FinTech Futures Jobs: Three ways generative AI is being used in financial services
Ever since OpenAI launched its ground-breaking chatbot ChatGPT, every industry has been debating not just the merits, but the morality of AI.
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After launching in November 2022, ChatGPT had gained 100 million users by January of this year, making it the fastest growing and most speedily adopted app yet—it took Instagram more than two years to reach the same kind of numbers, and TikTok nine months.
Such rapid adoption is why Google is hot on the heels of OpenAI in an effort to establish Bard, its own generative AI tool, as the world’s go-to conversational AI partner.
On a governmental level, the UK has unveiled its approach to AI innovation via a recent white paper. In it, it details how businesses can use artificial intelligence to responsibly innovate, grow and create jobs.
And according to an analysis conducted by Stanford University’s Institute for Human-Centered AI, global corporate investment in AI reached almost $276.14 billion in 2021, up 88% from the previous year, when $146.74 billion was invested into AI-focused companies.
However, not all advances in AI are being welcomed with open arms. Detractor Dr Geoffrey Hinton, the so-called “godfather of AI”, has spoken out about the danger of the “scary” chatbots he helped create at Google.
Then there’s the very real cybersecurity threats: research has found that cybercriminals on underground hacking forums are using generative AI to create encryption tools, write malware and even launch new dark web marketplaces.
Despite these worries, the financial services industry in particular is charging ahead with its plans to use generative AI to overhaul the way it does business for the better.
1. Streamlining processes
When it comes to compliance, natural language processing has the capacity to bolster fraud prevention by enhancing anti-money laundering (AML) and know your customer (KYC) processes and protocols.
Machine learning technology is also being used to reinforce and strengthen credit risk analysis by automating loan underwriting.
2. Improving customer service
According to recent data by chipmaker Nvidia, banks, trading firms and hedge funds are using generative AI to create more personalised customer experiences. The study used Deutsche Bank’s recently revealed plans to embed AI into financial services, including intelligent avatars, speech AI, fraud detection and risk management, as an example of this.
3. Turbocharging data
While data analysts have been using analytics and consumer trends to inform decision making for several years, generative AI has the potential to give data the edge when it comes to creating vast knowledge bases.
OpenAI has already been used by Morgan Stanley to power an internal-facing chatbot that can search wealth management content and which “effectively unlocks the cumulative knowledge of Morgan Stanley Wealth Management”, says Jeff McMillan, head of analytics, data and innovation at Morgan Stanley.
He adds: “You essentially have the knowledge of the most knowledgeable person in Wealth Management—instantly. Think of it as having our Chief Investment Strategist, Chief Global Economist, Global Equities Strategist and every other analyst around the globe on call for every advisor, every day. We believe that is a transformative capability for our company.”
One of the biggest challenges company’s now face in the booming AI market is attracting top talent, meaning the job market is ripe with opportunities.
And if switching jobs has been on your radar or you’re ready to pivot to a career in AI, the FinTech Futures Job Board is the perfect place to start your search.
It features thousands of jobs in companies that are actively hiring, like the three below.
Senior ML Ops Engineer, Zilch UK, London
Since launching as an FCA-regulated business in the UK in September 2020 and in the US in May 2022, Zilch has amassed over three million customers. As a Senior ML Ops Engineer, you will design the data pipelines and engineering infrastructure to support enterprise machine learning systems at scale.
You will also work with data scientists to turn offline models into real machine learning production systems and develop and deploy scalable tools and services to handle machine learning training and inference.
You will also be required to identify and evaluate new technologies to improve performance, maintainability and reliability of the company’s machine learning systems.
Consultant, Business Intelligence Analyst (AI & Data), Defence and Security, SAMA, Deloitte, London
Do you want to be at the heart of some of the biggest and most ambitious programmes undertaken to keep Britain safe? Deloitte is hiring a Business Intelligence Analyst to work with defence and security clients on a range of initiatives.
The data and analytics delivery team sits within the firm’s AI and data consulting group, and you’ll be working on a range of initiatives and projects across the defence and security sector.
All applicants must be willing and eligible to apply and obtain UK security clearance to Security Check (SC) or Developed Vetting (DV) level, if not holding an existing clearance.
See the full job description here.
Senior Manager AI Risk Management, HSBC, London
HSBC’s risk and compliance function oversees a comprehensive risk management framework and it is seeking an individual to join the team in the role of Senior Manager AI Risk Management.
You will help build management, regulatory and external confidence in all AI tools used across the group, work collaboratively and provide subject matter expertise for a team of governance and technical professionals in AI operating across geographies, support the development of a risk review framework for AI applications and assist in running the governance cycle for newly identified AI use cases.
For hundreds more opportunities across fintech, visit the FinTech Futures Job Board today.
