Strict regulation, along with time and cost restraints, means financial services must take a measured approach to technological advancements. However, with the emergence of GenAI, particularly large language models (LLMs), organisations have an opportunity to maximise the value of their data to streamline internal operations and enhance efficiencies.
Embracing GenAI has never been more important for organisations looking to stay ahead of the curve. 40-60% of the global workforce will be impacted by the growth of AI. Moreover, global adoption of GenAI could add the equivalent of $2.6tn to $4.4tn in value annually to global industries. The banking sector stands to gain between $200-340 billion.
But whilst the financial services industry can gain incredible benefits from GenAI, adoption is not without its challenges. Financial organisations must prioritise responsible data management. They must also navigate strict privacy regulations and carefully curate the information they use to train their models. But, for companies that persevere through these obstacles, the benefits will be substantial.
Building customised LLMs for financial services
Consumer chatbots have brought GenAI to the mainstream. Meanwhile, the true potential of this transformative technology lies in its ability to be tailored to the unique needs of any organisation, in any industry. Including the financial sector.
Risk assessment, fraud prevention, and delivering personalised customer experiences are some of the use cases of custom open source models. Created using a company’s proprietary data, these models ensure relevant and accurate results. And are more cost-effective due to their smaller datasets. For instance, banks can use a customised model to seamlessly analyse customer behaviour and flag up any suspicious or fraudulent activities. Or, a model can leverage sophisticated algorithms to assess an individual’s eligibility for a loan.
Another huge benefit of these tailored systems is trust and security. Deploying a custom open-source model eliminates the need to share sensitive information with third parties. This is crucial for organisations operating within such a highly regulated industry. This approach also democratises the training of custom models. Furthermore, it allows organisations to harness the power of GenAI whilst retaining control and compliance.
Using data intelligence to boost AI’s impact
To truly harness the power of GenAI, organisations must cultivate a deep understanding of data across the entire workforce. Every employee, regardless of how technical they are, must grasp the importance of proper data storage. Also how data can be used to improve decision-making.
Organisations can use a data intelligence platform to help implement this. Built on a lakehouse architecture, a data intelligence platform provides an open, unified foundation for all data and governance. It operates as a secure end-to-end solution tailored to the specific needs of the financial services industry. By adopting such a platform, businesses can eliminate their reliance on third party solutions for data analysis. They can create a streamlined approach to data governance and accelerate data-driven outcomes. Users across all levels of the business can navigate their organisation’s data, using GenAI to uncover important insights.
The future of AI in the financial sector
The path to success lies in embracing GenAI as a canvas for crafting bespoke solutions. Whilst no two financial institutions are exactly the same, the industry’s tools must strike a delicate balance between supporting specific use cases and addressing broader requirements, Customised, open source LLMs and data intelligence platforms hold the key, sparking transformative change across the sector. These tailored solutions will empower financial businesses to integrate cutting-edge innovations and ensure security, governance and customer satisfaction. Organisations that embrace this change will not only gain a competitive edge, but also pave the way for larger transformations, re-shaping the financial landscape and setting new standards for the industry.
Databricks is the data and AI company with origins in academia and the open source community. Databricks was founded in 2013 by the original creators of Apache Spark™, Delta Lake and MLflow. As the world’s first and only lakehouse platform in the cloud, Databricks combines the best of data warehouses and data lakes to offer an open and unified platform for data and AI.
- Artificial Intelligence in FinTech
