Calybre: accelerating compliance with generative AI

Tech Central
June 18, 2024

In many industries, especially the financial sector, adherence to an ever-increasing regulatory burden is crucial. When used effectively, generative artificial intelligence (gen AI), and particularly large language models (LLMs), empower organisations to respond more swiftly and effectively to these requirements.

The practical application of LLMs

LLMs are advanced AI algorithms that use neural network techniques with a vast number of parameters to process and understand human language, generally in the form of extensive passages of text.

There are multiple practical use cases for LLMs, and the applications are increasing daily as more businesses realise the power of being able to make sense of textual data. This technological advancement has been swift as processing power has become faster and cheaper and tools have become smarter and more able to make sense of a myriad textual formats, languages and contexts.

The usefulness and relevance of models

Models that are available through various gen AI sources are only able to base their “intelligence” on data that has been publicly shared up to their last update, meaning that the model may not be up to date with the latest information. To make these models useful for business, especially when dealing with sensitive information, we need to combine them with our own data, a personal touch made possible by recent technologies.

The advantage of rapid prototyping

The enablement of rapid prototyping allows teams to swiftly confirm the feasibility of gen AI-based solutions before having to commit any substantial investment to the initiative. Rather than manually collecting and processing news articles to understand the sentiment, LLMs simplify the process by identifying articles that reference a specified topic and directly querying the LLM to ascertain whether the coverage is negative or positive.

Revolutionising KYC processes

LLMs can be used to revolutionise client data validation, required in KYC (“know your customer”) processes, by swiftly identifying and rectifying inconsistencies in address and contact information. Such solutions efficiently process extensive datasets and verify them against reliable sources, thereby streamlining operations and enhancing data accuracy and client relationships. Furthermore, integrating this technology with an organisation’s customer management system ensures consistent, up-to-date client data, thus providing the added benefit of improved data integrity and quality.

Enhancing CDD processes

Enhancements in customer due diligence (CDD) processes can be implemented with relative ease. When dealing with politically exposed individuals and multinational corporations, CDD processes have traditionally been labour intensive, with staff manually verifying customer identities from various sources. However, by strategically integrating a series of web services together with OpenAI, tasks that typically took several minutes can now be completed in mere seconds. Although this may appear to be a minor improvement, the time savings become substantial when applied to each customer with the added benefit of rapid repeatability.

Analysing complex legal documents

Another instance of the efficiencies brought by gen AI in compliance processes is in the analysis of complex legal documents. Advanced data science techniques, ranging from fine-tuning an existing model to retrieval augmented generation, may significantly boost the organisation’s ability to categorise and assess potential risks arising from contract breaches or situations that could disadvantage the company. A practical implementation might involve developing a system that incorporates various regulations, such as the General Data Protection Regulation (GDPR), the “AI Act” and other relevant laws, to create a tool that finds areas of potential vulnerability. This tool could be especially beneficial in detecting non-compliance with data protection standards or potential legal liabilities, thus enabling proactive risk management and mitigation strategies.

Moving LLMs into production

Before moving any solution into a production state, it is essential to continue refining the solution to improve its performance and to ensure that further risks are not introduced. While a toolset or framework may hasten the development of an application, it might overlook certain nuances that only business insight with human intervention can address. It is also critical to thoroughly investigate and rectify any biases present in the model. This may only be possible by retraining the model to the relevant situation over a period, based on renewed and enhanced datasets.

Transitioning the solution from a developer’s machine to a more controlled, often cloud-based environment is crucial for stability and scalability. Once the solution is in production, consideration needs to be given to how data may change over time, and mechanisms must be put in place to ensure that the model is running at a consistent standard.

Calybre: your partner in governance and compliance solutions

It is a fact that gen AI is changing the world of work as we know it and that tech-savvy business professionals will be able to use the power of technology to increase efficiency in their processes and output volumes. Setting up a robust, accurate, and reliable model and architecture should not be underestimated. At Calybre, we support our customers in setting up practical models, focusing on extreme time-to-value solutions, and underpinning these business outputs with understanding of corporate governance and compliance needs. We can guide and assist you from conception to realisation, as well as embarking on an iterative growth journey to ensure the optimal result from your data.

About Calybre

Calybre is a dynamic data consulting company that guarantees delivery beyond expectations. Our business model and forward investment in our people allow us to remain consistently a step ahead. We guarantee the performance of our people by continuously sourcing, selecting, growing and nurturing the right talent to ensure abundant capability on demand. We structure ourselves in small teams with expert leaders to foster the agility, creativity, simplicity and speed needed to build trust in our customers. We focus on co-creation, embedding our people into our customers’ worlds for a seamless experience. We refuse to settle for mediocrity, and we embrace complexity, aiming for extreme clarity in everything we do. We really care about making a difference. Visit Calybre on LinkedIn, Facebook or Instagram.

This article was originally published on Tech Central on 18 June 2024

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