The AI technology landscape in financial services
The world of AI technology is accelerating at breakneck speed, even though it is still relatively in its infancy and still largely experimental. The fact that it is rapidly making waves everywhere, truly breaking new ground, and early iterations of the product are being adopted at such a rapid pace is a testament to its utility that is demonstrated across a wide range of business applications. It’s also improving at an astonishing pace with new iterations and versions coming out in quick succession. As new AI products and services emerge in the financial services market, it can be difficult to separate the sizzle from the steak.
One of the biggest barriers the industry faces in realizing the great benefits of AI was underscored by an Accenture survey that interviewed 100 wealth management executives across North America. Reports indicate that wealth management firms are having difficulty separating the “signal from the noise” when it comes to artificial intelligence and wealth management. While 84% of survey respondents agree that AI adoption will transform the industry in the next five years, more than 80% of companies are stuck in the proof-of-concept phase with narrowly siled efforts within a department or team.
It starkly appears that there is a need for more education and learning on exactly how AI works and how it can best be applied strategically and operationally in a financial services company.
To better understand the AI landscape and its applications in financial services, we reached out to the institute’s founding member Nathan Stevenson, CEO of ForwardLane – a financial technology company founded specifically to help financial institutions harness the power of artificial intelligence. They have developed the AI Insights platform and Next-Best-Action Engine and recently launched a new AI decision and intelligence platform called EMERGE. They have also been honored with a range of awards along the way, such as the Wealth100, AIFinTech100 and FinTech Futures Banking Tech Awards. As a long-time innovator in the AI community, we asked Nathan questions to learn from his unique perspective and experiences applying AI to the financial services industry.
age: How did you first get involved in AI technology and what are some of the most compelling experiences you’ve had along the way?
Stevenson: My background is in quantitative finance in alternative asset management, CQS and so I have spent most of my career analyzing data and coming up with systems and algorithms to find opportunities in that data – trading opportunities, research opportunities, working with both organizations and brokers. Unstructured data. When I got into AI early on, what I found interesting is that the basic mathematics at the core of AI is very similar to the mathematics I studied when I was studying financial derivatives and credit derivatives in financial markets. I discovered that my advanced credit math skill set directly related to AI and I was very excited about it. Then I immediately immersed myself in the topic and read literally hundreds of research papers on artificial intelligence.
The defining moment for me really came when IBM Watson came out and there were rumors that Watson would be available to beta testers and researchers. I quickly connected with IBM and we became part of the first “Powered by IBM Watson” program. We’ve got early access to Watson. At the time, we thought it was the Deep Blue supercomputer that was used to beat chess grandmaster Garry Kasparov. It wasn’t actually like that, but it was actually a great foundation to start from.
So today we work closely with Amazon Web Services (AWS), NVIDIA, and Entropik. And the way we dealt with these companies was actually through this development that we saw in the world of artificial intelligence. OpenAI has already come out of the gates with GPT 4, and now GPT4 Turbo – a really cool piece of technology, and of course ChatGPT. And we’re working with a big language model called Claude2 from Anthropic, with which we’re making amazing progress. Additionally, we are part of the first-ever AWS NVIDIA Global FinTech Accelerator program.
age: Where do you see us being now in AI technology development and AI solution providers?
Stevenson: This is a very interesting question. Although the market seems saturated now, we are really at the beginning, at the beginning. Think of this as the beginning of the Internet and chatGPT is Netscape or Mosaic. It’s really the first time we’ve been able to use this technology in so many different ways and we can really see how this changes the workflow.
AI is now involved in many different parts of creative, from visuals to video editing, from content writing to podcasting, and a whole host of other different tools. So, I would say it’s moving faster in this creative space.
When it comes to other areas like financial services, they are really green opportunities right now, and we are starting to see large organizations responding to this first phase of testing and piloting the technology. What we’ve seen first-hand is that it can be launched very quickly, relatively easily, and can provide immediate value. That’s what we’re really excited about, the speed at which we can now do things with our AI platform.
age: AI technology is evolving so rapidly that we are introduced to ChatGPT, which is now GPT4 Turbo and GPT proxies. In your opinion, where do we go next with AI technology and its applications in the financial services industry? Are we close to another major bridge with technology?
