processes that are handled by the bank’s operations centers are inefficient and need to be automated. Service deficiencies in certain processes hinder branch sales efforts. Due to the large investments at stake, branch operations decision support teams have to spent more than two months conducting in-depth analysis.

Project Objectives and Scope Analysis of all recent branch operations activity in response to requests from branches, an invest-ment brokerage subsidiary and three contact centers. Collect and analyze process information easily from multi-ple systems and determine the top ten high priority and high frequency processes that will be automated.

Results DeliveredEight processes selected and prioritized for automation in a fraction of the budgeted time. In other cases, process step and work reduction was indicated in detail.


16 | 22

4.8. Credit Risk Management Business ProblemWith large numbers of creditors sliding into delinquency it is clear that preventive maintenance of credit terms is required. Behavior based risk scores are not sufficient for credit restructuring needs resulting from housing downturn.

Project Objectives and Scope Design a model that will bench-mark mortgage borrowers and help recommend principal reduc-tion and other restructuring targets case by case for 22,000 mostly non-performing residential mortgages across the USA.Formulation of credit rework offers, based on current balance sheet and targeted behavior, using EPO score as the main ingredient in a logistic probability of default model.

Results DeliveredMortgages heading toward delin-quency in the next three months were identified and regrouped by next steps of action. Expected NPV was used to decide whether to foreclose, restructure or do nothing. 15% of the assets were marked for restructuring, most involving principal reduction.


17 | 22

4.9. Enterprise Incentive Compensation rewardable performance range

Business ProblemIncentive compensation is too little, too late and causes discord. The primary issue is that in a multi-factor performance-reward system, the rewardable KPI ranges are difficult to set correctly and poorly set targets encourage gaming. Headquarters staff reward system is not linked to branch network performance. Account managers are compensated sporadically for “campaign” performance.

Project Objectives and Scope Distribute bonus funds among 18,000 HQ staff and branch network employees. Build a risk adjusted enterprise bonus system based on branch and account manager performance.

Results DeliveredBonus distribution process is com-pleted within days not months. Three times as many account officers qualify for bonus as bank profits set a record.


18 | 22

5.1. How does EPO work?

1. 2. 3.Units are segmented using clustering methods based on key performance variables, which ensures we are comparing “like-for-like” in performance evalua-tion.

Analysis of data in indi-vidual segments using EPO Analysis to deter-mine the most efficient units (on the efficient frontier) which are subsequently used as benchmarks to gauge the relative efficiency (and slack or potential performance improve-ment) of the other units.

Slack re-allocated to the efficient units to opti-mize volume and profit-ability.Inputs: # of Staff

# of Customers Cost

Outputs: Loans Deposits

EPO treats performance as a resource constrained production problem and optimizes performance targets based on peer benchmarks on resource, wage and output levels.

Input

Out

put Efficient frontier

Cluster 1Cluster 2Cluster 3

21.00%

18.00%

15.00%

12.00%

9.00%

6.00%

3.00%

0.00%

-3.00%

-6.00%

-9.00%

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

-11.59% -10.84% -9.10%

20.36%Total Improvement

20.36%

Deposits


19 | 22

5.2. Enabling Power Analysts

Classify data Segment for optimization

Benchmark against

objectives

State objectives using data

fields

1.

3.

2.

4.


20 | 22

5.3. Enabling Enterprise Performance

Discover potential

improvement

Analyze sources of

performance lift

Explain recom-mendations

Generate unit specific recom-

mendations

5.

7.

6.

8.


21 | 22

6. EPO prescriptive analytics at work

EPO approach delivers cross functional analytics for long-range strategies, short-range plans, and annual tactical initia-tives.Data sources can include P&L, Operational Data, syndicated data and more.

Internal data sources are typically refreshed monthly and weekly, external data sources as they become available.

EPO results are inte-grated into the enter-prise BI platform.

PERFORMAnCE WAREhOUSE OPTIMIzER

OlAP CUBE

1. 2.

5.

3.

6.

4.

vISUAlIzATIOn


22 | 22

Contact Us

Thank You.

Levend Beriker, Managing Partner [email protected] Karayel, Partner – Chief Scientist [email protected] Fernandes, Director Business Development [email protected] Bilgili, Senior [email protected]

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

Economy & Finance

Alta Bering Retail Banking Solutions