Lingua Custodia proves conclusively that it is possible to develop cutting edge generative AI tools without a 10M€+ investment!

The French Fintech company Lingua Custodia, a specialist in Natural Language Processing (NLP) applied to Finance since 2011, releases its new Document Analyser, a generative AI tool allowing its 10,000+ financial users to easily and securely answer due diligence questionnaires and find information in large volumes of documentation.


With one click and the input of questions, the users of Verto, Lingua Custodia’s secure document processing platform, can now retrieve information in multiple languages from vast amounts of data. The aim of the document analyser is to meet the business case for speed and accuracy in responding to regulatory, client and investment queries.


The Lingua Custodia team of research scientists and engineers had been working on the product design for the Document Analyser tool for over a year to propose this secure solution hosted in the EU on secure and segregated GPU servers.


Olivier Debeugny CEO of Lingua Custodia declared : “Generative AI tools are hot topics at the moment for funding rounds, I however firmly believe that innovative document processing technologies can be produced without large investment, provided you have a lot of data, experience and a skilled team! Lingua Custodia has been at the forefront of language technologies since its creation in 2011 and we believe the Document Analyser will empower our clients, improving operational efficiency, and enhancing their decision-making processes.”


The Document Analyser is available on Lingua Custodia’s financial document processing secure platform, together with its translation, transcription and other data extraction AI tools.

IA Frugale : Sans lever des millions d’euros, Lingua Custodia met à disposition de ses clients un nouvel outil d’IA générative

Sans lever des millions, Lingua Custodia met à la disposition des professionnels de la finance un nouvel outil d’IA générative répondant à des cas d’usage précis

Lingua Custodia, la fintech spécialisée dans les technologies du langage depuis 2011, a mis en ligne sur sa plateforme Verto accessible par plus de 10 000 professionnels de la finance, un nouvel outil permettant d’interroger des documents confidentiels multilingues.


C’est en analysant les besoins de ses clients, en utilisant sa longue expertise en technologie du langage et ses corpus linguistiques développés depuis plus de dix ans que l’équipe d’experts de Lingua Custodia sort aujourd’hui sur le marché un nouvel outil d’analyse de documents sécurisé et multilingue spécialisé pour le secteur financier.


Ce nouvel outil permet par exemple d’interroger des procédures internes pour répondre très rapidement à des questionnaires reçus de régulateurs ou clients, des situations très fréquentes dans les institutions financières.


Olivier Debeugny, Président de Lingua Custodia, déclare : « Je suis particulièrement fier de notre équipe qui illustre un autre angle de l’Intelligence Artificielle frugale. Avec des bases de données de grande qualité constituées sur plusieurs années, notre équipe de chercheurs très expérimentés travaillant main dans la main avec des universités et laboratoires de recherche, et une compréhension des besoins de nos clients, nous avons su mettre en ligne, sans devoir faire appel à des financements massifs, un nouvel outil à la pointe de l’état de l’art apportant une réelle valeur ajoutée à nos clients. »


L’analyseur de document est disponible sur Verto, la plateforme de traitement documentaire sécurisée de Lingua Custodia et vient s’ajouter aux outils de traduction automatique, de transcription et autres outils d’extraction de données.

A propos de Lingua Custodia


Lingua Custodia est une Fintech leader du Traitement Automatique des Langues (TAL) pour la Finance basée en France et au Luxembourg. Elle a développé son expertise avec une offre pointue de traduction automatique spécialisée par type de document financier. La société propose aujourd’hui également des services de transcription automatique, des services d’analyse linguistique de documents et des services d’extraction de données via sa plateforme en ligne ou par API. Ses clients sont des institutions financières et les départements financiers de grandes sociétés et ETI.


Contact Presse
Charlotte BAIN , CAO : charlotte.bain@linguacustodia.com / +33 1 83 43 95 25

Do Multilingual Language Models Think Better in English?

Do Multilingual Language Models think better in English?!

