With a B2B model, Altilia utilises AI to create software robots that understand documents for extracting data and knowledge quickly, securely, and accurately to efficiently automate operations and decision-making processes. But there are some document-intensive processes where human understanding and contextualisation are needed and cannot be automated by standard RPA tools. Altilia’s platform addresses this challenge and streamlines the application of AI to business processes that require human understanding capabilities, allowing clients to dedicate the human workforce toward highvalue tasks and strategic decision-making.
In the financial service industry, there is a need to explain why a specific machine learning algorithm has extracted the particular data from a given document. Therefore, Altilia’s module ‘Altilia reviews’ enables users to visualise the exact location of the extracted data within documents. This provides concrete context to users, so they can check and ensure that the target data is precisely the one provided in output by the algorithm. The financial service industry is also a continuously changing environment where documents can change in format or layout in several ways. With Altilia’s technology, users can review the results and provide feedback to the system. The platform considers this feedback to retrain continuously and learn from the user interaction. The extracted output data can then be exported to clients’ third-party technologies (like ECM, ERP or CRM tools) to run together efficiently with Altilia’s platform.
Altilia implements deep learning algorithms and neural information retrieval features to automatically index and classify documents. Furthermore, information extracted from documents is stored in the platform’s knowledge base.
Thus, the platform transforms all the documents owned by clients into a knowledge base where end users can apply full text and rich multifaceted semantic search into the contents.
In the financial and banking sector, there are many activities that still require manual documents processing. For example, today banks need to account for credit scores and ESG profiling considerations when evaluating enterprise loan applications. This involves analysing several documents that describe a company, its board composition and administrative history, including many official documents like financial statements. Banks store all these documents into a specific repository or an Enterprise Content Management (ECM) system, to be accessed by backend officials who need to understand revenue projection from the investment or the business plan for the requested amount. In this case, Altilia firstly extracts target data through an input connector directly from the ECM system (like OpenText Documentum), it classifies documents by type and assigns metadata to each one. The platform then provides output data through multiple connectors to be used for the credit scoring algorithm and compute the interest rate to apply to loan applicants. Backend employees can simply check and review extracted data for quality control.
We cut the manual work around 80 percent and speed up the loan processing cycle from five days to two days, leading to improved customer satisfaction
Nowadays, various financial service operators, like debt collection agencies, buy Non-Performing Loans (NPL) from banks and then work to recover the distress debt. There are several different types of documents to classify, and Altilia applies machine learning to extract each type of document's specific set of data. Through a similar process of data intake, classification, and output, the platform helps significantly to reduce the timeframe and the manual work. The most crucial benefit, in this case, is that clients can evaluate a specific NPL case more rapidly and accurately, which drives higher margins and more revenues.
In the financial service arena, Altilia is also working on extracting specific data points from notes to balance sheets to understand the risk exposure related to commodities, forex, and debts. Banks can utilise this information to compose accurate company profiles and create sales pitches for their highly complex derivative products.
During the second half of 2022, Altilia will be focused on the internationalisation of its business in North America, UK, and the Western European market. The company will collaborate with other players in the financial service industry to solve the most painful document-based processes. Altilia will be extending its product offerings to address customers purely with a software as a service approach. The company’s scope is focused on the democratisation of AI, so the goal is to let enterprises buy the technology directly from its website and apply it to new use cases.