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15th December 2022. Today Altilia is featured by Il Sole 24 Ore, the Italian national daily business newspaper.

The article, published in a special feature about best emerging innovative enterprises, explains how the use of artificial intelligence, to improve workflows and augment business, can be rendered accessible with Altilia’s Intelligent Document Processing (IDP) platform.

Altilia Intelligent Automation can process and reorganize data contained within all types and format of document, like, for example, notes to financial statements, land registry reports, or more simply invoices, orders, and forms in general. All of which contain information that is fundamental for the proper execution of business processes in organizations of any size and industry.

With the evolution of RPA (Robotic Process Automation) into IPA (Intelligent Process Automation), Altilia can now automate complex processes that require human cognitive abilities. Companies can reduce their skill shortage problems, by having Machine Learning (ML) algorithms trained directly by business users.

The article also describes some of the most relevant use cases examples of how Altilia can make a difference in the workflow of a business ecosystem: automating the creation of company ESG risk profiles to support lending operations; automating data extraction from complex documents to support Non-Performing-Loan (NPL) evaluation.

Click here to learn more about main IDP applications and use cases.

Altilia has been quoted by influential business magazine Forbes in an important article on the future of AI and how it will change the type of employees required by organizations in the future.

On November 24th, 2022, the magazine published an article entitled “Does Working With AI Help Or Hinder Employees?”. It focused on the necessity of tweaking the ways of managing internal processes to reap the benefits of new technologies being introduced with the fourth industrial revolution.

One of the main arguments supported by the article is that technology can be beneficial in the workplace when it is meant to complement human capabilities. In fact, there is a greater sense that AI will augment the work humans do rather than replace them.

Time and talent

In the article, Massimo Ruffolo, Founder and CEO of Altilia stated: “When we choose humans to work with, we don’t tend to choose people that are identical to us as that would be a waste of time and talent.”

“It’s exactly the same with technology, and if we’re to achieve truly intelligent automation then we need to think of the kind of things that technologies like AI can do well and the kind of things that humans continue to do well.”

This implies that AI tools must not hinder the degree of control and autonomy employees have over their work, and this will quite probably require a rethinking of the processes we use at work so that the capabilities of the technology are fully capitalized on.

The article, which is available online here , is based on research from the University of Georgia in the US, which argues that the ability to work effectively alongside human staff may be hindered by our perceptions of just what is good in the workplace.

The study argues that the characteristics we typically value at work, such as conscientiousness, are also things that AI often thrives in, creating an unhelpful overlap of strengths.

Work values

The study makes the point that it’s commonly assumed that conscientious employees are strong performers but argues that technology is beneficial when it complements human capabilities and that, even when we choose human collaborators, we tend to prefer those who complement our own characteristics rather than replicate them.

The Atlilia Intelligent Automation platform is designed, in fact, to allow business-line users and domain-experts to leverage AI technology for intelligent automation, while maintaining control over the design and quality of internal processes.

This is possible thanks to the use of low/no-code interfaces to improve user accessibility (also for AI non-experts), and thanks to AI explainability features to simplify quality control of the automation solution.

Click here to read the complete article from Forbes.com.

From November 23rd to 25th 2022, Altilia participated in the “Salone dei Pagamenti” event in Milan. Promoted by ABI (Italian Banking Association) in collaboration with Banca d’Italia and Fintech Milano Hub. The event is a national reference point in the payments sector and for innovation in the Italian banking industry.

During the event, the project developed by Altilia, was recognized by Banca d’Italia among the 10 best innovative projects selected as part of the “Call for Proposals 2021” for innovative applications of AI technologies in banking.

The project, made collaboration with the ItaliaFintech Association, the Chiomenti law firm (as legal partner) and with the participation of Prometeia (as partner/user ), is an AI application in the field of ESG investments, aimed at facilitating banks in the process of corporate sustainability risk assessment and corporate sustainability goals assessment.