Most large language model (LLM)-based chatbots are trained on data from dozens of languages, but English is still the dominant language, as most of the web data is written in this language. Because of this, multilingual LLMs have much better understanding and generation capabilities in English than the other languages. However, we still need LLMs to perform well in other languages to ensure accurate and reliable results in multilingual contexts.

One solution which has been around for a while is to detect the input language, translate it to English, let the LLM process the question and generate the answer in English. Finally we can translate the response back to the desired language of the user. Although this process works well, in practice, it means you will need a few extra tools, such as a language detector and a machine translator. These additional tools can add to the complexity of the project.

In an experiment conducted by the University of the Basque Country, researchers confirmed that multilingual LLMs perform better in English than other languages seen during training. Their study shows that using multilingual LLMs to translate the input into English and perform the intended task over the translated input works better than using the original non-English input. This work shows that letting the model translate the input by itself can achieve almost the same performance as using an external translation system. This opens up opportunities for end-to-end multilingual chatbots and other generative AI models without relying on external translation systems. 

Lingua Custodia’s VERTO NLP financial document processing platform allows you to easily translate documents from several languages to English.  Our NLP translation service detects both the source language and document type which helps to optimise the translation quality. Our generative AI document analyser service then allows you to process questions in English, and again the responses can then quickly be translated back to the necessary language.  

How LLMs (Large Language Models) use long contexts

Large language models (LLMs) are capable of using large contexts, sometimes hundreds of thousands of tokens. OpenAIs GPT-4 is capable of handling inputs of up to 32K tokens, while Anthropic’s Claude AI can handle 100K context tokens. This enables LLMs to treat very large documents which can be very useful for question answering or information retrieval.

A newly released paper by Stanford University examines the usage of context in large language models, particularly long contexts for two key tasks: multi-document question answering and key-value retrieval. Their findings show that the best performance is typically achieved when relevant information occurs at the beginning or end of the input context. However, the performance of models significantly declines when they need to access relevant information in the middle of long contexts.This could be attributed to the way humans write, where the beginning and concluding segments of text mainly contain the most crucial information.

These findings show that one needs to be careful when using LLMs for search and information retrieval in long documents. Information found in the middle might be ignored by the LLM and hence wrong or less accurate responses will be provided.

Lingua Custodia has over 10 years of experience in language technologies for financial document processing and we are very aware of the importance of context for search and information retrieval sentiment analysis, content summary and extraction. We continuously study the impact of context size of these language models

Our expert team consists of scientists, engineers and developers, so we are well placed to create, customise and design secure LLMs which are perfectly tailored to meet your business needs.

Generative AI for Enterprise Solutions – privacy and quality issues

There are clear advantages for companies in using generative AI tools – they can provide financial analysis, forecasting and report generation.  Chat bots are another area where generative AI can offer human-like interactions, responding to queries and generating content in the form of emails and documents, providing a fully optimised client service response model.

While companies can see clear advances for productivity in terms of using generative AI chatbots, concerns remain regarding privacy and the protection of confidential financial data.  

Open AI and privacy

Open AI tools such as Chat GPT, will reuse the prompts input when using their platform to train their models, unless the opt out option is used. 

 This is one of the reasons for several large companies such as Apple and Samsung restricting their employee’s usage to generative AI models, because of the potential risk of employees inadvertently sharing proprietary or confidential data. 

Microsoft Bing Enterprise

Microsoft Bing Enterprise was developed in response to these concerns, as the chat access is not saved, ensuring that data remains private.  This distinguishes it from other open Chat bots which are built on more open models.   Bing Chat Enterprise will provide a similar user experience to Bing Chat. providing answers with citations as well as visual answers including charts and images. It’ll be available free with existing Microsoft 365 E3, E5, Business Standard, and Business Premium subscriptions, and the company also plans to sell a standalone subscription in the future.

Other solutions for companies include developing in-house chat bots, based on their own data, which ensures their data stays in house. 

