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Americas FSI Digital Commentary: 3 Ways to Accelerate Digital Strategy in 2023

Cisco - Contact Center

As a change agent serving the financial services industry for over 20 years, it is a great privilege to collaborate with Bank, Insurance, and Wealth Management institutions to devise and execute digital transformation strategy, solve complex business problems, and leverage technology to strengthen business results.

Banking 145
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InformedIQ automates verifications for Origence’s auto lending using machine learning

AWS Machine Learning

The solution automatically extracts data and classifies documents (for example, driver’s license, paystub, W2 form, or bank statement), providing the required fields for the consumer verifications used to determine if the lender will grant the loan. Main advantages.

APIs 72
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Create powerful self-service experiences with Amazon Lex on Talkdesk CX Cloud contact center

AWS Machine Learning

The benefits of Amazon Lex and Talkdesk CX Cloud are exemplified by WaFd Bank , a full-service commercial US bank in 200 locations and managing $20 billion in assets. The bank has invested in a digital transformation of its contact center to provide exceptional service to its clients.

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Schneider Electric leverages Retrieval Augmented LLMs on SageMaker to ensure real-time updates in their ERP systems

AWS Machine Learning

This post was co-written with Anthony Medeiros, Manager of Solutions Engineering and Architecture for North America Artificial Intelligence, and Blake Santschi, Business Intelligence Manager, from Schneider Electric. These filings are available directly on SEC EDGAR or through CorpWatch API.

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Capital One Announces Launch of DevExchange / Offers New APIs

Natalie Petouhof

They are starting something new again by becoming one of the first banks to open their platform to external developers and partners. Foundational things like: APIs that matter, are easy to integrate and are standards-based. It isn’t just about APIs, SDKs or toolkits. They are launching Capital One DevExchange.

APIs 40
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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

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Redact sensitive data from streaming data in near-real time using Amazon Comprehend and Amazon Kinesis Data Firehose

AWS Machine Learning

You previously had to rely on personally identifiable information (PII) rules engines that could flag false positives or miss data, or you had to build and maintain custom machine learning (ML) models to identify PII in your streaming data. Total cost for identifying log records with PII using ContainsPiiEntities API = $0.1

APIs 83