​Intelligent production support for a multinational bank
  • Case study

Intelligent production support for a multinational investment bank

How cloud and AI transformed the employee and client experience

Who we worked with

A multinational investment bank that provides financial support to governments, institutional investors, small and medium-sized businesses, and private individuals.

What the company needed

  • To boost employee productivity and reduce frustration
  • To speed up issue resolution and improve the client experience
  • To modernize and simplify its IT infrastructure

How we helped

Developed a self-learning issue resolution platform – built with AI, running on Google Cloud – for a more predictive and proactive approach.

What the company got

  • Faster issue resolution and shorter client wait times
  • A better experience for employees and clients
  • A simplified IT landscape


Reactive responses frustrate employees and clients

This investment bank was initially proud of the user experience its client-facing applications offered. But as the number of apps and users grew, the client support teams were crumbling under the pressure.

Production support teams are responsible for making sure systems and applications run smoothly. Unfortunately, the production support model was very reactive and built on siloed IT infrastructure. Issues went to one of three support teams based on the level of severity – a very manual process that required a lot of back and forth.

Overall, this production support model lowered productivity, raised operating costs, and resulted in a high mean time to recovery (MTTR) – the average time between issue detection and resolution. This frustrated employees and clients, and so the bank set its sights on modernization.


Predictive and proactive solutions powered by Google Cloud

Enquero, a Genpact company, partnered with Google Cloud to develop a self-learning production support solution for the bank, built with artificial intelligence (AI) and machine learning (ML). The goal? To predict and proactively respond to client issues.

As we built the next-gen production support application, we focused on transforming the employee and client experience. We relied on a range of Google Cloud products and solutions such as Dataproc Clusters, Cloud Storage, BigQuery, Vertex AI, Dialogflow, and Kubernetes Engine (GKE).

Today, the AI/ML engine detects potential issues based on app irregularities and usage patterns – then alerts the production support team before an issue becomes a problem. The platform solves recurring problems, prevents common challenges, and predicts future issues to completely transform how the support teams work. Clients get faster responses and even have access to a range of self-service portals, including chatbot support.


People and technology working in harmony

Now, production support is proactive and fast thanks to augmented intelligence – a seamless combination of machine intelligence and human expertise. The platform enables support teams to work more efficiently to reduce MTTR. And because they're no longer held back by tedious and manual processes, employee satisfaction is on the rise.

The user experience the bank offers its clients has also been transformed by the self-service offerings. Clients can solve minor issues with convenient self-service portals and chatbots but if an issue calls for human intervention, the expert digital apps team make sure to help resolve the issue as quickly as possible.

Overall, the bank enjoys faster issue resolution, a better employee and client experience, and a simplified IT landscape. The bank will continue its modernization journey with cloud and keep prioritizing its people well into the future.

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