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Client Profile

The client is one of the leading banks in Australia-New Zealand region and holds the position of the largest banking group in New Zealand and Pacific region. With a rich legacy of over 180 years, the client offers diverse services in retail banking, private banking, commercial banking, wealth management, and institutional banking.

The Problem

The mortgage team of the client was reliant on relevant and timely available of property data for accurate valuation and mortgage assessments. But lack of real-time access to the latest and comprehensive information on the property prices listed on different websites and other sources was creating bottlenecks for the mortgage team. Moreover, the data was coming from different sources, making the management of these vast datasets a major pain point.

  • Absence of End-to-End Data Collection: There was an evident lack of comprehensive data collection which hindered the mortgage team’s access to up-to-date and complete information on property prices from different data sources. This data was essential for accurate property valuation and mortgage assessments.
  • Error-prone Data Collection: The accuracy and reliability of the property price data was critical to make business-critical lending decisions. Any discrepancy in this data can result in severe financial risks.
  • Delayed Data Capturing: The client faced issues with efficient and timely updates on data collection as delays in capturing the property prices hindered the mortgage application process, resulting in delays for the customers.
  • Inconsistent Data: There was a lack of consistency on the data format and quality in the data collected across 11 different websites. The client required standardized data to ensure easy comparison and analysis of the property prices.
  • Need for Robust Data Security Measures: Given the sensitive nature of financial data, there was a need for strong data security measures to secure the property price data from any unauthorized access and data breaches.
  • Need for Strong Quality Assurance Process: The client required a strong data quality check and validation process in place to ensure that the collected data matches the criteria of consistency and accuracy.


Lack of a comprehensive property data collection solution

Delays in property data capturing from diverse sources

Absence of a standardized data format

No robust data security measures

Lack of data quality assurance process

The Solution

Damco’s team of data automation technology experts brainstormed and analyzed the business challenges and associated requirements and planned to utilized a cost efficient, hybrid automated data capture and reporting solution to optimize the resource utilization for the client’s team. This approach combined the power of technology, a highly skilled dedicated team, and rigorous quality checks to outperform the client’s expectations.

Resource Allocation & Shift Planning

  • Damco assembled and assigned a dedicated team of subject matter experts with strong hold on data capture, data analysis, and data quality assurance and this team ensured the optimum effectiveness of the implemented solution.
  • We further planned and implemented round the clock, multiple shifts to accelerate data collection process while minimizing the downtime.

Implementation of Robotic Process Automation

  • Our Robotic Process Automation team analyzed websites from which data was sourced and they were categorized on the basis of similarities among them.
  • The team further created a suite of specialized bots tailored to different types of websites and mobile apps to capture and extract data accurately and swiftly from these sources.

Deployment of Manual Data Capture Processes

  • The team decided to deploy manual processes for data capturing and entry into predefined templates for data from sources that cannot be automated.

Implementation of Strict Quality Control Process

  • We implemented a robust quality control process, which included performing 100% quality checks on the captured data to ensure reliability and accuracy. Any flagged discrepancy or anomaly was addressed immediately.

Establishment of a Robust Reporting Mechanism

  • We established a strong reporting mechanism through which daily and monthly summaries of captured data were shared with the client. These reports included details on the quantity, quality, and downtime faced during the data capture process.

The Benefits

Humanized automation powered data capture and reporting solution, in combination with dedicated manual efforts, helped client’s mortgage team manage huge datasets from disparate sources while making informed lending decisions swiftly and efficiently.

  • Greater Cost Savings: Significant reduction in the costs as implementation of RPA-driven automated data capture operation reduced the need of extensive manual labor, thereby improving cost savings.
  • Reduced Errors: Stringent quality checks and automated processes reduced the error margin while improving data accuracy, thus minimizing the cost associated with data correction and reconciliation.
  • Enhanced Efficiency: Significant improvement in the data collection efficiency as the automated solution not only improved the time taken to capture data, but also optimized workflows, reduced bottlenecks, and ensured smoother operations.
  • Higher Data Accuracy: Stringent quality checks and manual verifications reduced inaccuracies and errors in decision-making processes, thus resulting in higher data accuracy.
  • Greater Data Consistency: Automated processes ensured the deployment of consistent data capture methods across all data sources, leading to minimized discrepancies.
  • Ease of Scalability: The implemented RPA-powered solution was highly scalable and designed to adapt to the needs of evolving data sources and categories while handling larger volumes of datasets without any major disruptions.
  • Improved Decision-Making: Regular, detailed reporting with consistent, accurate, and complete datasets provided client with better and accurate insights, leading to more accurate and impactful strategic decisions.
  • Competitive Advantage: The automated data capture and reporting process helped client respond to market changes and customer demands in a better way while reducing operational costs, and moving the focus of employees on higher-value tasks.
data capture - success story

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