June 24, 2022

Email Automation Use Cases for Efficient Customer Support in Banking

This article will primarily focus on how the use of an AI enabled Mail Bot can boost operational efficiency and productivity, bringing a profound sense of customer satisfaction and loyalty by automation of customer support email responses.

Meeting customer expectations is one of the most essential issues for the banking sector post digitalization. A great CRM is now more critical than ever before. The prevalence of customer relationship management is imperative for a tailored approach towards customer data, personalized outreach at scale, and proactive insight to keep up with the competition. CRM helps the banking sector to build a customer-centric business model to deliver effective and fast digital engagements. The CRM is significant for reducing loads of the bankers by helping them collect and streamline data for better customer engagement thus helping in strengthening customer relationships.

AI Integration in the CRM

Artificial intelligence is almost omnipresent across the post-modern world. AI algorithms make human lives easier with a seamless human and machine synergy. The significance of providing better customer service can profoundly guide the business in the banking sector to boost the decision-making process. As per a McKinsey report, 75% of online customers expect a response within 5 minutes of their approach. Thus, in order to drive real-time data-driven business decisions, AI integration in customer relationship management is ushering a newfound sense of innovation for more efficient data management. As per a report in Forbes, less than 0.5% of all data can be appropriately analyzed and used. Thus adopting AI technology in the CRM of the banking sector is imperative for an enhanced customer experience at each node of the sales funnel. Banking, now more than ever, is driven by customers and a research by Bain & Co proves that customers are 4 times more likely to buy from a competitor if the problem is related to service than the product.

This article will primarily focus on how the use of an AI enabled Mail Bot can boost operational efficiency and productivity, bringing a profound sense of customer satisfaction and loyalty by automation of customer support email responses. The results are multifold, from reduced human errors, fraud detection, efficient resource allocation, identifying patterns from past decisions to making workers more productive.

Stereotypical email responses and the problems with manual response management:

Less Output Value and High Input Time for Repetitive Tasks:

From manual data entry to updating the CRM, responding to repetitive customer queries via email, more than 80% of the tasks can be automated, allowing more work to be completed in less time. The operations team can thus utilize their time in more constructive higher-quality work. As per Microsoft’s State of Global Customer Service report, 51% of all customers feel that most brands do not take action on customer feedback.


High Turnaround Time (TAT):

Without automation, human efforts can be overwhelmingly time consuming, especially with backlog of emails during peak seasons. A McKinsey report suggests that 75% of online customers expect help within 5 minutes, and 60% Customers expect the same standards even in non-working hours. Automation of repetitive queries brings down the TAT by more than 90%, resulting in more satisfied and loyal customers.


Human Error:

Increased dependency on manual response management runs the risk of human error and poor quality of communication. Automation ensures constituent quality with better than human accuracy.


Operational Inefficiency:

The constant attrition of agents coupled with seasonal volume fluctuations causes an operational havoc within contact centres. This compromises productivity by increasing the duration of the learning curve, also incurring a huge cost on the training of new agents.


Email Automation in Banking


A growing number of customers choose email as a channel for communication, thus emerging as the most preferred digital platform for customer service. Email automation using a mail bot automates mundane and repetitive tasks leaving more time for agents to handle complex queries.


MailERA is a self learning, out of the box email automation tool pre-trained on customer support queries for the Banking industry. With several implementations across the BFSI sector, MailERA is the predominant domain expert to drive automation in banking customer experience.


How MailERA Transforming the CRM through Email Automation


The application of email automation as a technological capability renders renewed opportunities to achieve business goals. MailERA’s deep Learning capabilities combined with robotic process automation, natural language processing, and machine learning algorithms provide a delightful omnichannel customer experience.


MailERA is an intuitive platform that connects the mailbox with your CRM to automate responses to customer queries. It scans through emails, processes content, automatically tags emails into predefined buckets, extracts relevant information from the email and validates the same with the CRM in order to draft automated responses with minimal human effort.


Banking Use Cases Running in Automation Mode


Complete automation has been achieved in some of the most repetitive, mundane, and time-consuming use cases that occupy the highest bulk of incoming email in a banking CRM. Some of the many use cases that have undergone complete automation with MailERA’s Deep Learning based automation are:


KYC Status

MailERA uses NLP to identify emails of customers requesting for their KYC status. Using APIs, it fetches the required information and addresses the request instantly, using customised response templates.


Offers Reading Cash Back

MailERA reads and understands the query and communicates with the database to quickly draft relevant Applicable offers.


Queries Regarding the transaction

MailERA addresses such repetitive queries seamlessly to provide instant relief to the customer seeking reasons for the freezing of their transactions such as

Credit Freeze

Debit Freeze


Explanation of Various Charges

Banking includes subsequent explanation of various charges incurred by the customers such as alerts charges, debit card charges, POS charges, cheque book charges, NB pin charges. MailERA quickly gathers the correct information from the CRM, verifies the customer’s inputs, and automatically reverts with a comprehensive explanation behind the charges in less than 5 minutes, without involving human intervention.


Request for Static Data Updation

Customers often request to change or update basic KYC related information such as email ID, mobile number, PAN number, Aadhaar Number etc. MailERA automates this process by capturing the information provided by the customer and verifies it with the supporting documents attached in the email using its proprietary OCR tool to quicken the process and avoid the risk of fraud.


Some other repetitive banking queries that have benefitted from Automation are:

Account Statement Requests

Transaction Status Requests

Unable to carry out Transactions requests etc.


Conclusion

MailERA’s advanced NLP capabilities combined with deep learning technology identifies and decodes intents from the email body using a unique pattern-based recognition approach. It further categories and tags emails with more than 90% accuracy. It is a complete end-to-end platform that can fetch, extract and update the information in the CRM from the e-mail, and can generate tickets through the CRM when needed. What’s more, with immense domain expertise with several implementations in the banking sector, MailERA is now available as an “Out of the box” tool that can be trained in-house, and tailored to fit customised requirements without the need to share sensitive data outside the organisation’s premise. An AI powered tool that trains itself using data limited to the walls your organisation. What more could you look out for!

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