Transforming Transaction Models: $50MM in Cost Savings

7Alder is the only end-to-end transaction execution partner for lower-middle-market M&A, providing flexible analytical and deal-team capacity from opportunity through close.

Client

The client is a revolutionary company in the vehicle technology sector, transforming how vehicles, businesses, governments, and drivers interact. With its advanced digital platform, the Client offers seamless integration and intuitive interfaces that simplify complex processes across dealerships, drivers, government agencies, and enterprises. The Client’s solutions include digital title and registration, fraud protection, digital signatures, DMV compliance training, and much more. Their services are available across all 50 states, ensuring that each state’s unique requirements are met with tailored solutions.

The Challenge

The Client’s transaction models were housed in a database, written in SQL code. This allowed models to process very quickly. Each model is made up of thousands of logical statements layered on top of another. Combined, this web of logic creates a model that can ingest hundreds of inputs, run those inputs through logical calculations, then output the desired results based on the input data. Each model being written in code and housed in a database limited the Client’s ability to fine tune and correct errors that may have occurred in the model. Over time this created a host of problems which were detrimental to operations and negatively impacted potential revenue and profit margins.

Initial Situation

• Need for ChangeThe Client needs to be able to adjust models within minutes, not days. Models need to be fine tuned to penny perfect, not within a hundred dollars. Models need to be 100% dynamic, adaptable, and scalable.

7Alder’s Approach

When the Client approached 7Alder, the challenges were clearly articulated:

• Sustainability IssuesThe existing models struggled to maintain correct logic as time went on.
• Accuracy ConcernsErrors in transaction processing were leading to client dissatisfaction.
• Model AdaptabilityModels were difficult to adjust and fine tune, leading to false patches and compounding logic problems.

Understanding the Challenge

Working alongside the Client, 7Alder determined a strategic plan:

• Enhancing SustainabilitySwitch out the database SQL models for API-connected Excel models.
• Improving AccuracyIncorporate advanced algorithms and clear structures to reduce errors while maximizing reliability.
• Increasing AdaptabilityLeverage clear structure and logic to easily fine-tune and adjust models at a moment’s notice.

Implementation Process

Models were grouped into batches; each batch went through this process:

• TransitionOriginal SQL code was extracted and converted into Excel, including all tables, data, calculations, and structure.
• CorrectionOnce models were in Excel form, they were duplicated for the documentation process, and corrected. The corrections included working closely with research experts providing relevant model information. Each model was corrected until it was penny perfect against thousands of historical transactions.
• DocumentationThroughout this process, everything was documented and notated to work as a guide to understand and manage models into the future. A complete structure and user guide was generated to make model adjustment easy to understand for anyone.
• DeploymentOnce models had been documented and tested for correctness against historical data, they were deployed. Models were connected to an API to handle customer transactions. These models are handling millions of transactions on a weekly basis, continuing to maintain correctness.

Improving Correctness

• Phases of ImplementationThis chart depicts the amount of correctness errors in a model over time and the impact of working with 7Alder. Remaining correctness errors are due to incorrect data entry by the client. The model is theoretically perfect in all possible situations.

Key Features

• Improved AccuracyEvery logical decision within a model is documented. All relevant constants and variable calculations are easily accessible for fine-tuning. Models are tested against thousands of historical transactions.
• ScalabilityModels are honed to penny perfect in thousands of situations and duplicated within the API, allowing for easy adjustments and the ability to handle millions of transactions simultaneously.
• EfficiencyModels are designed with tight, clean logic and algorithms, maximizing compute strength and efficiency. A transaction can be processed through the API and model in less than a second.
• Ease of UseModels are designed to be user-friendly. Constants that change on a weekly or monthly basis can be easily adjusted. Variable logic changing in a cyclical schedule is built into the model for automatic updates.

Benefits to Client

• Operational EfficiencyStreamlined operations and reduced downtime.
• Cost SavingsThe new models generate an estimated ~$50MM in cost savings and client retention.
• Accuracy and AdaptabilityAccurate and adaptable models using cutting-edge logic.
• Enhanced Client SatisfactionImproved service, near-instant response times, and highly accurate models lead to increased client satisfaction.
• Future-ProofingModels are designed to adapt to future needs and technological advancements.

Client’s Perspective

“Wil and the team are masters of Excel. No matter the issue we ran into, they were able to find a solution that worked for us. They adapt quickly and finish the job on time. Wil responds quickly and communicates complex ideas in a simple, easy-to-understand way. 7Alder has supported us on a variety of projects, exceeding expectations consistently.”

Impact Statement

Working with 7Alder has been a successful experience for our company. Their expertise in model development and operational logic has allowed us to overhaul our transaction models. The new models are more accurate, efficient, and scalable, directly contributing to enhanced client satisfaction and operational efficiency.

Closing

The collaboration between 7Alder and the Client has resulted in a significant transformation of the Client’s transaction models, with benefits of ~$50MM and improved operational outcomes.

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