Data and accuracy

In addition to privacy, concerns over the use of generative AI tools generals are relate to accuracy and hallucinations. The data on which the tool is based needs to be ‘clean’ and of good quality for the tool generate correct content.  

Lingua Custodia and Generative AI


Lingua Custodia has been working on generative AI models for its financial clients for several years, and as a specialist in the financial industry, it is very aware of the importance of ensuring its clients data remains private.  Lingua Custodia’s Data team play a key role in ensuring the underlying data is cleaned and good quality, which is fundamental to the accuracy and reliability of the responses. If models use unreliable data, then this will have a strong impact on the output data quality.

How will the AI Act impact start ups?

AI is part of Lingua Custodia’s DNA! Olivier Debeugny, our CEO was recently featured in a Luxembourg Startup article on the topic of How Will The AI Act Impact Startups? In this article, he emphasized the commitment of our company, Lingua Custodia, to transparency towards our customers regarding the risks and opportunities of our AI systems.

Olivier also felt that the European Parliament’s risk-based approach to AI autonomy, was practical and realistic. He expects this approach to create new opportunities for first movers in AI-compliance.

Lingua Custodia has always been transparent with clients about the risks and opportunities of its AI systems which largely depend on the usage and autonomy of the solution’

At Lingua Custodia, we look forward to exploring these new opportunities and continuing to offer secure and transparent AI solutions.

You can find the full article by clicking on the following link:   https://lnkd.in/eQceuwwn

Financial Document Processing with AI

Introduction

In today’s fast-paced financial landscape, businesses are constantly seeking ways to enhance their operational efficiency and accuracy. One area that holds immense potential for improvement is financial document processing. Traditionally, this task has been time-consuming, prone to errors, and resource-intensive. However, with the advent of Artificial Intelligence (AI) technology, financial document processing has undergone a transformative shift. In this article, we will explore how AI is revolutionizing the way financial documents are processed, providing businesses with a streamlined and automated solution.

Financial Document Processing with AI: Enhancing Efficiency

Financial document processing involves various tasks such as data extraction, classification, validation, and interpretation. These processes, when performed manually, are not only time-consuming but also susceptible to human errors. By leveraging AI technologies, businesses can significantly enhance their efficiency in handling financial documents.

Automated Data Extraction

AI-powered systems can automatically extract relevant data from financial documents, such as invoices, receipts, and bank statements. Utilizing techniques such as optical character recognition (OCR), AI algorithms can accurately capture and interpret data from structured and unstructured documents. This eliminates the need for manual data entry, reducing the chances of errors and speeding up the overall processing time.

Intelligent Document Classification

AI algorithms can analyze the content and structure of financial documents to classify them into different categories. By training the AI models on a vast amount of data, businesses can automate the document classification process, ensuring that each document is accurately categorized. This allows for easier retrieval, organization, and analysis of financial information.

Real-time Validation and Verification

With AI-powered systems, businesses can automate the validation and verification of financial documents. These systems can compare the extracted data with predefined rules and business logic to ensure accuracy and compliance. In addition, AI algorithms can identify anomalies and flag potential errors or fraudulent activities, providing businesses with real-time alerts and notifications.

Smart Interpretation and Analysis

AI technology enables businesses to gain valuable insights from financial documents. By leveraging natural language processing (NLP) and machine learning techniques, AI algorithms can interpret and analyze the textual content of financial documents. This enables businesses to uncover patterns, trends, and anomalies in financial data, empowering them to make informed decisions and improve their financial strategies.

FAQs (Frequently Asked Questions)

1. What is financial document processing with AI?

Financial document processing with AI refers to the utilization of Artificial Intelligence technologies to automate and streamline the handling of financial documents. This includes tasks such as data extraction, document classification, validation, and interpretation.

