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October 21, 2024

OTP Bank Case Study: how to boost customer experience in banking

Chief Executive Officer

Elaine Iosifov

Commercial Retail OTP Bank offers individual customers a wide range of services, including checking and savings accounts, mortgages, personal loans, credit cards, and deposits. In retail banking, a customer’s decision to stay with the bank further and continue using its services depends on their satisfaction with the bank. This means that boosting customer experience in the banking sphere is crucial.

According to statistics, retail customers usually communicate with banks in the following ways:

  • Visiting branches in person – 15%
  • Using online banking services – 20%
  • Calling contact centers – 30%
  • Using mobile banking apps – 20%
  • Chatting with virtual assistants or chatbots – 10%
  • Sending emails – 5%
  • Engaging through social media platforms – 3%
Ender Turing Gen AI speech analytics for OTP Bank Call Center

In many ways, the OTP Bank contact center has become customers’ most common communication method. For various reasons, customers call the contact center (or contact the bank via emails, chats, or web forms). The primary objective of the contact center is to provide high access to bank services, help customers with any issues that may occur while using bank products, and generate more revenue for the organization by selling extra products and services.

The contact center serves several divisions in the bank:

1) Help Desk: customer support with the option of selling additional services;

2) Retail Banking: announcing special offers, up-sales, and cross-sales for retail customers;

3) Premium Banking: customer support and up-sales, cross-sales for key customers;

4) Debt Collection: calls to customers who are late in paying their debts;

5) Verification Department: CC serves for customer identity verification and helps prevent fraud;

6) Customer Experience: conducting customer surveys and gathering feedback.

The primary functions of the OTP Bank Contact Center

As a retail bank, OTP Bank aims to accomplish the most essential task:

Provide individual customers with various financial services while maintaining a high level of Customer Experience.

In simple terms, it means keeping customers satisfied and generating revenue.

Banks have a specific metric called “the number of financial products per customer.” The metric measures each customer’s average number of financial products or services. It helps banks understand customer engagement, cross-selling effectiveness, and overall customer relationship depth.

Why the metric The number of financial products per customer is so important for customer experience in banking:

The number of financial products per customer in OTP Bank

The recent report of Accenture says:

Globally, consumers have an average of 6.3 financial products, but only half are from their primary bank.

the stats about average percentage of financial products per customer in retail banks

Therefore, each bank’s primary task is to ensure that customers purchase as many financial products as possible within the bank. This is where a poor customer experience in banking can ruin everything.

Let’s see how Ender Turing AI Speech Analytics and QA automation have improved the CX metrics at the OTP bank contact center.

The challenges for customer experience in banking

When a person becomes a bank customer, they have long-term communication regarding their financial management. Usually, the communication is done through the CC. Here are the reasons for inbound calling:

Account Management Requests

  • Account Inquiries: Checking account balances, recent transactions, or account details.
  • Account Management: Opening or closing accounts and updating personal information.

Security and Fraud Notifications

  • Fraud Alerts: Reporting or inquiring about suspicious or unauthorized transactions.
  • Card Issues: Requesting replacement cards, reporting lost or stolen cards, card activation problems.

Loans and Credit Service

  • Loan Services: Inquiring about loan applications, status updates, or repayment details.
  • Credit Reports: Questions related to credit scores or credit report details.
  • Interest Rates: Inquiries about current interest rates for savings accounts, loans, or mortgages.

Technical Support

  • Technical Support: Assistance with online banking or mobile app issues
  • Transfer Services: Assistance with wire transfers or internal account transfers.
  • Bill Payments: Issues or questions about bill payments.

Information Requests

  • Product Information: Learning about new products or services offered by the bank.
  • Branch Information: Locating a branch or ATM or asking about branch hours.

While carrying out these tasks, contact center agents are required to meet various efficiency KPIs:

FCR should be high, the majority of customer problems should be solved on the first call.

AHT should be low, i.e., customers should not wait long for an agent to assist them.

The agent should not leave the customer hanging on the line for long to find out or check something.

If the contact center’s performance meets these conditions, it will receive a high Net Promoter Score (NPS). NPS measures customer loyalty and their likelihood of recommending the bank to others.

High NPS indicates high customer loyalty, trust in the bank, and willingness to continue cooperation. it’s really crucial metric for customer experience in banking.

A correlation has been observed: when the bank’s NPS is high, the number of bank products per customer tends to increase. Conversely, the number of bank products per customer declines when the NPS is low.

Therefore, maintaining a high NPS level is extremely important for OTP Bank, as it creates favorable conditions for successful sales and customer loyalty.

