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Why Financial Services Firms are Championing Natural Language Processing

CIO Business Intelligence

In business, when a trend is forecast to grow by more than 3000% and generate cost savings of $7.3 billion in cost savings for the insurance industry as well during the same period. . Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

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NLP Isn’t Enough. Leading Financial Services Companies Are Now Moving to Conversational AI.

CIO Business Intelligence

Today, most banks, insurance companies, and other kinds of financial services firms have deployed natural language processing (NLP) tools to address some of their customer service needs. Juniper Research forecasts that in 2023 the global operational cost savings from chatbots in banking will reach $7.3 Just starting out with analytics?

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How Financial Services and Insurance Streamline AI Initiatives with a Hybrid Data Platform

Cloudera

The way to manage this is by embedding data integration, data quality-monitoring, and other capabilities into the data platform itself , allowing financial firms to streamline these processes, and freeing them to focus on operationalizing AI solutions while promoting access to data, maintaining data quality, and ensuring compliance.

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Trusted AI Cornerstones: Key Operational Factors

DataRobot

In an earlier post, I shared the four foundations of trusted performance in AI : data quality, accuracy, robustness and stability, and speed. Industries such as banking and credit, insurance, healthcare and biomedicine, hiring and employment, and housing are often tightly regulated. Meeting Regulatory Expectations.

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Augmented Analytics: Empowering Users with Deeper Intelligence

Sisense

From data preparation , with attendant data quality assessment, to connecting to datasets and performing the analysis itself, helpful AI elements, invisibly integrated into the platform, make analysis smoother and more intuitive. A typical data science text outlining these methods is 1,000 pages of equations and algorithms.

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7 Advantages of Using Encryption Technology for Data Protection

Smart Data Collective

million penalty for violating the Health Insurance Portability and Accountability Act, more commonly known as HIPAA. If you trust the data, it’s easier to use confidently to make business decisions. Organizations receive significant fines for noncompliance. The good news is that the encryption software market is growing.

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Why Data Will Power the Self-Driving Car Revolution

Sisense

AVs of the future will require different types of storage — and lots of it — to gather data from LiDAR, radar, cameras, and other sensors as well as in-vehicle infotainment, navigation systems, and maintenance data. What if this data is also used for open warrants? For insurance company premiums? Advertising?