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AI in banking and finance transforms operations, including fraud detection, credit scoring, personalized customer service, and compliance monitoring. Proper data development practices play a crucial role in this highly regulated sector. Data scientists must ensure that AI models deliver accurate, transparent, and secure results. Proper data management and labeling practices help institutions develop models that predict risks, optimize trading, and enhance customer service without compromising compliance.
All articles on Banking & Finance
Call center AI for customer experience management: a case study
How one large financial institution used call center AI to inform customer experience management with real-time data.
August 14, 2024
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How we achieved 89% accuracy on contract question answering
A customer wanted an llm system for complex contract question answering tasks. We helped them build it—beating the baseline by 64 points.
April 2, 2024
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Here’s how Snorkel Flow + Google AI built an enterprise-ready model in a day
Google and Snorkel AI customized PaLM 2 using domain expertise and data development to improve performance by 38 F1 points in a matter of hours.
March 19, 2024
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How to scale chatbot development with Google Dialogflow and Snorkel Flow
A brief guide on how financial institutions could use Google Dialogflow with Snorkel Flow to build better chatbots for retail banking
December 12, 2023
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How AI saves money and improves banking complaint handling
Handling complaints effectively and efficiently with AI is essential to maintain customer satisfaction and protect the bank’s reputation.
August 24, 2023
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How AI and foundation models improve email surveillance for banks
Recent developments in AI tools have made email surveillance for banks better than ever. See how foundation models and Snorkel Flow can help.
August 8, 2023
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Capital One’s data-centric solutions to banking business challenges
Three experts gave a look into Capital One’s data-centric solutions to solve the bank’s business problems and improve customer experience.
May 12, 2023
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AI for banking in the era of ChatGPT
Forward-looking companies in finance, including banks, have looked to technology to meet challenges and are reaping the rewards of doing so.
April 20, 2023
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How a top 3 US bank used Snorkel Flow to automate 10-K review for their analysts
A central innovation team at a top US bank wanted to modernize its AI development and data annotation processes in order to create a custom natural language processing (NLP) model that could extract important financial information from 10-Ks. Manually reviewing these documents was taking up valuable time that could be better spent assisting customers. The team used Snorkel Flow’s data-centric AI development process and programmatic labeling to train a customized NLP model that could accurately extract information on interest rate swaps.
December 23, 2022
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Top-10 US bank uses AI/ML to triage loan documents based on risk exposure
To meet the requirements of unexpected regulatory changes brought on by the pandemic, a top-10 US bank needed to urgently adapt its underperforming model-centric artificial intelligence and machine learning development approach to a data-centric one. The team used Snorkel Flow to automatically classify thousands of loan documents and extract critical clauses in just 24 hours, saving loan managers thousands of hours of manual document review.
September 30, 2022
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10-Ks information extraction case studies
Building NLP techniques to understand 10-Ks is time-consuming, costly, and challenging. In this post, Machine Learning Engineer, Aarti Bagul discusses three information extraction case studies on how banks around the world are building highly accurate NLP applications using Snorkel Flow’s AI platform. From retail banking to hedge fund investing, NLP is used across the financial industry. By processing and extracting
July 6, 2022
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Data extraction from SEC filings (10-Ks) with Snorkel Flow
Leveraging Snorkel Flow to extract critical data from annual quarterly reports (10-Ks) Introduction It can surprise those who have never logged into EDGAR how much information is available in annual reports from public companies. You can find tactical details like the names of senior leadership, top shareholders, and more strategic information like earnings, risk factors, and the company strategy and vision. Warren
May 10, 2022
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