2. How does AI enhance efficiency in financial document processing?

AI enhances efficiency in financial document processing by automating data extraction, intelligent document classification, real-time validation and verification, and smart interpretation and analysis. These AI-powered processes save time, reduce errors, and provide valuable insights for businesses.

3. Can AI accurately extract data from different types of financial documents?

Yes, AI algorithms can accurately extract data from various types of financial documents, including invoices, receipts, bank statements, and more. Using techniques like optical character recognition (OCR), AI systems can capture and interpret data from both structured and unstructured documents.

4. How does AI ensure accuracy and compliance in financial document processing?

AI ensures accuracy and compliance by validating extracted data against predefined rules and business logic. AI-powered systems can perform real-time validation and verification, flagging potential errors or fraudulent activities. This helps businesses maintain accuracy and adhere to regulatory requirements.

5. Can AI provide valuable insights from financial documents?

Yes, AI can providevaluable insights from financial documents. By utilizing natural language processing (NLP) and machine learning techniques, AI algorithms can interpret and analyze the textual content of financial documents. This enables businesses to uncover patterns, trends, and anomalies in financial data, empowering them to make informed decisions and improve their financial strategies.

6. Is financial document processing with AI secure?

Yes, security is a critical aspect of financial document processing with AI. Businesses can implement robust security measures to protect sensitive financial data throughout the processing cycle. This includes encryption, access controls, and data anonymization techniques to ensure the confidentiality and integrity of the information being processed.

Conclusion

Financial document processing with AI is transforming the way businesses handle and manage their financial documents. By automating tasks such as data extraction, document classification, validation, and interpretation, AI technology enhances efficiency, accuracy, and compliance. Businesses can streamline their operations, reduce errors, and gain valuable insights from financial data. Embracing AI-powered solutions for financial document processing is crucial for organizations looking to stay competitive in the rapidly evolving financial landscape.

Lingua Custodia.

Wealth Management Traduction: Understanding the World of Financial Management in French

Introduction

In today’s globalized economy, financial management has become an essential aspect of personal and business success. With the increasing internationalization of markets, it is crucial to have a clear understanding of financial concepts in different languages. This article aims to provide a comprehensive guide to wealth management traduction, focusing on the French translation of key terms and concepts. Whether you are a professional working in the finance industry or an individual looking to expand your financial knowledge, this article will serve as an invaluable resource.

Wealth Management Traduction: Exploring the Basics

What is Wealth Management Traduction?

Wealth management traduction refers to the translation of financial and investment terms from one language to another, specifically in the context of wealth management. It involves accurately conveying financial concepts, strategies, and best practices in a target language, such as French. The goal of wealth management traduction is to ensure effective communication and understanding of financial matters across different linguistic communities.

The Importance of Wealth Management Traduction

In today’s interconnected world, effective communication is key to success in any field. When it comes to financial management, language barriers can hinder understanding and collaboration. Wealth management traduction plays a vital role in breaking down these barriers, allowing individuals and businesses to access valuable financial information and services in their preferred language. It enables seamless communication between financial professionals and their clients, ensuring that everyone is on the same page when it comes to managing wealth effectively.

Key Terms and Concepts in Wealth Management Traduction

To gain a deeper understanding of wealth management traduction, let’s explore some essential terms and concepts commonly used in financial management. The following table provides translations of key terms from English to French:

EnglishFrench
Wealth ManagementGestion de patrimoine
Investment PortfolioPortefeuille d’investissement
Risk ManagementGestion des risques
Retirement PlanningPlanification de la retraite
Tax OptimizationOptimisation fiscale
Estate PlanningPlanification successorale
Asset AllocationAllocation d’actifs
Financial AdvisorConseiller financier
High-Net-Worth IndividualIndividu fortuné
Wealth PreservationPréservation du patrimoine

Understanding these terms is essential for anyone involved in wealth management or seeking professional financial advice in French-speaking contexts.

