From the automated credit decision to
the customer journey map
ML enables
interest-free installment payment options with automated approval or rejection.
Big data analyzes
provide information about profitable or unprofitable ATMs. Big data in
combination with ML can protect a financial institution today by detecting
fraud, adapting offers for each customer and increasing the security of
transactions. Big data processing systems with microservice-based architecture
enable fast and secure transaction processing. The use of ML algorithms enables
faster, more efficient and more secure credit checks. The Internet of Things
(IoT) as portion of the digital transformation can optimize customer service
processes. For example, IoT uses a customer tracking system to collect data on
the movements of customers in the store in order to create customer journey
maps and to develop and adapt its own marketing strategy. For example, a
digitized customer journey enables a customer to click on an ad, sign up for an
account online, receive tutorials and onboarding information through their app,
receive automated credit decisions and pay bills or send funds online.
Chatbots and Robo Advisors
AI in the front end is used to facilitate the identification
and authentication of customers, to connect employees via chatbots and voice
assistants, to deepen customer relationships and to provide personalized
insights and recommendations. AI technology enables precise scoring with
improved credit access and helps banks provide their customers with appropriate
debt plans. Robo-Advisors are automated platforms for financial and investment
management advice that collect information with the help of algorithms. In the
interplay of AI with cognitive systems, ML and Natural Language Processing
(NLP) , these platforms are able to submit investment proposals that are
tailored to customer expectations.
Automation technologies such as Intelligent Process
Automation (IPA) and Robotic Process Automation (RPA) help hospitals automate routine front and
back office operations such as: B. Reporting. Technologies of artificial
intelligence (AI) as Analytics collect and extract data, for example, to
health, to medicines, clinical study reports and medical records and analyze
the different data types such as clinical data, research and development data,
and medical conditions. The results of the analyzes help healthcare workers
diagnose, suggest treatments, and review prescriptions for potential errors.
Chatbots and Conversational AIimprove patient communication and revolutionize
not only the patient experience, but also internal processes. Different drugs
do not work in some patients because genetics affect the individual's drug
response. Digital twins can help in these cases by generating genetic
replacement data for a patient prior to surgery.
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