Case Studies Top U.S. bank uses Snorkel Flow for Rapid AI application Development

Edit This Case Study Record

	Top U.S. bank uses Snorkel Flow for Rapid AI application Development

Top U.S. bank uses Snorkel Flow for Rapid AI application Development

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation
Services	Software Design & Engineering Services System Integration
Challenge	The bank faced a significant challenge in processing a large volume of documents for a time-sensitive use case. Hand-labeling the data required for this task was estimated to take over a month, which was not feasible given the urgency of the situation. The bank needed a solution that could expedite the data labeling process and enable the rapid development of AI applications to classify and extract information from their documents. Read More
About Customer	The customer is a top U.S. bank, a major financial institution with a large-scale operation. The bank deals with a vast amount of documents daily, requiring efficient and accurate processing to maintain operational efficiency and compliance. As a leading player in the finance and insurance industry, the bank continuously seeks innovative solutions to enhance its business operations and customer service. The bank's commitment to leveraging advanced technologies like AI and machine learning underscores its dedication to staying at the forefront of digital transformation in the financial sector. Read More
Solution	To address the challenge, the bank implemented Snorkel Flow, an AI platform designed to streamline the development of machine learning models. Snorkel Flow enabled the bank to quickly build AI applications that could classify and extract information from their documents. The platform's ability to automate the data labeling process significantly reduced the time required to prepare the data for model training. This allowed the bank to develop and deploy AI applications in a fraction of the time it would have taken using traditional methods. The flexibility of Snorkel Flow also meant that the resulting AI applications could be easily adapted to new problems and business lines, providing a scalable solution for the bank's diverse needs. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Services

Software Design & Engineering Services

System Integration

Challenge

The bank faced a significant challenge in processing a large volume of documents for a time-sensitive use case. Hand-labeling the data required for this task was estimated to take over a month, which was not feasible given the urgency of the situation. The bank needed a solution that could expedite the data labeling process and enable the rapid development of AI applications to classify and extract information from their documents.

About Customer

The customer is a top U.S. bank, a major financial institution with a large-scale operation. The bank deals with a vast amount of documents daily, requiring efficient and accurate processing to maintain operational efficiency and compliance. As a leading player in the finance and insurance industry, the bank continuously seeks innovative solutions to enhance its business operations and customer service. The bank's commitment to leveraging advanced technologies like AI and machine learning underscores its dedication to staying at the forefront of digital transformation in the financial sector.

Solution

To address the challenge, the bank implemented Snorkel Flow, an AI platform designed to streamline the development of machine learning models. Snorkel Flow enabled the bank to quickly build AI applications that could classify and extract information from their documents. The platform's ability to automate the data labeling process significantly reduced the time required to prepare the data for model training. This allowed the bank to develop and deploy AI applications in a fraction of the time it would have taken using traditional methods. The flexibility of Snorkel Flow also meant that the resulting AI applications could be easily adapted to new problems and business lines, providing a scalable solution for the bank's diverse needs.

Impact #1	The AI application developed using Snorkel Flow could be quickly and easily adapted to new problems and business lines, enhancing the bank's operational flexibility.
Impact #2	The implementation of Snorkel Flow significantly reduced the time required for data labeling, enabling faster development and deployment of AI applications.
Impact #3	The bank was able to process a large volume of documents efficiently, improving overall productivity and operational efficiency.

Impact #1

The AI application developed using Snorkel Flow could be quickly and easily adapted to new problems and business lines, enhancing the bank's operational flexibility.

Impact #2

The implementation of Snorkel Flow significantly reduced the time required for data labeling, enabling faster development and deployment of AI applications.

Impact #3

The bank was able to process a large volume of documents efficiently, improving overall productivity and operational efficiency.

Benefit #1	99.1% Snorkel Flow accuracy
Benefit #2	<24hrs from problem start
Benefit #3	>250K documents processed

Benefit #1

99.1% Snorkel Flow accuracy

Benefit #2

<24hrs from problem start

Benefit #3

>250K documents processed

Download PDF Version

Overview

Top U.S. bank uses Snorkel Flow for Rapid AI application Development

Operational Impact

Quantitative Benefit