Remove Business Intelligence Remove Fintech Remove Innovation Remove Machine Learning
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Piramal CTO Saurabh Mittal on financial services innovation

CIO

To create innovative products that meet the various finance requirements of the market, Piramal Capital & Housing Finance opened the Piramal Innovation Lab in Bengaluru on Dec. CIO.com caught up with Mittal to know more about his plans for the innovation lab, as well as the technology strategy for the financial services company.

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Financial services firms turn to automated, data-driven processes for new products and services

CIO

Between the host of regulations introduced in the wake of the 2009 subprime mortgage crisis, the emergence of thousands of fintech startups, and shifting consumer preferences for digital payments banking, financial services companies have had plenty of change to contend with over the past decade.

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Harmonic helps investors query the startup searches of their wildest dreams

TechCrunch

Siri, show me fintech companies, founded in the last two years, that haven’t raised over the past year but have grown headcount by 100% in the same time frame; and can it be founded by Stanford alumni whose Twitter traction has grown by at least 50% in the last six months? Floodgate, another customer, was Harmonic’s first investor.

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Intelligenza artificiale e gen AI: i quattro elementi per passare al “next level”

CIO

L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%). Le reti neurali sono il modello di machine learning più utilizzato oggi.

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Software Development for Financial Services: Technologies, Trends, Challenges, and Best Practices

Existek

The financial services industry is one of the most heavily regulated and complex sectors, and software development is critical in driving innovation and growth within it. One of the key trends driving innovation in the financial services industry is using technology to drive growth.

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What is AI Analytics for Different Industries?

Existek

AI technologies like machine learning, NLP, and computer vision have become reasonable approaches to complement existing analytical approaches. In other words, artificial intelligence actually complements traditional analytics and co-exists with it. Besides, it supports valuable insights for long-term strategic planning.

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Data Science use cases & tools

Apiumhub

Machine Learning. Machine learning is the backbone of data science. Using machine learning, predictive analytics and data science, self-driving cars can adjust to speed limits, avoid dangerous lane changes and even take passengers on the quickest route. . Scoring and ranking (e.g., FICO score). Healthcare.

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