Allowance for Loan and Lease Loss: Organizing Data & Analytics for Success

The biggest challenge banks face in computing ALLL is gathering data from disparate sources or spreadsheets through manually-intensive, error-prone, and timeconsuming processes. All too often, ALLL production demands an excessive effort from bank staff—requiring 80-hour work weeks. Teradata and Fuzzy Logix can help banks greatly improve the efficiency, accuracy, and regulatory compliance of their methodology. By organizing the bank’s ALLL data in a central repository with embedded analytics, they can enhance the quality, consistency, and timeliness of their calculations.

Spotlight

Paradata

Paradata addresses supply chain inefficiencies by providing current and verifiable component data to optimize product design and manufacturing. Paradata's machine learning engine classifies and ranks public and private data to deliver components that fit customers' specific product needs. This increased transparency into their global supply chains delivers efficiency and cost savings.

OTHER WHITEPAPERS
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The Inevitability of Data Science Modernization During the Machine Learning and AI Revolution

whitePaper | June 16, 2022

It seems like the business world has gone crazy for machine learning (ML) and artificial intelligence (AI), viewing the technologies as the essential keys to the very future of the enterprise. In fact, a recent survey from ESIThoughtLab found that two-thirds of business leaders see AI as critically important for their future. And yet, the respondents report that only 25% of AI projects are in widespread deployment and 40% of all projects are generating negative or no returns.

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Future of care: Patient-centricity with real-world predictive analytics

whitePaper | February 8, 2023

For centuries, patients have sought medical help for their ailments. Just as in the past, however, there are still many illnesses – both wellknown, widespread diseases and rare conditions – that initially cause few or inconclusive symptoms, and many patients leave the doctor’s office with an incorrect diagnosis. In addition, diseases may progress slowly or quickly depending on the individual.

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Human-Proofing Sensitive Data Governance with Automated Data Classification

whitePaper | December 1, 2022

IT and business leaders are increasingly seeking to harness the valuable data they collect every day to transform their business operations. Yet, these data assets are only as valuable as their organization’s ability to securely access and convert siloed information into scalable enterprise-wide insights. Even though every modern enterprise generates a goldmine of data, many lack the necessary infrastructure to mitigate data privacy and security concerns enough to fully leverage that data for informed decision-making and maximum impact.

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The Definitive Guide to Test Data Management

whitePaper | November 10, 2022

In this hyper-competitive era, faster time-to-market plays a vital role in the success of an organization. Any lag accounts for the 'Cost of delay,' impacting the value a product could create otherwise. This is the primary reason teams are adopting an agile approach to software development, testing, and release. Unfortunately, teams that don't follow suit find it challenging to deal with this accelerated timeframe.

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Self-Service Data Intelligence

whitePaper | September 20, 2022

Self-service is without question no longer an option for successful businesses. Find out how Alation can accelerate data-driven decisions with our Self-Service Data Intelligence white paper.

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The Alignment Problem with "Sale of Data"

whitePaper | December 12, 2022

In August 2022, the California Office of the Attorney General announced a $1.2 million settlement with international cosmetic retailer Sephora for violations of the California Consumer Privacy Act. Following this announcement came a wave of questions about the regulator’s emphasis on the broad interpretation of the CCPA’s “sale of data” and adoption of the Global Privacy Control.

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Spotlight

Paradata

Paradata addresses supply chain inefficiencies by providing current and verifiable component data to optimize product design and manufacturing. Paradata's machine learning engine classifies and ranks public and private data to deliver components that fit customers' specific product needs. This increased transparency into their global supply chains delivers efficiency and cost savings.

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