Transforming EastWest Bank’s Operations With a Smart Data Platform
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.
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:
- Upon receiving a customer complaint, the average turnaround time was one month to validate claims.
- Bank analysts had to dig through thousands of transactions for validation processes,
in which they were only able to negotiate 60% at any point. Poor customer experience was a recurring challenge as most errors were solved reactively due to customer complaints.
- The manual process ran the risk of revenue loss on ATM transactions.
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:
- Automating data pipelines from their on-prem systems to leverage the power of Google Cloud Platform’s BigQuery. We also developed parsers to work with unstructured (pure-text) transaction data from their ATMs so that their SQL analysts can process their ATM transaction information automatically and simplify the process of matching and validating transactions.
- Developing Google Data Studio dashboards to streamline the process of hunting down data across siloed sources. These dashboards also automatically and proactively flagged suspicious or erroneous transactions for investigation.
- Building automated and customizable reporting functions to simplify reporting processes for the bank’s management teams. The Recon and Customer Service Teams have access to this 24/7 to reduce inter-team communications and resolve customer complaints quickly. The key features include management reporting summary, custom reporting via filters and metadata, transaction details, and downloadable reports.
The cloud-based data platform was built with the following tools:
- Google Cloud Storage: a provider of computing resources for developing, deploying, and operating applications on the Web.
- Google Cloud Composer: a managed workflow automation tool that authors, schedules, and monitors software development pipelines across clouds and on-premise data centers.
- Google Big Query: a big data analytics web service for processing very large read-only data sets. It helps manage and analyze data using built-in features such as machine learning, geospatial analysis, and business intelligence.
- Google Data Studio: a reporting solution that turns data into informative, easy to read, easy to share, and fully customizable dashboards and reports.
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.
- An increase in performance output by 33%: EW increased their weekly average transactions reconciled with 33% to 1000 transactions.
- Reduced fixed costs by 44%: EW reallocated the workforce efficiently. The ATM Cash Reconciliation analysts could refocus their time on more productive tasks.
- A proactive approach in identifying claims: EW is no longer reliant on customers complaints to trigger branch operations to resolve concerns.
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.