OTP Bank Ukraine is using Ender Turing AI speech analytics

Challenges in contact centers that cause low NPS/CSAT:

  • Call avoidance among agents. Because of fatigue or burnout, agents may tend to avoid calls: artificially delay the call (looking for “the right information” while a customer is on hold), stay on the line when the customer has already hung up, fail to handle customer objections during the sale over the phone, etc.
  • Lack of call categorization or its insufficiency. In banking CCs, 2 out of every 100 FTEs go to sorting and categorizing calls each year. However, this effort doesn’t lead to clear reports because agents are too busy to flip through a list of categories to choose the best match with call content. They prefer to pick the first one they come across. As a result, the bank can’t accurately understand why customers call, what they’re dissatisfied with, or what’s in high demand.
  • Manual QA leads to a mess in monitoring, missed errors, and non-compliant calls. When supervisors monitor calls manually, only 5% of random calls can be verified. So, a bank has a very fractional idea about the quality of service. At the same time, the supervisors are overloaded with QA tasks instead of doing analytics and agent coaching.
  • Lack of training as Team leads and Supervisors are overloaded with manual tasks. Usually, one supervisor cooperates with 10 to 15 agents. They do a lot of manual work: listen to conversations, evaluate them using scorecards, and provide feedback. Team leads solve challenging situations and manage the team. Training is just a distant priority for 1-to-1 once per week. According to statistics from banking CC agents’ reviews on Glassdoor, at 99% of banks, no one trains agents enough on how to work better, what financial products the bank has, and what discounts and special offers are available.

Solution for improving Customer Experience in banking

The OTP Bank contact center started to use The Ender Turing Generative AI software to analyze customer communication across all channels, including calls and chats. This is how the process was built.

Automated call categorization

If you calculate it in labor costs, approximately four thousand dollars monthly are spent for manual call categorization for every 100 agents in the US. And the managers still end up with 50 % of calls marked as “Other.”

Ender Turing makes call categorization as granular as possible, creating as many categories as a banking contact center and operations need. Thanks to the automate QA module, assigning categories to each call is automatic.

The Head of contact center gets the most detailed reports of why customers call the bank, whether they have technical issues with the bank, or seek informational and advisory support.

Call categorization at Ender Turing AI software. Picture 1.
Call categorization at Ender Turing AI software. Picture 2.

“Give your staff the opportunity to work with people and develop their communication skills, instead of wasting time on the unproductive task of manually selecting wrap-up codes.”
Dmytro Gramatik, Head of Call Center, OTP Bank

Call avoidance detection

Call avoidance might be a real curse for the customer experience in banking. Ender Turing software identifies it and shows the evidence in one click. It delves deep into each conversation’s content using neural networks.

Ender Turing is tracking specific agents’ behavior in conversations close to real-time to identify suspicious calls:

  • Average Handling Time: agents may keep customers with simple requests on the line to get as close as possible to the target AHT and, at the same time – rest.
  • Another trick with Handling Time: agents keep the line active even after a customer hangs up (to get some rest).
  • Long pauses in the conversation: Agents avoid putting the client on hold, so the telephony systems do not register any hold time. It results in a long pause in the conversation. The client is listening to silence, so Ender Turing tracks the minutes of silence in the calls.

Automated call avoidance detection helps to identify:

  • The agents who are going through the burnout stage and need immediate support;
  • The agents with a significant lack of expertise and knowledge;
  • The agents who are trying to play the system.

Monitoring and evaluation of 100% of conversations

The system monitors and analyzes all calls, chats, emails, and web forms, conducting in-depth analyses of customer conversations using the Speech Analytics Module. Unlimited scorecards and automated evaluations are available 24/7 and are done just seconds after the call is performed.

Thanks to this analysis, Ender Turing gives managers all the reasons for low CSAT in real-time. The data is detailed enough for your own research and report preparation for upper management.

Moreover, scoring 100% of calls helps to cut supervisor costs in half. From now on, the CC manager can redirect supervisor resources from manual tasks to more strategic tasks, such as focused call evaluations and feedback to agents.

Automated call monitoring with Ender Turing

Self-training module for agents to improve customer experience in banking

A self-training module allows the creation of individual learning plans, quizzes, and tests for every agent. The module includes:

  • Training plans.
  • The space to upload presentations, pdf materials, video and audio recordings.
  • The opportunity to build playlists with the best (or the worst) calls made by an agent or their colleagues.
  • Quizzes to check the agents’ level of knowledge.

Training based on real-life examples and best practices helps improve the skills of every team member without involving supervisors.

The supervisors and training department have the opportunity to create quality training materials, dedicate more time individually to each agent, especially newcomers, and update materials about new products, special offers, etc.

Determining each agent’s strengths and weaknesses allows the supervisor (or coach) to create individual Training plans in minutes.

The results of Customer Experience boost in banking:

  • Achieved a bump in First Call Resolution: from 81% to 86%
  • Service Level enhanced up to 96%
  • Abandoned Calls were reduced by 2%
  • Slashed Average Handling Time by 25%
  • FTE reduction by 34%: the OTP bank staffing needs were reduced by 6 FTEs
  • Improved NPS & CSAT scores from 47% up to 62%
The OTP Bank call center is using Ender Turing AI Speech Analytics

Related posts:

  1. How to Build a Call Center Quality Monitoring Scorecard for Your Call Center (1)
  2. Life is a Big Game, or How Call Center Gamification Can Help Your Agents (1)
  3. Top 7 CallRail Competitors in 2024 (1)
  4. Best Gong Competitors to Check Out (1)

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