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3 ways generative AI is being used in Financial Services

3 ways generative AI is being used in Financial Services

Artificial intelligence (AI) and the financial services industry are not new bedfellows.

As far back as 1982, hedge fund firm Renaissance Technologies developed expert, or knowledge systems to solve problems and answer questions within a specific context, according to the Turing Institute. Expert systems were also used in the stock market in what was known as program trading.

3 ways generative AI is being used in FS

In fact, most of us have been using AI-powered tools and platforms in our daily lives for many years. From customer service chatbots we may interact with when a parcel doesn’t arrive, or the requests we make of Siri or Alexa, to the personalised product recommendations we receive on Amazon, or the search results we get from Google, all of these have been enabled by artificial intelligence –  writes Kirstie McDermott, Senior Content Manager, Amply.

The rise of generative AI, a branch of artificial intelligence that enables machines to create original and realistic content, such as images, music, or text, by learning patterns and generating new outputs based on that learned information, is now influencing all sorts of industries and sectors––including financial services.

In a wider context, global content and technology company Thomson Reuters has announced a new plugin with Microsoft 365 Copilot, which offers advanced AI experiences across its productivity suite. Steve Hasker, president and CEO at Thomson Reuters, says that “Generative AI empowers professionals to redefine their work and discover innovative approaches”.

At Goldman Sachs, developers are internally testing generative AI tools to assist their code writing, according to its chief information officer Marco Argenti. He said usage was currently in a “proof of concept” stage and that “developers are already using some of the assisted coding technology”.

Chipmaker NVIDIA’s recent State of AI in Financial Services report notes that fintech companies are increasing the pace at which they deploy AI-enabled applications and that the number of companies which would have considered their adoption to be lacking has reduced.

Within the finance sector, AI can be used for a host of issues including fraud detection and prevention; customer marketing and acquisition; client satisfaction and retention, and credit risk management. NVIDIA’s report highlights some specific areas of interest too.

1. Reduce costs

Forty-six percent of respondents reported improved customer experience via AI, 35% said it created operational efficiencies, with 20% reporting a reduction in the total cost of ownership. Plus, 36% indicated decreased annual costs by more than 10%, a “needle-moving impact,” according to the report’s authors.

2. Drives opportunity

Creating new business opportunities is key for any growing business regardless of industry. AI is a driving force for 17% who said it created a competitive advantage, and 15% reported that it yielded more accurate models.

3. Offers future potential

AI offers financial services companies the potential to make a difference in how financial companies operate, across numerous different use cases and applications. Natural language processing (NLP) or large language models (LLMs) are being used by 26% of companies, recommender systems / next-best action are being utilised by 23%, 12% are using AI for their environmental, social, and governance (ESG), with 12% using it for fraud detection across anti-money laundering and know your customer

If you are in the market for a new role, then the Payments, Cards and Mobile Job Board is a great place to start your search. It contains thousands of open fintech roles, like the three below.

At Ripple in London, there is a Product Manager, Blockchain Data role on offer. Here, you’ll identify and generate use-cases for new data products, understand XRP ledger use cases for data infrastructure, translating those into tangible requirements, and write product requirements focused on data API and services feature development. You’ll need five years’ of experience in both product management and in driving data platform development.

Metro Bank seeks a Credit Risk Commercial Analyst, in London. You will support data analysis and processing, perform reconciliation and validation routines across all deliverables, and ensure data and reporting is timely and accurate. Sound technical experience in SAS or SQL is required and you will be able to perform data manipulations, investigations and report findings.

A Software Engineer – Future Needs role is available at American Express Company in London. You’ll drive the latest development practices, will write code and unit tests, work with API specs and automation and identify opportunities for adopting new technologies. To apply you will need a BS degree in computer science, computer engineering, or another technical discipline, plus proven experience with multiple full cycle implementations.

For thousands of opportunities across the finance sector, visit the Payments, Cards and Mobile Job Board today

The post 3 ways generative AI is being used in Financial Services appeared first on Payments Cards & Mobile.

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