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CONVERSATIONAL AI LEADING BANKING ENTITIES TO SAVE 20-30% ON OPERATIONAL COSTS:
REZO.AI

Companies
KS Aditya Rao | Manager, Ticker Team
Updated Oct 22, 2021 | 16:20 IST



TO STAY AHEAD OF THE CURVE, LEADING BANKING ORGANISATIONS ARE ACCELERATING THEIR
DIGITAL TRANSFORMATION AND CUSTOMER EXPERIENCE PLANS WITH CONVERSATIONAL AI AND
AUTOMATION.


(Representational Image)  |  Photo Credit: IANS


KEY HIGHLIGHTS

 * Conversational AI ensures no calls go unanswered with a faster resolution

 * 24x7 support resulting in lower churn rate and satisfied customers

 * Conversational AI can replace time-consuming, error-prone, costly tasks
   traditionally handled by agents in banking sector

The global conversational AI market growth is largely driven by a surge in
AI-powered customer support services demand, data centre applications adoption
and omnichannel methods’ deployment.

In today's world, customers want a tailored and more automated service
experience with less friction at every level even in their banking operations.
Conversational AI is also helping banks reduce operational costs.

A few of the factors that influence the banking operations are interpreting
customer complaints, mapping the frequency of complaints and streamlining the
processes. Conversational AI also upsells and cross-sells the relevant offers on
a real-time basis to consumers who may not be aware of it otherwise.

Here are a few excerpts of our Q&A with Rashi Gupta, Chief Data Scientist &
Co-founder, Rezo.ai:

 1. What is the role of Conversational-AI in smoothening customer support?
    Notifications/reminders enable the entire process of multiple calls to
    customers before the payments may be shortened and automated with
    conversational AI. Conversational AI ensures no calls go unanswered with a
    faster resolution and 24x7 support resulting in a lower churn rate and
    satisfied customers. It combines quality with cost-efficiency, by delivering
    appropriate first call experience with lower handling time in a fraction of
    the agent cost. While also assists the agents by automating repetitive time
    consuming, error-prone and costly processes so they can support customers’
    complex needs.
 2. Is the industry also gearing up for AI assistance for BFSI in the regional
    languages? What would be the major challenges?
    Regardless of whether the input is text or speech, language input can be
    problematic. Dialects and background sounds can have an impact on the AI's
    understanding of the raw input. Slang and unpolished language can sometimes
    cause problems when dealing with inputs. However, conversational AI-powered
    with a strong NLU engine combined with deep learning capabilities helps
    understand customer language appropriately and recognize multiple intents
    and emotions. An AI engine is built with millions of customers’ historic
    interactions and behavioural patterns, which delivers the most personalised
    experience possible. Conversational AI in today's age can seamlessly talk in
    multiple languages with a natural human voice, just like talking to a
    friend. This results in reducing the monotony of interactions and makes
    banking interactions more humane for customers.
 3. What are the security features of the chatbots being used in the BFSI
    industry?
    In the BFSI industry, fraud has been a big problem. Conversational AI offers
    appropriate and accurate results based on a deeper knowledge of consumer
    behaviour, allowing more accurate scam identification. The methods for
    masking PII data (Personally Identifiable Information Data) are highly
    encrypted and cannot be decoded. In essence, the PII data is completely
    secure, and no one has access to it.
 4. How does Conversational AI help in optimizing the workflow of a BFSI
    company?
    Personalisation: Using voice, text, email and chat-based solutions,
    Conversational AI helps banks create personalised experiences for customers
    leveraging their historic preferences and behavioural patterns while
    conversing, making customer experiences streamlined.
    Accuracy: Conversational AI is backed with a powerful Natural Language
    Processing (NLP) engine; hence it can interpret customer complaints, map the
    frequency of complaints and streamline the processes. As a result, the
    support provided by banks for customers becomes more accurate and reliable.
    Boost Revenue: Conversational AI can replace time-consuming, error-prone and
    costly tasks traditionally handled by agents in the banking sector. With AI
    tools and predictive analytics, it can upsell relevant offers on a real-time
    basis to consumers who may not be aware of it otherwise. This results in a
    highly personalised service and the potential for boosting revenue.
 5. What could be the future of Conversational AI with banking in the next five
    years?
    Banks have grown well beyond simply holding clients' funds; AI enables banks
    to give consumers different omnichannel experiences, facilitate at-scale
    personalisation and drive quick innovation cycles in order to remain
    relevant in today's environment. AI's transformation from a fascinating tool
    to an irrevocably important technology looks to be unavoidable. The banks
    will seize the unprecedented opportunity to incorporate AI into their
    operations, enhance working capital management and reduce capital costs.



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