Today, analytics help organizations establish trends, discover opportunities, and predict
events or actions. While data analysis refers to reviewing data from past events for patterns;
or trends, predictive analytics makes assumptions and testing on past data to produce future
"what if" scenarios to help predict what will happen next, or to suggest actions to take for
optimal outcomes.
Analytics relies on the application of statistics, computer programming, and operations
research to quantify and gain insight into the meanings of data.
Artificial Intelligence
Artificial intelligence applies advanced analysis and logic-based techniques to interpret
events, support and automate decisions, and take actions; AI applies different technologies
working together to enable machines to sense, comprehend, act, and learn with human-like
levels of intelligence.
In short, AI's focus is to create human-like abilities performing tasks that would normally
require human abilities. It can self-correct, understand and learn. More importantly, AI
analyzes data, makes assumptions, learns, and provides predictions at a scale and depth of
detail that is impossible for individual human analysts.
Today, AI takes many forms. It is used in a variety of applications such as:
Speech Recognition
These AI utilize natural
language processing
(NLO) to transform
human speech into a
written format.
Applications include
transcription and
speech-to-text
translation.
Virtual Agents
Known also as
Chatbots, they replace
human agents with a
computer-assisted
customer journey --
one that can help
answer frequently
asked questions or
provide simple,
personalized advice.
Recommendation
Engines
Engine algorithms are
designed to effectively
used by companies like
Amazon, AI algorithms
utilize data trends to
make purchase
recommendations to
customers.
THE NEW RISK MANAGEMENT | 9
