Trending
The financial sector quickly adopted generative artificial intelligence, barely pausing to consider the ramifications. While this technology is powerful, it won’t be effective without you. How can you achieve synergy between you and your generative model?
Generative AI’s Affect on Traditional Financial Services
Have you noticed how quickly generative technology is catching on? According to a recent McKinsey report, 65% of respondents adopted it for at least one business function in 2024, up from 33% in 2023 — nearly doubling in just 12 months. If it continues at this rate, it may become a staple in financial services.
AI’s data-driven insight generation is among the main drivers for this exponential growth. It can quickly extract pertinent details from financial documents, bank statements and debt reports, helping you better understand your clients’ situations and needs.
Since a single model can engage with multiple individuals simultaneously, you can use it to personalize client interactions. For example, it could offer custom investment recommendations based on predetermined parameters and user prompts. This feature could be beneficial since over 50% of people expect companies to be available around the clock.
This technology can automatically complete routine processes like document aggregation, invoice processing and compliance reporting with minimal intervention. It can handle all the administrative work, freeing you up to focus on more value-adding tasks. You can automate almost anything depending on how you train your model and which integrations you leverage.
Using a model to streamline your tasks, expand your client list and add value to your services can increase your returns. Organizations that invested in this technology grew their revenue by 4.79%, while those that didn’t saw a 3.56% increase. You can probably recognize why its popularity in this industry is increasing.
Why Financial Institutions Shouldn’t Get Carried Away
AI is already shaping your industry. However, while you might be excited to implement it as soon as possible, you shouldn’t get ahead of yourself — an algorithm can only imitate human intelligence, not replicate it.
Currently, developing a human-like consciousness is impossible for any model, no matter how convincing they may seem. Moreover, the term “hallucination” people use to describe inaccurate output is misleading — they’re not so much hallucinating as intentionally producing incorrect answers by design simply to fulfill the query.
Researchers recently discovered that 1 cubic millimeter of the human brain contains 150 million synapses, 57,000 cells and 230 millimeters of blood vessels, totaling approximately 1.4 petabytes of data. Did you know that a typical AI holds less information than that?
Even GPT-4, one of OpenAI’s most advanced models, contains roughly 1 petabyte of data in its training dataset — 4,000 terabytes less than 1 cubic millimeter of the human brain. This is all to say that AI isn’t some superior, infallible decision-making machine. It is capable of bias and errors, so you must be careful not to give it too much freedom.
Factors That Make Human Judgement Irreplaceable
The value of human judgment in financial advising is irreplaceable. You can think critically, come up with unique solutions and don’t automatically give people the benefit of the doubt like an algorithm would. You also have emotional intelligence and complex reasoning skills — both are essential in your line of work.
Conversely, generative AI has built-in biases. It also can output erroneous answers — research shows chatbots invent data between 3% and 27% of the time — but you might not even realize. Advanced algorithms typically can’t explain how they came to the conclusion they did, meaning even minor errors can cause much more significant issues when they inadvertently replicate.
While leveraging AI in an administrative role comes with relatively few risks, you don’t want to take chances when compliance and client satisfaction are on the line. Incorporating yourself into the interpretation or review stages is essential when handling complex decisions or covering ethical considerations.
Strategies for Achieving Synergy Between the Two
While leveraging AI in financial services can drive revenue and attract clients, replacing the human element isn’t practical. An explainable model is ideal but may not be possible, depending on your circumstances. For a successful implementation, you must leverage your expertise alongside this technology.
One way to achieve synergy between you and AI is to consider value, complexity, risk and ethical considerations when determining use cases for your algorithm. Returns are important but must come second for compliance and reputation-related reasons.
Who will design the guardrails for your generative model? How will you identify and mitigate algorithmic risks? Establishing a governance framework can help you answer these questions. It enables you to set realistic limitations and inform others of your expectations. It also provides a well-documented record of accountability.
A Synergistic Relationship Requires Ongoing Effort
The recent explosion of generative artificial intelligence in financial services promises exciting developments but underscores the importance of human decision-making. You must keep yourself in the loop and occasionally readjust your strategies to ensure success.
Related: Helping Clients Finance Commercial Real Estate Acquisitions