Retail and Corporate Banking

Transforming Customer Experience, and a 30% enhancement in NPS for Asia’s Largest Private Bank with Scout

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The Challenge

Asia’s largest private retail bank, with over 8,000 branches and 150,000 employees, was at a crossroads. Faced with fierce competition from digital-first banks, it struggled with missed customer service level agreements (SLAs), high operating costs, and an outdated customer experience framework.

The bank handled nearly 10 million customer requests annually, with a significant portion—70% of customer instructions like address changes, contact updates, and new chequebook issuances—being processed manually through its extensive branch network. This not only strained the bank’s resources but also jeopardized its reputation for customer service excellence.

Industry

Retail and Corporate Banking

Location

APAC

150,000

Employees

8,000

Employees

Attempted Solution before Scout

Demanded approximately

3,000 hours

to conduct in-depth discovery workshops and interviews

The bank’s leadership initiated a digital transformation effort, aiming to overhaul its customer service operations. This included partnering with a Systems Integrator (SI) and deploying traditional process mining tools, which ultimately failed to capture the complete picture of the bank’s operational inefficiencies.
Furthermore, attempts to conduct in-depth discovery workshops and interviews to understand team workflows demanded approximately 3,000 hours from the business teams, exacerbating their workload and leading to increased stress and attrition among the staff.

Enter

In search of a more effective solution, the bank’s Head of Digital Strategy and Banking Operations decided to implement Scout, to find and fix this problem within their Central Processing team.

This team was responsible for managing the bulk of the customer service requests, numbering around 1 million annually. Scout’s deployment was swift and seamless, requiring no intricate integration with the bank’s existing systems and fully adhering to the strictest data security and privacy standards.

Within just

2 weeks

of deployment Scout's analysis unearthed several critical insights

Scout’s AI to “find and fix”

Scout’s AI to “find and fix”

Step 1: Find

Scout’s analysis unearthed several critical insights within just two weeks of deployment:

A significant discovery was that 80% of branch requests were not related to debit cards, indicating a potential area for enhancing digital self-service options.

Another alarming issue was that 70% of the requests handled by the central processing unit were placed on hold due to incomplete or incorrect information from the branches.

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The analysis also showed that the team spent about 30% of their time toggling between the core banking application and the document tracking system, leading to inefficiencies and delays. This startling statistic pointed to a massive work recall gap across the team, highlighting the disparity between the team’s understanding of how work is being done and how work was actually being done.

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Step 2: Fix

Armed with Scout’s insights, the bank swiftly implemented several quick and deep fixes:

Quick Fixes

Enhancements to the net banking and mobile app interfaces for non-debit card related services were rolled out

Increased marketing
efforts to promote digital channel usage

Enhancements to the net banking and mobile app interfaces for non-debit card related services were rolled out

Deep Fixes

The bank initiated a project to integrate the core banking system with the form tracking system, reducing the need for manual toggling and to reduce the disconnection debt. It also developed a combined cognitive automation and OCR-based solution for the service request workflow, significantly improving straight-through processing rates.

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It is important to note that in all of these recommendations, privacy was of the utmost importance – and no employee data was shared. Empathy was at the core of all recommendations and the focus was on addressing and improving the core issues i.e.

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Business outcomes

In summary Scout was able to drive the following business outcomes

30%

improvement in end-customer NPS

20%

reduction in operational costs, streamlining the bank's expenses

80%

improvement in straight-through processing of customer instructions, demonstrating the efficiency gains from the implemented solutions.

AI connects interaction data to business outcomes

Scout lights up the ‘dark side of the moon’.

Your business generates billions of data points from team-machine interactions. Scout, our AI model, deciphers this interaction data to reveal what often remains unseen—the hidden challenges your teams face at work and how they affect business outcomes, whether it's cost optimization, revenue growth, customer or employee experience, or business continuity.

The AI then provides data-based recommendations to address these challenges, paving the way for improved outcomes.
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