| Client | Banco de los Trabajadores (BANTRAB), Guatemala |
| Sector | Banking / Financial Services |
| Partner | Asher & Company |
| Engagement since | 2021 |
| Technology | Oracle Enterprise Profitability & Cost Management (EPCM) |
| Methodology | Decision-to-Value™ (D2V™) |
| AI layer | Sáasil, from early ChatGPT experimentation to Anthropic in production |
| Headline outcome | Model build cycle cut from 16 weeks to 10; decision processes that took up to 4 weeks now run in one. |
The challenge
Every bank can tell you whether it is compliant. Far fewer can tell you, with rigor, where the institution makes and loses money by product, by channel, by client segment, by activity. Regulatory reporting answers “are we in order?” It almost never answers the question that drives strategy: “where do we act?”
Closing that gap takes more than a report. It takes an advanced profitability and cost management model. The model has to trace costs through activities to the products and segments that drive them, hold up under scrutiny, and keep evolving as the business does.
Ambition was never the constraint. The constraint was the distance between the people who understand the business and the technical architecture that has to encode it. The bank’s logic lives in the heads of its financial experts. The Oracle platform needs that logic expressed precisely, consistently, and fast enough to keep pace with decisions. That distance has to be crossed again with every model iteration. It is where most cost-and-profitability programs lose momentum and stall.
The solution
Since 2021, Asher & Company has worked alongside BANTRAB to design and build these models on Oracle EPCM, anchored in Asher’s proprietary Decision-to-Value™ (D2V™) methodology. D2V™ is a disciplined path from framing the business question to modeling it, evaluating it, and putting it in front of the people who decide.
The work is built so the model is never a black box. Cost flows, activity logic, and allocation rules are made explicit and traceable inside the Oracle architecture. That discipline is what lets a profitability model survive contact with a bank’s reality: regulatory scrutiny, organizational change, and a standing demand for traceability.
The AI layer: Sáasil
When the AI wave arrived, Asher and BANTRAB did what disciplined teams do. They experimented before they committed. The first exploration ran on ChatGPT. Over a year ago the work moved to Anthropic, which became the foundation of Sáasil, an AI layer that sits between the financial experts and the application.
Sáasil does not replace the expert or the model. Its job is to collapse the distance between them. In practice, it:
- Accelerates communication with impact. It translates between the language of the business and the precision the Oracle architecture demands, so intent becomes implementation faster.
- Helps model the business. It reasons through cost and profitability logic alongside the team and surfaces edge cases and inconsistencies before they reach production.
- Prepares relevant data. It structures and readies the inputs the Oracle EPCM architecture needs, which cuts the manual handling that slows every iteration.
Choosing Anthropic was deliberate for a regulated-banking context, where accuracy, reliability, and traceability are non-negotiable. Those qualities matter most the moment an AI layer touches financial logic.
Results
|
37%
Faster model deployment
|
75%
Faster decision cycles
|
64%
Less manual data prep
|
- 37% faster model deployment. Profitability model build cycles went from 16 weeks to 10, so the bank can respond more quickly to new business questions and organizational changes.
- 75% faster decision support cycles. Going from a business question to a validated, model-backed answer now takes one week instead of up to four.
- 64% reduction in manual data preparation effort. Less time goes into collecting, validating, and preparing inputs for profitability and cost analyses.
- Greater transparency and traceability. The Oracle EPCM architecture shows clearly how costs flow across activities, products, channels, and customer segments.
- Enhanced multidimensional profitability visibility. Management can evaluate performance across customers, products, channels, activities, and organizational units with one consistent profitability framework.
In their words
“For a long time the hard part wasn’t knowing where the bank made money. It was getting that knowledge into a model fast enough to act on it. Working with Asher on Oracle EPCM, with Sáasil in the loop, the time between a question and a defensible answer has dropped sharply. The model stopped being something we wait on. It’s an instrument we use.”
Edy Campa, Head of Profitability (Responsable de Rentabilidad), BANTRAB
What’s next
The collaboration continues to deepen the profitability and cost management models on Oracle EPCM, with Sáasil expanding the team’s capacity to model, validate, and act. The aim is to turn financial architecture into a faster instrument for decisions.
See how Asher can bring Decision-to-Value™ to your finance function. Talk to our team →
© Asher & Company 2026 · Strategic Finance · EPCM · Decision-to-Value™
