The benefit of artificial intelligence and machine learning will come from enhanced productivity so long as banks can identify and pursue the right business cases. 
 

At Monocle we can assist you to identify and prioritise the following:

 

 

 

 

 

 

 

Value

Target opportunities with clear business cases and benefits

 

 

Use an enterprise LLM to handle the repetitive and time consuming task of analysing routine reports and providing initial variance commentary.

Sustainability

Match your bank’s strengths to attainable AI capabilities

 

 

 

 

BCBS 239 compliance has made risk data and risk reporting some of the most robust in banks, lending itself to reliable input for an LLM.

AI Risk Management

Avoid critical operations where ethical concerns are most intense.

 

 

 

 

Enterprise LLM solutions ensure strong security and privacy frameworks are in place to protect the bank’s data.

By 2026, more than 80% of banks will have adopted GenAI. Let us assist you in getting a meaningful return on investment.

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Artificial Intelligence Business Case

Reporting Commentary Through Generative AI

Automated Financial Commentary

 

 

 

 

In a recent proof of concept (PoC) project, Monocle consulted for a large retail, corporate and investment bank to enhance its internal financial reporting process using Generative AI (GenAI). This initiative was part of the bank’s broader strategy focused on integrating AI into its business architecture.

 

 The bank chose to leverage an enterprise large language model (LLM) which provided robust data and privacy controls essential for handling sensitive financial information securely.

 

The project’s primary objective was to streamline internal financial reporting by automating the generation of customised commentary on financial data. Using data from the General Ledger, the LLM would produce variance commentary and eventually provide reasoning behind the change if provided the necessary data. The benefits of this solution is that you can build customised prompts for the commentary output as well as significantly reduce the routine workload of the finance control team, thereby freeing up their capacity to perform decisioning making analysis.

 

Extensive risk assessments were conducted prior to and during the project. Concerns around data governance were addressed in these assessments and in the choice of a trusted technology vendor. As part of the enterprise service, all prompts, completions, embeddings and training data are not provided to any third party and LLM service providers and can be deleted at any time.

By launching and scaling this solution, the bank expects to reduce the time spent on routine report commentary tasks by approximately 15% of the total monthly reporting time across hundreds of financial report stakeholders.

 

 

 

 

Monocle's AI Expertise

 

 

 

 

 

 

With over 20 years of experience, Monocle offers cross-functional consulting services across a comprehensive range of roles, including data scientists, business analysts, developers, and project managers. Monocle assists our banking and insurance clients in identifying viable opportunities for AI and ML application and then executing these projects starting at proof of concept through to embedment.