The Process of Wealth Management Traduction

To ensure accurate and effective wealth management traduction, a systematic process is followed. Let’s take a closer look at the key steps involved:

  1. Gathering Source Material: The first step in the traduction process is to gather all relevant source materials, including financial documents, reports, and industry publications. These materials serve as the foundation for accurate translations.
  2. Identifying Key Terminology: Once the source materials are gathered, the translator identifies the key financial terminology that needs to be translated. This step ensures that all critical concepts are appropriately conveyed in the target language.
  3. Translating and Localizing: The actual translation process begins, with the translator converting the source materials into the target language while ensuring that the content is adapted to the local linguistic and cultural context.
  4. Review and Editing: After the initial translation, the work is reviewed and edited by language experts and industry professionals to ensure accuracy, coherence, and compliance with industry standards.
  5. Quality Assurance: The final step involvesconducting a thorough quality assurance check to ensure that the translated content meets the highest standards of accuracy, clarity, and readability.

By following this systematic process, wealth management traduction providers can deliver high-quality translations that effectively convey financial concepts to French-speaking audiences.

FAQs About Wealth Management Traduction

1. What skills are required for wealth management traduction?

To excel in wealth management traduction, translators need a strong command of both the source and target languages, as well as a deep understanding of financial concepts and terminology. Attention to detail, research skills, and cultural sensitivity are also essential.

2. Can automated translation tools replace human translators in wealth management traduction?

While automated translation tools can be helpful for basic translations, they are often unable to accurately capture the nuances and complexities of financial terminology. Human translators with expertise in finance and language are still essential for ensuring accurate and reliable translations.

3. How can I find a reputable wealth management traduction service?

When searching for a wealth management traduction service, it is important to consider factors such as the company’s experience in the field, the qualifications of their translators, and their track record of delivering accurate translations. Reading reviews and seeking recommendations can also help in making an informed decision.

4. Is wealth management traduction limited to French-speaking countries?

No, wealth management traduction is not limited to French-speaking countries. In today’s globalized economy, financial management involves cross-border transactions and collaborations. Wealth management traduction is necessary in any context where effective communication in financial matters is required, regardless of the language spoken.

5. Can I translate financial documents myself without professional assistance?

While it is possible to attempt translating financial documents yourself, it is highly recommended to seek professional assistance. Professional translators with expertise in wealth management traduction can ensure accurate and reliable translations, saving you time, effort, and potential errors.

6. How much does wealth management traduction cost?

The cost of wealth management traduction varies depending on factors such as the volume of content, the complexity of the material, and the level of expertise required. It is best to request quotes from different translation service providers to compare prices and choose one that offers a balance of quality and affordability.

Conclusion

Wealth management traduction plays a vital role in bridging the gap between different linguistic communities in the field of financial management. By accurately translating financial concepts, terms, and documents, wealth management traduction facilitates effective communication, collaboration, and understanding. Whether you are an individual seeking financial advice or a business operating in international markets, having access to accurate and reliable translations in wealth management is crucial for success.

Remember, when it comes to wealth management traduction, it is essential to rely on professional translation services with expertise in both finance and language. By doing so, you can ensure that your financial information and documents are effectively conveyed to your target audience in their preferred language.

Lingua Custodia.

Lingua Custodia contributes to the WMT21 Conference on Machine Translation for the third time.

On November 11th, Melissa Ailem, Researcher at the Lab, presented Lingua Custodia’s submission to the WMT21 shared task on machine translation using terminologies. It is the third time the Lab contributes to the conference.

WMT is a major event where best MT players, both academic and industry-side, present their latest findings.

Abstract

This paper describes Lingua Custodia’s submission to the WMT21 shared task on machine translation using terminologies. We consider three directions, namely English to French, Russian, and Chinese. We rely on a Transformer-based architecture as a building block, and we explore a method which introduces two main changes to the standard procedure to handle terminologies. The first one consists in augmenting the training data in such a way as to encourage the model to learn a copy behavior when it encounters terminology constraint terms. The second change is constraint token masking, whose purpose is to ease copy behavior learning and to improve model generalization. Empirical results show that our method satisfies most terminology constraints while maintaining high translation quality.

