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Transforming EastWest Bank’s Operations With a Smart Data Platform

May 4, 2022 case-study data-platform artificial-intelligence gcp bigquery sql banking

Thinking Machines improved East West Banking Corporation's operations and customer experience by automating its transaction reconciliation process for 587 ATMs nationwide and streamlining 2 million monthly customer transactions leading to:

  • 33% Performance Improvement: Pre-solution, EastWest (EW) flagged an average of 750 ATM transactions per week–specifically withdrawal and deposit transactions. With Thinking Machines’ solution, this increased to 1,000 transactions.
  • 44% Fixed Cost Reduction: EW restaffed half of the reconciliation team on other tasks, boosting overall productivity.
  • 15x Turnaround Time Improvement: It takes two days maximum to alert bank customer operations to validate transaction dispute claims, versus a one-month turnaround previously.
  • A Streamlined, Proactive Approach: EW can now identify claims proactively instead of relying on customer complaints to resolve concerns.
Improved EastWest Bank’s operations and customer experience by automating its systems for 587 ATMs nationwide and streamlining 2 million monthly customer transactions. As a result, it led to 33% more transactions captured with nearly half the manpower.

Fixing a manual and error-prone reconciliation process

EastWest is one of the fastest-growing banks in the Philippines that offers financial services through a wide range of banking products and services to consumers and the middle corporate market.

There are more than 2 million customer transactions across its 587 ATMs nationwide every month. However, reconciling these ATM transactions was a manual and error-prone process, leading to significant operational challenges:

The team likened the reconciliation process to digging for needles in a haystack–a tedious and time-consuming process. With this in mind, EW requested support from Thinking Machines to build a solution that will resolve the operational holes in their existing systems and boost operational efficiency.


An integrated data platform built around a human-centered workflow to act as a single source of truth

Thinking Machines built and deployed a cloud-based data platform that integrated all the necessary information into one source. We integrated the output into a human-centered workflow that helps augment EW staff to semi-automate its ATM Cash Reconciliation processes.

Eastwest Bank simplified a tedious and manual process critical to shaping the overall customer experience with this solution. We worked with them in:


The cloud-based data platform was built with the following tools:


A streamlined, automated solution that reduces errors and accelerates the reconciliation process

“Thinking Machines has been a key partner for EastWest Bank in adopting and productionalizing AI. The “ATM Auto-Reconciliation Project”, using an Integrated Cloud Data Platform and AI to detect fraud and predict which of the bank’s ATMs are broken down has improved EastWest Bank’s operations and customer experience by automating its systems for 500+ ATMs nationwide and streamlining 2 million monthly customer transactions,” says Isabelle Yap, EastWest Bank’s Senior AVP and Executive Director.

This automated reconciliation system, on top of a cloud-based data platform, addresses the issue of data silos and facilitates seamless knowledge transfer across teams. It increased performance output by 33%, reduced costs by 44%, and improved process resolution turnaround times by 15x.

As one of EW’s first integrated cloud data solutions, this paves the way for future innovations. It serves as a precedent for other automation in the workplace that will further improve the team’s efficiency.

“Adopting AI for its bank operations has allowed our staff more time to focus on more value-adding tasks, boosting productivity. Thinking Machines’ consultative approach was critical in translating business needs into human-centered AI workflows,” Yap adds.

The tool also promotes a self-service culture for the EW’s Recon and Solutions teams. They are now able to produce analyses and reports without external assistance.

The successful implementation of the data analytics platform aligns with the company’s roadmap towards becoming a data-driven organization with leading-edge technology.

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