Systems of Record are Required for Systems of Intelligence
Systems of Record are Required for Systems of Intelligence
Businesses need systems of record. Only when we have systems of record can we have systems of intelligence. And business leaders who develop systems of intelligence within their organizations will define the next frontier in their sector.
Let’s look at financial crime.
Systems of record at a bank or fund services firm can allow teams to learn about and then store info on a particular financial scam or scheme. When a bad actor attempts to repeat that scheme, the system of record recognizes it from its databank and can tell systems or people to shut down that bad actor.
But financial criminals know how banks and other institutions work. They are constantly changing their methods and schemes. It’s not enough for bankers or fund administrators to defend against the same types of crime. They must look for the same repeating patterns in their data. They need to defend against the crimes of the future. These crimes may look nothing like previous digital heists or fraudulent transactions.
The learning loop
This foresight requires a system of intelligence. AI tools should power it. These tools can run perpetual analyses on incoming data. They identify known dangers and flag suspicious “unknown unknowns.” These may indicate criminal activity. This kind of smart system helps bankers or other business leaders make breakthroughs. They do this based on the data that’s been collected. They provide foresight for what might come next using probabilities based on the system of record.
Systems of intelligence – a term coined by author Geoffrey Moore in 2017 – look deeper into transactional data to uncover the most well-hidden risks lurking within an organization. The feedback loop of finding new crimes then helps create new rules, keeping pace with the criminals while maintaining an expanding archive of their schemes.
More crime
It’s never been more important for financial firms to show they are serious about financial crime. The cost of financial crime compliance in the United States was predicted to hit almost $ 46 billion in 2022, up from more than $ 26 billion in 2019. Global financial crime costs banks north of $ 2 trillion annually.
Finance and investing firms need systems that are agile enough to confront the compliance challenges of tomorrow and take on the ever-expanding amount of work involved in financial crime and transaction monitoring. Only AI-powered solutions at this stage can deliver this level of efficiency and security.
As the Wall Street Journal’s Richard Vanderford reported, customers and regulations increasingly expect banks, funds, and others to deploy financial-crime-detecting AI systems. There’s no other way to scour billions of transactions while money launderers, human traffickers, drug dealers, and other criminals grow more sophisticated and tech-savvy daily. Vanderford cited AI proponents, saying, “AI can do the job better, require less staff, and enable continuous check-ups on customers and transactions for money-laundering issues and sanctions violations.”
From financial crime to heart attacks
To understand the power of AI-driven systems of intelligence in confronting these myriad challenges, it’s worth looking at how similar tools are revolutionizing health care – specifically preventing heart attacks.
The Semmelweis University Heart and Vascular Center in Hungary has treated thousands of patients with heart disease. They collected troves of data and images to create a patient similarity network. In short, they had a potentially powerful system of record. However unlocking the system’s potential required deploying an AI platform. The platform found patterns and delivered insights. This was achieved through a combination of topological data analysis and supervised and unsupervised learning.
The Center created a system of intelligence that is now detecting cardiovascular risk sooner, predicting patient outcomes more accurately — and saving lives.
Headcount
This example shows how a system of record is only the first step in deploying data to improve outcomes. Taking the next step allows organizations to identify recurring problems. And they do it far more effectively. They start looking ahead constantly to identify risk. During a time of staff shortages and rising demands across sectors, AI crucially allows companies to increase efficiency without increasing head counts.
More than three in four financial executives see AI-enabled risk detection driving improvements in fraud prevention over the next year, according to a recent survey. More than half see it driving advancements in credit decisions and cost savings.
Firms with a system of intelligence stand to see significant reductions on two fronts. They significantly cut costs. And they avoid the potentially crushing blow of attacks or missed opportunities.
Featured Image Credit: Provided by the Author; Thank you!
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