Read the paper

Le Lab de Lingua Custodia publie ses recherches en NLP

Aujourd’hui, l’équipe du Lab de Lingua Custodia présente un article de recherche sur leur « approche pour intégrer les contraintes terminologiques dans les modèles de traduction neuronale » qui a été sélectionné pour publication à la conférence TALN RECITAL 2022 à Avignon, France.

Du 27 juin au 1er juillet 2022, le Laboratoire d’Informatique et de Systèmes (LIS) et le Laboratoire d’Informatique de l’Université d’Avignon (LIA), aux côtés de l’Association pour le Traitement des Langues Naturelles (Atala), organisent conjointement la 29e conférence sur le TALN et la 24e Réunion des Etudiants Chercheurs en Informatique pour le TAL.

Programme de la conférence TALN-RECITAL

Préparation de la conférence sur la traduction automatique WMT 2022

Pour la troisième année consécutive, le Lab participera à une tâche partagée lors de la septième conférence sur la traduction automatique – WMT 2022 – qui se tiendra à Abu Dhabi en décembre.

https://statmt.org/wmt22/word-autocompletion.html

Ils ont également contribué, pour la quatrième année, à la préparation de la tâche générale partagée de traduction automatique en fournissant des sets de test, aux côtés cette année de Microsoft, Facebook, NTT, l’Université de Tokyo et Webinterpret.

https://statmt.org/wmt22/translation-task.html

Dernières contributions et publications

Janvier 2022 / Covid-19 MLIA Challenge

Le Lab s’est classé 1er dans 4 paires de langues sur 7 lors du 2e tour du Covid-19 MLIA Challenge – un projet de collaboration européenne soutenu par la Commission européenne, la Coordination européenne des ressources linguistiques (ELRC), et plusieurs autres entités et universités.

Le projet coordonne un effort d’évaluation communautaire visant à accélérer la création de ressources et d’outils pour améliorer l’accès à l’information multilingue en utilisant la technologie du Machine Learning.

http://eval.covid19-mlia.eu/

Novembre 2021 / Conférence de Traduction Automatique WMT 2021

Publication de Lingua Custodia sur la tâche partagée de traduction automatique intégrant les contraintes terminologiques.

https://arxiv.org/abs/2111.02120

Juillet 2021 / Conférence ACL-IJCNLP

Le papier de recherche « Encouraging Neural Machine Translation to Satisfy Terminology Constraints » a été accepté pour publication à la 59ème conférence annuelle de l’Association for Computational Linguistics (ACL) et la 11ème International Joint Conference in Natural Language Processing (IJCNLP).

Cette reconnaissance confirme la position du Lab en tant que leader dans le domaine du TAL, aux côtés d’entreprises prestigieuses : Google Research, Facebook AI ou Amazon Sciences.

https://2021.aclweb.org/

A propos de Lingua Custodia

Lingua Custodia est une Fintech leader du Traitement Automatique des Langues (TAL) pour la Finance.

La société a été créée en 2011 par deux professionnels de la Finance pour, à l’origine, développer des moteurs de traduction automatique spécialisés pour les documents financiers.

Capitalisant sur son expertise en TAL développée depuis plus de 10 ans, la société offre maintenant une gamme en constante évolution d’applications : transcription audio/vidéo, classification de documents, extraction de données linguistiques de documents non structurés, Web crawling de données linguistiques … avec des niveaux de qualité très élevés grâce à ses algorithmes de Machine Learning hyper spécialisés dans le langage financier.

Sa technologie a été régulièrement récompensée et est reconnue à la fois par l’industrie et ses clients : Gérants d’actifs, Banque d’investissement, Banques dépositaires, Banques privées, Directions financières de grands groupes et prestataires de services aux institutions financières.