Success Story Financial Services

Rural Bank Modernizes Lending Capabilities with New Data Warehouse Platform

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This bank is part of the US Farm Credit System and has been lending financial and business support to agriculture and rural America for more than a century.

The company is committed to moving into the future with a progressive mindset and a passionate workforce to respond to rapid changes in the technology and business landscape. The bank strives to serve as an extension of the associations it serves, providing systems and services that can be optimized by leveraging economies of scale and centralization.

Apexon began its strategic partnership with the bank in December of 2019 starting with the current state assessment of its enterprise data warehouse and finance data warehouse.

  • Bank Headquarters in Columbia

    Headquarters in Columbia, SC

  • Wholesale lender

    Wholesale lender, BSP to local Farm and Ag credit associations

  • Provides financing to 80,000 farmers, agribusiness, real estate and rural homeowners

    Provides real estate, production financing to 80,000 farmers, agribusiness and rural homeowners

  • $37 billion company

    A $37 billion company, largest financial institution based in South Carolina, and one of four wholesale banks within the nationwide Farm Credit System

The customer journey
2019

2020

2021

2022

2019
  • Current State Analysis of data assets

2020
  • Build a roadmap to address the challenges identified
  • Build Investment Data Mart
  • Build application to make adjustments on investment data

2021
  • Build applications to adjust Mask data and report to Funding corp
  • Rewrite Loan Data Mart
  • Rewrite application to make adjustments on Loan data

2022
  • User acceptance testing the Data Marts and application
  • Onboard business users and execute parallel runs
  • Decommission Finance data Warehouse and Cognos application

the Results

Key Outcomes

Increased Flexibility & Ease of Use
Increased Flexibility
& Ease of Use

Higher Customer Satisfaction
Higher Customer
Satisfaction

Operational Efficiency
Operational
Efficiency

Our methodology

how
we did it

Apexon works with companies across the digital lifecycle.

Go Digital
Go Digital

Accelerating the delivery of new digital initiatives with confidence

Be digital
Be digital

Creating the infrastructure and foundation to scale digital initiatives

Evolve Digital
Evolve Digital

Leveraging data and analytics to continuously improve digital delivery processes

Launch & Experiment

Automate & Accelerate

Be Intelligent & Autonomous

Launch & Experiment

Enable digital adoption in a quick, and agile mannertransform the patient experience

Apexon helped assess the current state and identified opportunities to enhance the bank’s current data assets.

Automate & Accelerate

Build digital infrastructure and foundation for enterprises to scaledigitization on patient Experience

Apexon built a roadmap showing the transformation of existing data assets and the addition of new data assets.

Be Intelligent & Autonomous

Leverage data engineering to make strategic decisions and get digital right every time

The challenge

Building a New platform

The bank wanted to become a truly “data-powered” company. This required building an enterprise data warehouse platform to bring all the data assets together to address several challenges:

Source data in its enterprise data warehouse

Incomplete source data in its enterprise data warehouse

best practices in data modelling

A lack of best practices in data modelling

maintain and support the application

Inability to maintain and support the application to make adjustments to data

Data adjustment

Data adjustment being completed in multiple places

version of on-prem Hyperion in use

Unsupported version of on-prem Hyperion in use

build new Investment and District cubes

Incomplete Hyperion cubes required to build new Investment and District cubes

The solution

propose & execute a four-phase plan

The Apexon data services team understood the challenges faced with existing data assets like enterprise data warehouse and finance data warehouse. Apexon proposed and executed on a four-phase plan to address the bank’s needs:

Phase 1

Migrate Data Marts

Migrate Data Marts

Migrate the data marts (loan/finance) in the bank’s finance data warehouse to an enterprise data warehouse platform and decommission the finance data warehouse. This ensured that all data would be available on the same platform.

Custom Application

Custom Application

Build a custom application to replicate the functionality from the bank’s Cognos application and then decommission it.

Investment Cube

Investment Cube

Build an investment cube to process investment data and load Hyperion cube for the business to generate reports.

Upgrade Hyperion

Upgrade Hyperion

Upgrade Hyperion from 11.1.2.4 to 11.2.6 to extend Oracle support to the on-prem Hyperion application.

Phase 2

Migrate loan data mart

Migrate loan data mart

Migrate loan data mart from finance data warehouse to enterprise data warehouse platform.

Rewrite Existing Application

Rewrite Existing Application

Rewrite the existing Adjust It application to accommodate approval of adjustments.

Phase 3

Migrate Finance data mart

Migrate Finance data mart

Migrate the finance data mart from the finance data warehouse to the enterprise data warehouse platform.

Phase 4

Build ETL to process

Build ETL

Build ETL to process the District from loan/finance/investment data marts.

Build an application to adjust the District data

Build Application

Build an application to adjust the District data before loading the Hyperion cubes.

Build Hyperion cubes to load the District data

Build Hyperion Cubes

Build Hyperion cubes to load the District data and generate reports for users.

Key Outcomes

Increased Flexibility & Ease of Use

Increased Flexibility & Ease of Use The new application’s ability to make adjustments to data and process it in near real-time gives the bank the ability to configure the business rules and process those rules in near real time. Business users can add new fields and make changes to data in the fields. This revised flow of hierarchy reduces cycle time from 48 hours to 20 minutes

Higher Customer Satisfaction

Higher Customer Satisfaction New report configuration capability to add/edit/delete the fields in the report and provide approvals to the adjustments made to the data

Scalable Architecture

Scalable Architecture To support inclusion of multiple subject areas to scale