In particular, the project aims at automating the information gathering processes from different sources and documents (such as financial statements, sustainability reports and corporate websites) and, leveraging advanced Document Understanding and Natural Language Processing (NLP), provide automatic text comprehension and classification to create highly detailed ESG company profiles. These profiles can then be used by banks to monitor the evolution of ESG goals and risks over time and integrate the information to enhance their lending application procedures.

With the Altilia Intelligent Automation platform, users can directly train AI models to recognize the target data of interest. Using a no-code interface users can create a set of annotated document examples, and, with a sufficient number of examples, the algorithm becomes autonomous in recognizing the target data. The final results can be either stored in the platform or exported to be leveraged by other applications like CRM systems or customer’s databases. Thanks to this connectivity it is possible to automate the creation of detailed ESG report and risk scores.

With the proposed solutions banks can obtain up to an 80% reduction of the manual work required for ESG profiling, uplifting employees from all the repetitive tasks related to document reading and information extraction, and accelerating ESG profile generation speed by up to 10 times. In addition, the resulting profiles are more detailed and complete, with an accuracy score (F-score) of 95%.

At the closure of the “Salone dei Pagamenti” event, the project has been presented to Bank of Italy’s Governor Ignazio Visco, who directly met the awarded teams, and congratulated with Massimo Ruffolo, founder and CEO and of Altilia.

If you want to learn more, here you can find more information about AI applications for ESG in credit management.

After the initial enthusiasm about Large Language Models (LLMs) due to their impressive results that made them SOTA approaches for some new and traditional general purposes NLP tasks (e.g. question answering, text classification, information retrieval, token sequence tagging, entity extraction, sentiment analysis, intent detection, word sense disambiguation, POS-tagging), now it’s the time of reality.

Peraphs, LLMs are contributing more than computervision to the new AI spring. LLMs are powerful tools that can create great value in industry and help organizations to streamline business processes, improve operations, save a lot of money, and improve business performances. But, as a recent neural article optimally points out, they must be carefully adopted, furthemore they need to be fine tuned to solve specific business problems in vertical domains.

For this reason in Altilia we have built a platform that helps users to fine tune LLMs and control their results by human-in-the-loop AI, augmented intelligence, and composite and adaptive AI tools.

Users in highly specialized areas like pharma, health, and finance have to face problems cited in the article. In particular, LLMs cannot be used as they are. These models  are trained over general available data, hence specific data programming and fine-tuning techniques are needed to make them working in a trustworthy, explainable way on highly specific, regulated, privacy and security sensitive tasks.

Altilia Intelligent Automation platform leverages all LLMs available in huggingface and provides users with tools that allow to curate and program data set to fine-tune LLMs and apply them to solve any NLP and document processing task at the highest level of accuracy and trustworthiness needed by the users operating in highly regulated environments.

For more information read the following use cases: improving NPL data tapes management; enhancing credit scoring for lending applications; Extract ESG data from multiple sources; data extraction from notes to balance sheets.

The Financial Services Review magazine, a renowned digital and print publication with a solid reputation in discovering innovative technology trends and solutions for the Financial Services Industry, has just awarded Altilia as a Top Digital Banking Solutions Provider in Europe 2022.

Altilia has been nominated for its efforts to develop innovative solutions to automate many activities in the financial and banking sector, involving complex document intensive processes that still require manual work.

One relevant example is corporate ESG (Environmental Societal Governance) profiling for credit scoring purposes. In this case, Altilia is capable of classifying and extract target data from different types of documents (like balance sheets, annual reports, and financial statements), contained in several different sources (including corporate ECM systems).

Output data can then be used for the credit scoring algorithms to compute interest rates for loan applications. With this method, Altilia has been able to cut down manual work time requirements for the task by around 80%, with the effect of drastically reducing the loan processing lead time from ten days to just 2 days, thus greatly improving customer satisfaction.