Expert.ai Case Studies Smarter and Faster BNL Employees via a Semantic Search Engine and Customized Taxonomy

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	Smarter and Faster BNL Employees via a Semantic Search Engine and Customized Taxonomy Expert.ai

Smarter and Faster BNL Employees via a Semantic Search Engine and Customized Taxonomy

Expert.ai

Technology Category	Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries	Finance & Insurance
Applicable Functions	Human Resources
Use Cases	Search & Rescue
Services	Data Science Services
Challenge	BNL, a leading Italian bank, was facing a challenge with its internal support and enablement resources. The employees had to manually search for answers to their questions across numerous information sources. This process was time-consuming and inefficient. The bank wanted to establish a more efficient and reliable support process by automating their search and categorization systems. Read More
About Customer	BNL is a leading Italian bank with more than 14,000 employees. They are headquartered in Rome and are a subsidiary of the BNP Paribas Group. The bank is known for its comprehensive range of financial products and services, including retail banking, corporate banking, investment banking, asset management, and insurance. As a part of the BNP Paribas Group, BNL has a strong international presence and is committed to providing innovative solutions to meet the evolving needs of its customers. Read More
Solution	BNL partnered with Expert.ai to automate their search and categorization systems. Expert.ai provided BNL with custom taxonomy and semantic search capabilities which enabled them to understand and automatically process incoming employee requests and searches. As a result, employees were no longer forced to manually search for answers or consult the help desk for their requests. Instead, they could interact directly with the support system using natural language search terms and receive results carefully organized by a custom taxonomy. Now, when BNL employees search the internal portal for information on legislative documents, internal procedures, tutorials, data sheets, FAQs and more, the system returns the most relevant results. Read More Log in to view content
Contents

Technology Category

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Industries

Finance & Insurance

Applicable Functions

Human Resources

Use Cases

Search & Rescue

Services

Data Science Services

Challenge

BNL, a leading Italian bank, was facing a challenge with its internal support and enablement resources. The employees had to manually search for answers to their questions across numerous information sources. This process was time-consuming and inefficient. The bank wanted to establish a more efficient and reliable support process by automating their search and categorization systems.

About Customer

BNL is a leading Italian bank with more than 14,000 employees. They are headquartered in Rome and are a subsidiary of the BNP Paribas Group. The bank is known for its comprehensive range of financial products and services, including retail banking, corporate banking, investment banking, asset management, and insurance. As a part of the BNP Paribas Group, BNL has a strong international presence and is committed to providing innovative solutions to meet the evolving needs of its customers.

Solution

BNL partnered with Expert.ai to automate their search and categorization systems. Expert.ai provided BNL with custom taxonomy and semantic search capabilities which enabled them to understand and automatically process incoming employee requests and searches. As a result, employees were no longer forced to manually search for answers or consult the help desk for their requests. Instead, they could interact directly with the support system using natural language search terms and receive results carefully organized by a custom taxonomy. Now, when BNL employees search the internal portal for information on legislative documents, internal procedures, tutorials, data sheets, FAQs and more, the system returns the most relevant results.

Impact #1	Improved search accuracy via enriched content metadata
Impact #2	Significant time savings improved employee satisfaction
Impact #3	Compiled more than 8,000 FAQs and classified more than 20,000 documents using a custom taxonomy

Impact #1

Improved search accuracy via enriched content metadata

Impact #2

Significant time savings improved employee satisfaction

Impact #3

Compiled more than 8,000 FAQs and classified more than 20,000 documents using a custom taxonomy

Benefit #1	More than 8,000 FAQs compiled
Benefit #2	More than 20,000 documents classified

Benefit #1

More than 8,000 FAQs compiled

Benefit #2

More than 20,000 documents classified

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Overview

Smarter and Faster BNL Employees via a Semantic Search Engine and Customized Taxonomy

Operational Impact

Quantitative Benefit