Everyone is talking about AI. Forward-thinking businesses – from startups to conglomerates – are looking into the technology to understand how AI can benefit their operations, processes, and employees. Senior leaders in AML compliance and fraud are actively exploring the multitude of enterprise AI use cases to capitalize on cost savings, accuracy, enhanced productivity, and ultimately, enhanced financial crime prevention. So, what does this mean for employees ?
Is AI taking jobs or improving worker efficiency?
Early -adopters of AI are beginning to track metrics on operational benefits and the impacts on employees’ role function and effectiveness. Answers to questions such as ‘how will AI benefit employees?’, ‘how can AI augment what we do to deliver better outcomes’, and ‘what new roles will we need because of AI’s use in our organization?’ are all being carefully considered.
In AML compliance and fraud functions, results from the combined use of predictive and generative AI show:
- greater efficiency and effectiveness in employees’ overall standard of investigation and risk profiling activities
- time savings in performing manual and repeatable tasks
- previously hidden risky connections, behaviors, patterns, and profiles that are not easily seen or relatable by individual analysts and investigators
- faster highlighting of risks and new threats in this ever-changing landscape.
AI use is growing in business
In less than a year, driven by public curiosity and entrepreneurial development of new usage scenarios, interest in enterprise generative AI is thriving . Fast forward to now, and the possible use cases are broadening ten-fold while AI capabilities have grown exponentially.
Accenture reports that almost 75% of companies consulted have integrated AI into their business strategies, and 42% said the return on these initiatives is exceeding expectations. Interestingly, only 1% said otherwise.
Predictive AI use at an enterprise level is growing rapidly. Using advanced algorithms that analyze historical data patterns and existing information, it forecasts outcomes that predict market trends, customer preferences, and any other relevant insights to an industry.
Going forward, generative AI will do much of the heavy lifting . Forrester suggests that its use will see it capturing 55% of the AI software market by 2030, translating to an annual average growth rate of 36%.
Bearing all this in mind, will AI soon take jobs? Has it already?
AI will take some jobs
Automation, industrialization, and technology have been critical catalysts for job losses in decades past. From newspaper linotype typesetters, lamplighters, and coal miners to, more recently, local news losing out to online journalism, video rental stores losing out to streaming, and bank branch closures due to numerous online services. The examples are numerous, and the impacts are understood in retrospect.
With innovation, there will always be job losses and it would be unreasonable to assume that AI won’t take any jobs. Goldman Sachs predicts that ChatGPT will impact 300 million positions worldwide across multiple divisions. IBM will slow or suspend hiring for back-office positions that AI can do. Across front-to-back-office functions in financial services, such as AML compliance and fraud, Goldman Sachs speculates that as many as 35% of work tasks could be automated by AI in the face of exploding workloads that cannot keep pace with staffing and cost levels, the fifth largest area in their research.
Other positions, in human resources, media, and legal, are currently predicted to be most at risk, while a broad category – administrative, non-customer-facing roles – is also likely to diminish in the coming years. And with the implementation of AI in anti-financial crime, it’s likely that the automation of some aspects of level 1 investigations will also lead to job losses.
But that isn’t the full story.
AI will enhance current jobs
The most overwhelming influence of enterprise AI is how it enhances current jobs, making employees better in their roles. This is already being seen in digital, research-based, and educational roles.
For example, designers and copywriters may use AI as a starting point in projects, helping them to brainstorm, refine, or edit projects to give a more human touch that brings authenticity to an advert. In education, onboarding is seeing automation as is report grading and offering feedback. This allows teachers to spend time helping those who need it most, while still fulfilling their other duties.
In research-based roles, such as level 1 investigations in anti-financial crime, there is no room for error. Digital assistants are of particular benefit here. For example, technology like the Sensa Copilot, a generative AI assistant, improves efficiency and effectiveness of case investigations carried out by analysts and investigators.
Though some teams may become smaller, for the remaining employees, AI will improve their output and make research easier – analyzing patterns, spotting correlations, etc. Instead of wasting time on false positives, human expertise will be focused on investigating genuine risk. A human element will always be needed to ensure these findings are correct and to allow for transparency and a lack of bias in reporting.
