GDPR Compliance
Client: Building Society
Function(s): Credit Risk, Data Management, Data Warehousing
Objective(s):
- Migrate from an Oracle data-mart to a GDPR-compliant SAS data-mart;
- Automate monthly data load; and,
- Create an automated process to apply data-retention policies to personal data.
Outcome(s):
- Multi-phase approach that supported separable deliverables with reduced complexity, discrete test stages and iterative releases;
- GDPR data-separation dynamically generated from metadata allowing for faster iterations through test cycles;
- Flexible and extendable data-purge process that executed automatically, enforced data retention policies and maintained audit trails; and,
- Monthly processes integrated within the existing batch schedule, incorporating restart and rollback capabilities.
Data Centre Migration
Client: Financial Services
Function(s): Change Delivery, IT Systems, SAS Architecture, Platform Configuration
Objective(s):
- Migrate all SAS platforms, systems and data from incumbent data centres to replacement data centres;
- Minimize operational disruption at cutover; and,
- Ensure no gaps in data processing schedules or output generation.
Outcome(s):
- Multiple, version-specific, SAS platforms built and configured;
- Multiple, version-specific, SAS batches migrated and adjusted to support target environments;
- All SAS environments and processing integrated with new source and target systems;
- All SAS elements validated and assured prior to go-live; and,
- Cutover plan formulated, coordinated and executed to ensure zero-impact to business operations.
SAS Platform Consolidation
Client: Lending Administration
Function(s): IT Systems, Platform Configuration, Business Intelligence, Management Information, Data Management, System Administration
Objective(s):
- Consolidate multiple SAS platforms into a single instance to reduce run-costs, simplify platform management and provide alignment to the target operating model.
Outcome(s):
- Updated configuration and security model to support new data sources and outputs;
- Rationalised existing warehouse processes;
- Provided support to individual business units with adjustments required for their SAS components and general preparedness for go-live;
- Migrated SAS self-serve reporting via a metadata-driven partial-promotion process;
- Adjusted or rebuilt existing warehouse processes to function correctly on new SAS grid based platform;
- Built automated process to upgrade and validate all SAS files from 32-bit to 64-bit and move them to new file-system locations;
- Extensive testing and validation conducted to ensure all reporting, batch jobs and interfaces were as expected; and,
- Transition to target platform achieved with minimal disruption to the business.
Supply Chain Management
Client: Building Materials Provider
Function(s): Business Intelligence, Operations, Finance
Objective(s):
- Create self-serve reporting capability for new bespoke inventory management and logistics system; and,
- To run against the operational system and not a data warehouse in order to provide up-to-minute information.
Outcome(s):
- Created and configured environments to support separate development, test and live activities;
- Delivered browser-based ability for users to run reports against real-time data to support activities such as invoice generation; and,
- Implemented overnight batch reporting that automatically produced and printed pick-lists for each branch to action upon opening.
Systems Analysis & Data Mapping
Client: Mortgage Provider
Function(s): Change Delivery, Operations, Finance, Management Information
Objective(s):
- Accurately map customer and account information from one mortgage administration system to another;
- Ensure continuity of service and account processing in line with T&Cs and customer expectations on the target system; and,
- Ensure continuity of internal and external Management Information reporting.
Outcome(s):
- Identified all data items required to support system-based account processing and associated data-driven business processes;
- Defined the necessary transforms to map each data item from the source to target application databases;
- Undertook cutover and implementation planning exercises, and determined additional data manipulations required to support the real-time execution of the migration;
- Designed and built a multi-point reconciliation process to validate the migrated data at a record (eg customer, account, transaction) level;
- Quantified the impact on internal and external Management Information reporting as a result of the data migration and/or differences in the processing logic employed by the source and target applications; and,
- Performed gap analyses and process reviews on the target system with regard to data and reporting, plus their downstream impact on Operations and other business functions, leading to the identification of further data/reporting requirements to close the gaps.
Warehouse Optimisation
Client: Insurance Retailer
Function(s): Data Management, Data Warehousing, Change Management
Objective(s):
- Implement strategy to reduce the impact of late arriving data, expansion in data volumes, long-running batches and unavailability of the data warehouse to internal teams.
