How a Fortune 500 financial institution generated 15% risk discrimination gains with EXL

A Fortune 500 financial institution approached EXL seeking to leverage the power of bank transaction data to streamline their loan underwriting process and improve portfolio performance.


This financial institution’s primary challenge lay in extracting valuable insights from vast amounts of unstructured transaction data. This is a common issue among financial institutions. Raw transaction data is largely unstructured, making it difficult for organizations to extract insights and unlock the enormous potential of their data.

For this client, transforming raw data into actionable intelligence required the ability to create "smart variables" suitable for building a robust creditworthiness model.


EXL Transaction Insights is an advanced solution enabling financial institutions to significantly enhance their understanding of customer risks, needs, and preferences.

For this American Fortune 500 financial institution, it empowered them to unlock the hidden value within their bank transaction data.

By leveraging EXL's pre-built features and advanced text mining algorithms, the client achieved significant breakthroughs:

  • Transaction categorization: Over 90% of transactions were meticulously categorized into more than 300 distinct categories. This comprehensive classification unlocked a wealth of insights into customer spending habits and financial health.
  • Smart attribute creation: EXL Transaction Insights facilitated the generation of over 2,000 meaningful and predictive variables. These "smart attributes" provided a deeper understanding of each applicant's financial situation, enabling a more nuanced risk assessment.
  • Model development: Armed with these powerful insights, the client collaborated with EXL to build a sophisticated credit default model. This model seamlessly incorporated intelligence gleaned from bank transaction data, significantly enhancing the existing underwriting procedures.


By implementing EXL Transaction Insights, the client achieved remarkable improvements.

  • 15% improvement in risk discrimination: Measured by the Gini Index, a key metric for assessing a model's ability to differentiate between good and bad borrowers, this improvement translated to a more accurate risk assessment process.
  • ~15% increase in systematic decision rate: EXL Transaction Insights facilitated a significant shift towards data-driven decisions, leading to a more consistent and objective underwriting process.

These improvements translated into a more efficient and effective underwriting system.

The client achieved the following:

  • Systematically approve applicants with strong cash flow and stable bank accounts.
  • Decline applicants exhibiting signs of financial distress and high credit risk.
  • Verify self-declared income and tailor loan offers based on an applicant's true repayment capacity.

EXL Transaction Insights: Unlock the power of bank data

EXL Transaction Insights empowers financial institutions to unlock the hidden value within their bank transaction data. This innovative solution utilizes advanced text mining algorithms to categorize transactions, generate predictive variables, and ultimately fuel the development of powerful creditworthiness models.

As demonstrated in this case study, EXL Transaction Insights can significantly improve the underwriting process, leading to better risk discrimination, faster decisions, and, ultimately, a stronger loan portfolio.

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