AI will create more jobs than are lost
Looking back at technology innovations in history, great advancements alter how resources are used, how hiring happens and how skill sets change to adapt to new ways of working. The evolution of AI in business is no exception to this age-old trend.
For example, spreadsheets began appearing in the 1970s and the rise of Lotus 1-2-3 and Microsoft Excel helped them grow in the late 1980s and beyond to become standard software.
Although some bookkeeping jobs were lost in the accounting department because of the rise of Excel, many more were made. According to Morgan Stanley, between 1987 and 2000, there were 500,000 fewer bookkeepers in the US.
However, the number of accountants and auditors rose by 200,000, and management analysts and financial managers grew by 900,000 in the same period. The decline in one area was more than offset by the increase in adjacent positions.
The same can be seen with the introduction of the automated teller machine (ATM). Though some predicted the demise of the bank teller, ATMs resulted in branch operation costs decreasing, and demand for bank branches increasing.
The rise of AI in enterprises will likely see many people move into other areas of financial crime and risk management; human involvement will still be critical to key decision making as adjudication skills and contextual knowledge remains essential. Alongside this, demand for data scientists and quality and control analysts for governance of AI models will increase and become the norm.
Retraining may be necessary – but AI opens up numerous opportunities for supporting training too.
The numbers don’t always tell the full story – for example it’s hard to know how many bookkeepers became financial managers between 1987 and 2000. It is likely that some were unable to retrain and left the industry. However, opportunities arose for many to become experts with spreadsheet software, enhancing their skillset, improving their job prospects, and leading to higher earnings potential.
The same may be true for the rise in predictive and generative AI. While AI is a tool that can dramatically increase productivity within the workforce, overall it cannot work in isolation (though some autonomous operations are on the very distant horizon). AI’s power is guided by the hands that use them.
Ultimately, AI brings benefits to the working world, the most prominent being:
- Automating repetitive or manual tasks, enhancing productivity of workers to focus on more important duties
- Embedding learning opportunities throughout the workday
- Reskilling or upskilling
- Teaching new workers via adaptive, personalized learning
- Enabling the development of previously unachievable or expensive programs (personalized medicines, precision farming, etc.)
- Innovation leading to the creation of many new sectors and job opportunities
The Sensa-NetReveal Investigation Hub example
An example of this can be seen in Symphony AI Sensa-NetReveal’s Sensa Investigation Hub.
Within the software, investigators benefit from an AI-generated narrative of an investigation so far. This summary helpfully explains who the subject is and why an account has been flagged, highlighting key transactions and amounts.
Investigators can use the Sensa Copilot to delve deeper. Often this can be queries such as ‘find all transactions for 2023’ and then following that up with asking for the average from specific months, for example. There is no need to comb through the data as the Copilot highlights the information requested. It’s a little like using a more advanced version of ctrl+f to find a specific word or phrase in a multipage document but on a larger scale across internal data sources and any parameters.
Once questionable transactions have been identified, investigators can choose to add them to the case’s narrative summary. They can also add relevant information like recent articles mentioning the subject, and useful files or notes for subsequent investigators to follow up with. Once this is done, the investigator can generate and edit a full AI narrative of their investigation, with all procedures that have taken place helpfully listed in the event log.
The software is easy to learn but requires an adjustment for investigators that may not be accustomed to such tools.
Conclusion
The use of predictive and generative enterprise AI to assist employees can be seen across all industries, including financial services, AML compliance and fraud, healthcare, retail, media, and many more. Although AI won’t replace most workers, it will require some adaptation in the skills workers require.
In financial services, the AI benefits are clear, as is the expected roadmap that AI use will take. It is already being used across the financial sector, and with AI use increasing, these developments will only become more powerful.
With global AI private investment at $91.9 billion in 2022, an increase of 18x since 2013, AI is here to stay. Every day, companies are finding new ways to use predictive and generative AI in ways that have never previously been imagined. As such, it is fair to conclude that AI will, for the most part, make people better at their jobs while also creating new areas of work to allow people to excel.
