The 4th generation of AI, artificial intuition, is similar to human intuition. It can be used in various industries, especially financial services. (Image Credit: pixabay)
Artificial intelligence has proven to be one of the most active technologies in the world, but it’s not entirely new. Since its inception in the 1950s, it has progressed through numerous developments. There are four generations of AI. The first one was ‘descriptive analytics,’ which addresses “what happened?” The second generation was ‘diagnostic analytics,’ answering, “Why did it happen?” The third generation is ‘predictive analytics,’ addressing, “Based on what happened, what could happen next?” Now, the 4th generation of AI has come into play, and it’s called ‘artificial intuition.’
Descriptive analytics is an initial stage of data processing, which describes raw data to produce useful information for further analysis. The 2nd generation of AI, diagnostic analysis, utilizes techniques like drill-down, data discovery, data mining, and correlations. These features have been integrated into analytics frameworks. Predictive analysis, the 3rd generation, projects what could happen next. It uses data to train machine learning models, which can come in handy for data scientists. However, it still relies on historical data to work.
Artificial intuition is similar to human intuition. It allows computers to identify threats and opportunities without being instructed on what to find. This is equivalent to how humans use intuition to make decisions without being instructed on how to do so. Artificial intuition is capable of quickly observing an entire situation, which includes well-hidden indicators of a specific activity. The concept of artificial intuition seemed impossible just five years ago. Companies like Google, Amazon and IBM are attempting to develop solutions, and a few organizations are already putting it into operation.
Artificial intuition analyzes new data without any historical context behind it. By being presented with a current dataset, the advanced algorithms can identify any correlations or anomalies between data points.
In order to process data, the artificial intuition algorithm applies the quantitative model instead of building it. The dataset is analyzed, and a contextual language is developed to represent the overall configuration of what’s being observed. This language utilizes a wide range of mathematical models, including matrices, euclidean and multidimensional space, linear equations and eigenvalues to represent the “big picture.” For example, the “big picture” could be a giant puzzle that artificial intuition is able to see from the start. It fills in information gaps to provide insight based on the interrelationships of the eigenvectors.
Artificial intuition is applicable to any industry, but it’s currently making significant progress in financial services. It’s being used by large global banks to recognize new financial cybercrime schemes, such as ATM hacking, fraud and money laundering. Financial activity that looks suspicious is typically concealed among thousands of transactions with their own set of connection parameters. Artificial intuition can quickly identify the five most significant parameters and shows them to analysts.
When analysts look at the five most important parameters and interconnections out of tens of hundreds, they can quickly identify the type of crime shown in 99.9% of cases. Artificial intuition can produce the correct type of data, distinguish the information, detect with high-accuracy and low degree of false positives. It can then present it to analysts in a way that’s easy for them to interpret.
By discovering concealed relationships between transactions that may appear normal, artificial intuition detects and notifies banks to the “unknown unknowns.” The data is presented in a way that’s traceable and logged, allowing analysts to produce enforceable suspicious activity reports for the Financial Crimes Enforcement Network.
Artificial intuition is not designed to replace human instinct. It’s meant to be used as a tool to help humans effectively perform their job.
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