Artificial Intelligence solutions process data and make decisions and analysis, simulating thought and decision matrices. Artificial intelligence can be applied across a myriad variety of uses, from optimizing workflow processes, automating and adapting to changing landscapes through machine learning or processing user queries and responding with relevant information. The solution uses artificial intelligence (AI), natural language understanding (NLU) and automated speech recognition (ASR) to provide virtual assistant services. The solution automates consumer queries in a humanlike manner, reducing overhead manpower costs of the firm. The solution ensures that the consumers have access to around the clock support, with predictive capabilities to offer accurate answers. The solution is able to handle high call volumes simultaneously as well in more than 80 languages, allowing firms to increase speed and quality of processing calls. Find out more at www.ey.com/sg/fintechhub. For enquiries, contact us via email at fintech@sg.ey.com.

1. Virtual (and intelligent) customer assistant
in a box
Case study
Context:
An airline company wanted to extend their
customer services online by providing virtual
assistance to customers online so as to
increase customer engagement that could
predict and answer any customer queries.
Recommended configuration:
• An online virtual assistant capable of
answering customer queries swiftly was.
Services for the customer can be improved
through the use of AI, which is used to
predict and analyze customer queries that
are raised, thus answering them as
accurately as possible.
• Additionally, the virtual assistant can
provide automated customer assistance
through the use of NLU and ASR to function
as a “real agent.” The virtual assistant is
able to answer any customer who speaks
different languages.
Client impact:
• Reduced cost on customer care with the
help of automated virtual assistance.
• Efficiently resolves a customer queries.
• Cater to a wider range of customers who
speak different languages.
• Provides a better customer experience.
Contact us
Challenges faced from providing virtual assistance
Expensive care costs for the virtual
assistant
Unable to provide the service
around the clock
Limited number of languages
available
Inaccurate speech recognition
Extended call handling duration Poor call volume management
Varun Mittal
EY Global Emerging Markets FinTech
Leader
varun.mittal@sg.ey.com
Improve services through software services
Artificial Intelligence
(AI) trained and
programmed to
recommend
predictions
Natural language
understanding (NLU)
to comprehend up to
more than 80
languages
Automated speech
recognition (ASR)
manages the call and
function similar to a
real agent
Solution benefits
Provide efficient and fast outcomes1 Ensure first call resolution2
Reduce customer care costs3 Manage call volumes4
Leading-edge tech capabilities
Data sources Data ingestion layer
Data ingestion layer Hosted on public IP
Implementation channels
Microsoft office and PDF
Core banking
database
HRMS or CRM
E-banking
system
Websites
Databases
Javascript operating system
(JSOS)
Transforms and cleanses all
structured and unstructured data
into javascript object notation
(JSON) format
Service API generated
Service deployment
Prediction engine
Cross
training
Recommendation engine
Machine
learning
Voice or
chat
training
Interactive voice
response (IVR)
Mobile app or
browser
Web chat
Virtual reality
Desktop
application
Website: www.ey.com/sg/fintechhub
Email: fintech@sg.ey.com
Sahil Gupta
EY ASEAN FinTech Manager
sahil.gupta@sg.ey.com

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