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Technology
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Industry
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Solutions
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- ASSET MANAGEMENT
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- CYBER SECURITY
- DATA CENTER
- DOCUMENT MANAGEMENT
- ELECTRONIC DATA INTERCHANGE
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Platforms
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Functions
- Leadership Perspectives
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Rajib K Saha, CEOText Analytics, as developed by Parabole, allows for the extraction of critical information from these sources including documents on Model Risk Management, Risk Policy, Product, Regulatory Guidance, etc. Tactically, it provides structure to unstructured data in order to classify, cluster and contextually search this data.
“Our Text Analytics platform uses Parabole Knowledge Graph which is ingested with credit risk, market risk, liquidity risk, operational risk, finance, treasury and regulatory compliance knowledge and is trained to perform the automated analysis of domain documents” says Rajib Saha, CEO and co-founder of Parabole.
Parabole Text Analytics uses its proprietary Natural Language Processing models trained on risk, finance and compliance domain and a combination of proprietary Machine Learning algorithms to extract knowledge from unstructured content, which is then applied to automate the analysis of this information. Their platform offers several capabilities, including: Term Discovery, Topic Discovery, Content Similarity, and Named Entity Recognition.Term Discovery automates the identification of the key “terms” in a document. This would greatly reduce the effort spent by the data groups to manually read risk-finance documents to identify “CriticalData Elements”, their contextual usage and business side lineage of the data. Today, teams spend significant hours interviewing their respective business groups in order to understand business terms and their contexts. Topic Discovery is another tool that enables the reader to understand the theme of a document in a fraction of the time taken to manually read it. Using Content Similarity, a reader can find similar contentacross several documents and discover linkages.
The solution also facilitates audit and regulatory review by linking evidence and creating an auditable environment. Parabole’s real-time dashboards provide a 360-degree view of the analysis androle-specific performance.
To cite a case study, Parabole allows one of the global creditcard issuers to meet the challenge of analyzing the impact of the new FASB-CECL regulation. Every lender must make changes to their current models, accounting processes and amend the way they calculate and provide capital for credit losses. By automating the analysis of a 300-page regulation and mapping it to their current models, accounting policies and process documents, analysis that would typically take 80-90 percent of the overall assigned time, took only 20 percent of this time. This gave the bank more time to validate the analysis and added nearly 50 percentmore time for implementation, testing and audit at reduced cost. This automation being regulation agnostic can be used across regulatory regimes and geographies adding much needed muscle to banks compliance programs.
Our AI powered Text Analytics platform is aimed at extracting knowledge from unstructured data across risk, finance and regulatory compliance domain for banking and financial institutions
Parabole is building more domain-specific use-cases for banking clients which involves dealing with voluminous documents in risk and finance including but not limited to, data governance, contract management, covenant management, content rationalization and financial research news analysis. “We realized very early company, that we are only solving a part of the puzzle. It’s important to be part of the ecosystem to solve the larger issues of enterprises, and hence, we are working closely with leading companies, to build a cohesive ecosystem,” adds Saha. With its unique platform that is automating domain-rich analytics, Parabole remains a revolution extending big data-centric models into the world of big knowledge.
Parabole.ai announces the release of ESG-RC, an open-source follow-up to the popular ESG-BERT advanced ESG model
Thursday, September 21, 2023
The new ESG-RC model, to be released in October 2023, is built upon our TRAIN Platform and delivers Root Cause Analysis to empower investors and enterprises to navigate the complexities of ESG, championing sustainable business and responsible investment.
PRINCETON - With over 1,800,000 downloads, Parabole.ai's ESG-BERT model, was one of, if not the earliest ESG-trained language models to be released to the general public. Parabole.ai extends its commitment to open source and pioneering advancements in Causal Intelligence and ESG-focused AI. Enriched through a comprehensive dataset including sustainability reports and pivotal ESG materials, ESG-BERT is trained to discover intricate ESG contexts with industry leading precision. In a benchmark study of ESG-BERT, the standard BERT model scored a F1 rating of 0.79, while the ESG-BERT model delivered a score of 0.90.
Building upon its established legacy, the upcoming ESG-RC model offers an array of enhanced capabilities, most notably incorporating robust Root Cause Analysis. This unique feature is designed to assist users in delving deeper into the fundamental dynamics underlying ESG (Environmental, Social, and Governance) risks and opportunities. The innovation behind ESG-RC extends the reach and potency of the original model by shedding light on critical supply chain concerns, including newfound insights into Modern Day Slavery and Global Food Supply Chain practices and infractions. ESG-RC is slated for release in October, while ESG-BERT will remain accessible via ESG-BERT Bitbucket.
Notable Features of ESG-RC:
1. Root Cause Analysis: Unearths the underlying causes and effects of core ESG risks and opportunities, helping to answer the question "why?" behind sustainability reporting statements, claims, and outcomes.
2. Text Classification: Seamlessly categorizes text into distinct ESG components, facilitating the identification of risks and opportunities.
3. Contextual Analysis: Offers a comprehensive exploration of ESG narratives, pinpointing areas warranting detailed examination.
4. Entity Extraction: Identifies essential entities, such as corporate names or ESG metrics, fostering the development of knowledge graphs and enabling longitudinal performance tracking.
5. Risk Analysis: Employs advanced tools to conduct thorough evaluations of ESG risks, revealing latent opportunities.
6. Reporting: Generates transparent, detailed reports, presenting ESG metrics to stakeholders in a clear and comprehensible manner.
Anthony Sarkis, Head of Strategy at Parabole.ai, reflected on Parabole's history in ESG AI development, stating, "The TRAIN Platform equips our enterprise clients with a toolkit for crafting knowledge-enriched causal models, along with a robust library of frameworks to tackle novel and intricate challenges across various sectors, with a particular emphasis on manufacturing and supply chain sustainability. In 2020, we broke new ground in the Generative AI field with the launch of our open-source ESG-BERT model. Its widespread acceptance underscores our team's expertise in developing language models that seamlessly complement our Causal Platform. The forthcoming ESG-RC model, poised to redefine root cause analysis in the ESG domain, will also be open-source, aligning with our commitment to bolstering global sustainability initiatives for all."
Our TRAIN platform can construct customized frameworks that expand our continuously growing library of Causal Frameworks, tailored to meet the needs of manufacturing enterprises, government agencies, and standards organizations. These solutions are crafted to amplify insights and enhance decision-making capabilities in relation to supply chain and sustainability factors. For more information on how TRAIN can empower your enterprise, please contact Jonathan Doan, Vice President, at jd@parabole.ai.
Company
parabole.ai
Management
Rajib K Saha, CEO
Description
Automates analysis of risk and finance documents for risk management and regulatory compliance for banking and financial institutions