Stevenson: What Google is working on with its new multimedia AI system, Gemini, is another wave of AI developments. Multimedia just means a combination of images and text, not fully into video yet, but it’s getting there. What this means is that if you can combine images with text, you can get a more comprehensive picture or multi-faceted picture of a subject or topic.
If you think about economic reports and research reports, you’ll find that there’s a lot of work that goes into graphs and visuals and how they relate to text. In many cases, it creates additional context and better understanding. The next simple step is really this ability to process and understand economic reports, charts, and dashboards in new and interesting ways. Instead of necessarily having to dig into the dashboard, I can just take a screenshot of it, upload the image, and ask for insights directly from it. This would be a game changer.
The whole idea of dashboards will disappear. Dashboards are useful in some cases, but you won’t need them. Besides this ability to interpret charts, drawings, and other types of images, along with text in one context, you will also be able to create charts and reports in another context.
So, Open AI’s newly released Cloud2, Gemini, Bard, and GPT4-Turbo will reduce costs, expand the context window to 128K (300+ pages), and provide multimedia capabilities for interpreting and creating charts, analytics, and more.
These providers will provide custom, no-code tools to enable organizations and individuals to build their own “agents.”
age: What advice would you give to a company debating whether to build or buy AI capabilities at this stage? What do you need to know?
Stevenson: In building AI capabilities, you can do several basic things right now. With so many tools thriving everywhere on the internet, you can just go and use ChatGPT products directly yourself. There are a lot of cool things you can do with AI today. So, go all out and use the tools that have been created for you. But when it comes to financial data, when it comes to trying to apply that to the financial services space, you really want to find a trusted partner that has done this work before.
There is a lot to consider here. There is a lot of testing behind the scenes to reach the goal good Answer and you don’t want to waste your time trying to figure these things out. I think there will be horizontal capabilities. Marketing could be one of them. Processing information such as simply asking questions related to your knowledge base is another.
And so, certainly a lot of really good internal capabilities can be implemented on a build basis, but you have to ask yourself the question, What should you build, what should you outsource, and who should your partners be? So, it really depends on the use case and a lot of companies have adopted different strategies. With the vertical type of applications that need to be created across the company, they will be integrated with partners.
age: Having worked with several key technology partners, can you share recommendations or benchmarks for financial companies in the evaluation Amnesty International Solution providers?
Stevenson: Well, I think if you’re thinking about wealth management, asset management, and insurance applications, you want a technology partner with deep financial services experience. This goes without saying, but the devil is in the details. You need to be a partner that truly understands financial services data and the fundamentals of that data, but also has the experience needed to work with your solutions and existing data warehouse databases as they are today. This requires experience in solution architecture and organizations.
This requires a team with IT qualifications to be able to meet the highest ITIL standards for security, process and enterprise consideration. These are things like data governance, data provisioning costs, data security, data privacy, but also things like security by design where the solution is built from the ground up to be secure. The entire data path can be very complex to navigate and confusing.
This is where ForwardLane and others in the industry like it Craig Iskowitz And the Ezra CollectionWe specialize in the field of wealth management, interpreting structures and arriving at solutions. F2 strategy is another excellent asset and wealth management suite to help navigate these types of applications.
So, if you don’t have those skills, depending on your size, go to one of these consulting companies that can help you find solutions. If you are a mid-sized or larger company, look for partners who complement your skill set and are there to work in partnership with you and not to replace you. Think about partners like Forward Lane that enhance some of the capabilities you already have or amplify or multiply what you’ve already done with your data analytics teams and architectures and how you can get the most out of your existing investments. This is where we can be really helpful, as that connective layer that helps you achieve results.
the Innovation Development Institute It is an education and business development catalyst for growth-oriented financial advisors and financial services firms intent on leading their businesses in an operating environment to accelerate business and cultural change. We work as a business innovation platform and educational resource with members of fintech and financial services companies to openly share their unique perspectives and activities. The goal is to build awareness and stimulate open thought leadership discussions around new or cutting-edge industry approaches and thinking to facilitate next generation growth, differentiation and unique community engagement strategies. The Institute was launched with the support and insight of our founding sponsors – Ultimus Fund Solutions, Nasdaq, FLX Networks, TIFIN, Advisorpedia, Pershing, Fidelity, Voya Financial, and Charter Financial Publishing (publisher of Financial Advisor and Private Wealth magazines).