Outcome(s):
- Additional data-tier was introduced to support the separation of data-warehousing and analytics workloads to reduce contention of server resources;
- Data warehouse processing was reengineered to increase parallelisation, optimise efficiency and augment automation;
- A robust test-strategy of parallel running was designed and executed to identify differences between old and new processes and drive rapid and assured development; and,
- Warehouse processing time was reduced by more than 50% and the introduction of a dedicated data-tier for warehouse users provided successful shielding from batch-related issues.
Customer Remediation
Client: Mortgage Provider
Function(s): Account Processing, Compliance, Customer Service
Objective(s):
- Identify the non-compliant account populations;
- Apply the necessary amendments to rectify the previous errors driving non-compliance; and,
- Update processes (including automated processing) and procedures, where required, to ensure on-going regulatory compliance.
Outcome(s):
- Determined the rules-based selection criteria for affected accounts based on the non-compliant processing that had occurred, and applied those criteria to the mortgage account base to identify the affected population;
- Segmented impacted accounts based on the complexity of the non-compliance, the current status of the account and the number of triggers breached;
- Designed, built, tested and implemented a repeatable process to remediate impacted accounts one segment at a time. This incorporated a suite of SAS programs to:
- Recreate the transaction history and rolling current and arrears balances on each account with non-compliant transactions removed, while still replicating automatic system processing logic such as fee charging;
- Calculate the amount of redress due to each account;
- Generate input files to apply the redress transaction and relevant flags to the account on the operational system;
- Generate mailing files to support the communications strategy for affected customers; and,
- Create extracts to allow annual mortgage statements to be reproduced minus the non-compliant transactions for each year within the period of non-compliance;
- Developed a framework and supporting outputs to provide the Finance Department with up-to-date figures on the number of accounts remediated vs left to remediate, the amount of redress applied to date, and the projected cost of outstanding redress; and,
- Supported both internal and external audits of the project.
Marketing Campaign Process Improvement
Client: Credit Card Company
Function(s): Marketing, Campaign Execution, Process Improvement
Objective(s):
- Reduce the end-to-end development cycle for each campaign-run while maintaining the functionality to:
- Set parameters to limit the number, type, channel and combination of communications sent to an individual in a rolling time-period;
- Rank individual campaigns within the campaign-run to apply a hierarchy to which campaign(s) each eligible customer is selected to receive;
- Apply a hierarchy to the cells within a campaign to determine the content of the communication issued, or to assign the customer to a control group;
- Optionally set a cap on the maximum number of customers selected for an individual cell or campaign; and,
- Define any number and combination of inclusion and/or exclusion criteria, applied at a global, type, channel, campaign and/or cell level, to determine the selection of customers for each individual cell.
Outcome(s):
- Development cycle reduced from 8 weeks to 1 week;
- Campaign documentation generated automatically as part of the campaign build, saving time and effort and ensuring the documentation accurately reflected the logic applied to the campaign build;
- Customer profiling reports developed and generated as part of the campaign-run to ensure the selection criteria for each campaign cell were working as expected and picking the correct customers; and,
- Removed the need to retest the campaign-run each time changes were made to redistribute customer volumes across campaigns, by creating a matrix and detailed customer-level output on the first test run to show the downstream impact of re-ranking campaigns, or applying changes to inclusion/exclusion criteria and campaign/cell volume caps.
Team Formation
Client: Building Society
Function(s): Finance, Management Information, Learning & Development
Objective(s):
- Form, train and develop a new MI reporting team;
- Complete handover of existing MI reports, customer relationships and business/process knowledge from the incumbent team; and,
- Ensure continuity of service for internal and external customers.
Outcome(s):
- Selected the most appropriate candidates to match the role profiles;
- Scoped, shaped and drove delivery through effective project management;
- Extended and updated documentation relating to development processes and standards to be adhered to by the team;
- Captured, verified and collated the business, data and systems knowledge held within the incumbent team, and transferred it to the new one via documentation, structured teaching, practical support and mentoring on a one-to-one basis;
- Provided interim day-to-day management of the team and built strong relationships with internal customers and suppliers; and,
- Completed the handover of management activities to permanent staff members once appointed.