Helping Financial Services Tackle the Challenges of Unstructured Data

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swirl of endless blue representing unstructured data

Today, large enterprises are grappling with an onslaught of unstructured data and documents. IDC and Seagate predict that the global data sphere will grow to 163 zettabytes by 2025, and about 80 percent of that will be unstructured. In regulated industries, such as financial services, the challenges posed by unstructured and semi-structured data are exponentially higher.

Drawbacks of traditional technology

Traditional methods–ranging from manual entry to Optical Character Recognition (OCR)–have proved woefully inadequate. Even more recent and highly heralded methods such as Robotic Process Automation (RPA) have proven to be piecemeal solutions to the challenge. What is necessary is a more resilient and adaptable approach to extracting business data from unstructured documents. Natural Language Processing (NLP) emerged to address this gap.

NLP is a machine learning method that deals with analyzing and making sense of text from unstructured sources. Unfortunately, most NLP platforms are generic, one-size-fits-all solutions. Their lack of domain knowledge and industry-specific terminology diminishes their value.

The alternative solution

After a couple of generations of NLP solutions attempting to address the challenges, the founding team at nRoad identified the shortcomings of existing approaches and embarked on a solution that incorporated domain and language models specific to the financial services industry. The result was Convus™, an AI-powered, domain-led NLP platform for processing unstructured content in financial services–at scale and precision.

Convus is purpose-built with a patent-pending technology framework that leverages deep learning techniques. The framework enables companies to mine and extract actionable insights from structured and unstructured data sources with a low training burden.

Small footprint, bigger impact

Unlike generic NLP frameworks and engines, Convus focuses on domain infusion and the ability to deal with the structural nuances of various documents, including nested tables. In addition, the platform requires minimum training samples, enables faster deployment, and is built on a microservices-based architecture that can integrate with existing IT infrastructure in a non-intrusive way while maintaining the security of data needed.

The platform has proven its capabilities to some of the largest FinTech players, asset management firms, and financial data providers, including:

  • Allows financial institutions to extract, normalize, and incorporate critical business information buried in unstructured documents into mission-critical business processes.
  • Offers a purpose-built enterprise-grade platform that delivers scale, accuracy, and efficiency with minimal training burden.
  • Reduces costs and avoids manual data extraction and entry; deep learning models adapt to changing document formats and structure.

Financial services firms cannot leave behind 85 percent of their data. With Convus, they have an opportunity to incorporate valuable information and insights from unstructured sources into mission-critical business flows.

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