CASE STUDY

NATURAL LANGUAGE PROCESSING

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Key Highlights

Early Information & Reduced Latency

Fast, accurate and optimized data; Retrieval in quick time

Flexibility/ Scalability

Customizable algorithms and functions; Scalable model

Lower Costs

Better operational efficiency, lower operational costs

Reduced Model Risks

NLP techniques provides excellent insights enabling businesses to make informed decisions

Challenge

A leading Asset Management firm encountered significant delays in retrieving large volumes of trade/securities information available from public sources. The data was unstructured and lacking accuracy, making it unusable. Our solution would need to provide powerful and advanced techniques to extract usable data for research and analysis with a focus on swiftness.

NuSolution

    NuWare’s NLP experts proposed the following solution:

    • Implement SpaCy’s framework/statistically modeled NLP algorithm to extract, tokenize, tag, detect entities and parse data from unstructured information making it available in a structured format, real-time
    • Use intuitive technologies in the NLP environment such as Python, using spaCy & NLTK frameworks that allows scalability and flexibility to customize algorithms based on current business scenarios
    • Create and manage own data store for trade and securities information

Results

Use of NLP techniques created a positive business impact by reducing overall latency, optimizing business operations, and lowering costs significantly. NLP techniques hold promise by helping the business contain model risks thereby enabling business users to make important decisions accurately and quickly.