Artificial intelligence is known to be one of the most powerful tools in the field of data analytics and a 15-trillion-dollar industry, but surprisingly few companies incorporate AI into their security systems.
The spread of COVID-19 has drastically increased the number of employees working from home, particularly in cities where “non-essential” businesses were forced to close their doors.
As more employees switch to working from home, advanced conduct surveillance technology will be required to handle the increase in electronic communications and the associated risks. Artificial intelligence just so happens to be the best tool for the job.
AI and Conduct Surveillance Explained
At its simplest, artificial intelligence is software that can think like a human. At its most complex, it is the intersection of computer science, mathematics, behavioral psychology, and a long list of other industries.
Conduct surveillance is a risk management strategy that involves identifying, assessing, and controlling risk exposure. Across industries, these practices heavily involve fraud-detection systems and other security options intended to cut down on misconduct.
In the financial industry in particular, conduct surveillance is critically important; it enables investigators to monitor, track, and attack any nefarious or otherwise harmful practices of a company’s employees, covering both accidental and intentional violations of the company’s code of conduct.
With a larger headcount, however, manual conduct surveillance loses efficiency unless the team is expanded, increasing payroll obligations.
How AI and Conduct Surveillance Work Together
Working from home means an increased reliance on email, chat, and telecommunications.
Artificial intelligence uses detailed algorithms to monitor just about every aspect of employee relations, both internal and external. That includes all electronic and audio communications, employee behavioral trends, and risk identification.
While each of these three benefits can be achieved with a staff of expert conduct surveillance specialists, the amount of data generated by larger businesses can quickly overwhelm a small team, leading to the ever-increasing expansion of a firm’s conduct surveillance department. AI reduces operational expenses while handling each focus area more efficiently.
Monitor Employee Communications for Sensitive Information
Business to business, business to customer, and other business-related emails have been increasing in volume each year, growth that is projected to continue. By 2023, experts believe that there will be roughly 347 billion emails sent worldwide every day. Even if your firm accounts for less than 1 out of every 100 million emails sent, that’s still 3,470 emails per day.
It could take weeks for a conduct surveillance team to thoroughly examine only a single day’s worth of emails. However, AI can analyze the total correspondence of every employee in a fraction of the time.
The algorithms that form each model can also be tailored to monitor for each company’s specific context and domain.
Create Detailed Models to Analyze Employee Behavior
Data is the primary requirement of scientific modeling. Of course, scientific modeling is useful for more than just research. In the business world, scientific modeling can enable security teams to track transactions, monitor employee contacts, and “red-flag” employees suspected of violating the business’s code of conduct.
AI can also be programmed to compare employee data, client data, etc. with known risk factors to create a predictive model with risk profiles for each individual person. This kind of predictive modeling can cut down on costs associated with intelligence leaks, retraining, and other phenomena before they ever even happen.
Increase Risk Identification while Decreasing False Positives
AI conduct surveillance has been shown to increase risk identification rates five-fold while decreasing false positives by between 75 and 95 percent. As more people begin to work from home to stem the tide of COVID-19, increasing network traffic, better risk-identification software means less risk incurred over the long-term.
AI relies on extensive data collection, organization, and analyzation (all of which the AI can be programmed to do automatically), making it uniquely well-suited for threat identification tasks like the construction of employee profiles, quality assurance in voice recordings, future-proofing of a business’s cybersecurity portfolio.
As the economy continues to fluctuate, governments and central banks scramble to find the policy that rights the business cycle, and the COVID-19 continues to cause problems, future-proofing is a necessity.
In order to remain prepared for situations such as these, modern conduct surveillance solutions will be necessary. With decreases in revenue preventing the hiring of additional conduct surveillance professionals, AI holds the key to future-proofing this critical need.