Financial Services

Leverage AI to Discover
and Maintain an Edge
Solution brief

Financial Services

Leverage AI to Discover
and Maintain an Edge

AI Drives Digital Transformation

McKinsey estimates that AI technologies could deliver up to $1 trillion of additional value each year in the global banking market.1Source: McKinsey, AI-bank of the future: Can banks meet the AI challenge? But financial services firms face a number of technology barriers to innovation (e.g., outdated operations, disparate data) that make it difficult to advance from AI experimentation to scaled production across the enterprise.

To stay competitive, visionary firms must become “AI-first” businesses — leveraging machine learning technologies to create and deliver personalized products and services that meet the evolving needs of modern consumers. As rising costs and reduced barriers to entry continue to apply pressure, firms must accelerate this approach to digital transformation or risk insolvency.

The Fastest Path to Competitive Innovation With AI

From customer service chat to real-time fraud detection, financial services firms seek efficient ways to integrate AI solutions into front and back-office functions. Dataflow-as-a-ServiceTM augments your institution’s AI expertise by providing a comprehensive platform, services, and models that enable you to develop and deploy state-of-the-art AI solutions without the time and expense of building complex AI architectures and hiring teams of machine learning experts.

Compliance is an ever-changing environment that’s costs can consume about 10% of a firm’s revenue. With activities that involve thousands of documents, massive volumes of disparate data, and repetitive, manual processing, current compliance processes are long, expensive, and error-prone. With its ability to process large volumes of data with speed and accuracy—AI can help financial services leaders to better understand dynamic compliance requirements, integrate policies into business units, and monitor potential incidents in real-time.

Due to the sensitive nature of the information they handle every day, financial institutions are prone to risk. AI provides an efficient means for streamlining the management of those risks. Machine learning technologies can leverage much larger and diverse data sources than what’s possible with legacy rules-based risk reporting systems—enabling real-time risk monitoring and mitigation. AI is demonstrating measurable risk impacts in credit, portfolio, market, fraud, and underwriting, etc.

Financial services firms increasingly leverage AI and machine learning to drive alpha by developing highly accurate algorithmic trading strategies for better decision-making—in less time. Utilizing AI in quantitative research enables you to incorporate larger and more diverse data sets to accelerate the discovery of new trading triggers and yield models with a higher degree of confidence.

Use Cases

Compliance

Compliance is an ever-changing environment that’s costs can consume about 10% of a firm’s revenue. With activities that involve thousands of documents, massive volumes of disparate data, and repetitive, manual processing, current compliance processes are long, expensive, and error-prone. With its ability to process large volumes of data with speed and accuracy—AI can help financial services leaders to better understand dynamic compliance requirements, integrate policies into business units, and monitor potential incidents in real-time.

Risk Mitigation

Due to the sensitive nature of the information they handle every day, financial institutions are prone to risk. AI provides an efficient means for streamlining the management of those risks. Machine learning technologies can leverage much larger and diverse data sources than what’s possible with legacy rules-based risk reporting systems—enabling real-time risk monitoring and mitigation. AI is demonstrating measurable risk impacts in credit, portfolio, market, fraud, and underwriting, etc.

Algorithmic Trading

Financial services firms increasingly leverage AI and machine learning to drive alpha by developing highly accurate algorithmic trading strategies for better decision-making—in less time. Utilizing AI in quantitative research enables you to incorporate larger and more diverse data sets to accelerate the discovery of new trading triggers and yield models with a higher degree of confidence.

Accelerated AI Solutions for Financial Services

SambaNova enables financial services companies to deliver AI solutions that scale from idea to production in weeks to reduce operating costs, accelerate time to value, mitigate risks, and modernize compliance.

DATAFLOW-AS-A-SERVICE
FOR LANGUAGE

Achieve breakthrough efficiency in NLP while you free up your machine learning talent to focus on higher-value initiatives.

DATAFLOW-AS-A-SERVICE
FOR RECOMMENDATION

Improve the accuracy of your predictions to deliver more personalized, meaningful information and content to end-users.

DATAFLOW-AS-A-SERVICE
FOR VISION

In machine learning image processing and analysis—resolution is everything. Unlock the full advantage of your high-resolution images.

Learn how SambaNova can help your institution leverage AI to competitive advantage.

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