Abstract
Vadalog is a logic-based reasoning language for modern AI solutions, in particular for Knowledge Graph (KG) systems. It is showing very effective applicability in the financial realm, with success stories in a vast range of scenarios, including: creditworthiness evaluation, analysis of company ownership and control, prevention of potential takeovers of strategic companies, prediction of hidden links between economic entities, detection of family businesses, smart anonymization of financial data, fraud detection and anti-money laundering. In this work, we first focus on the language itself, giving a self-contained and accessible introduction to Warded Datalog+/-, the formalism at the core of Vadalog, as well as to the Vadalog system, a state-of-the-art KG system. We show the essentials of logic-based reasoning in KGs and touch on recent advances where logical inference works in conjunction with the inductive methods of machine learning and data mining. Leveraging our experience with KGs in Banca d’Italia, we then focus on some relevant financial applications and explain how KGs enable the development of novel solutions, able to combine the knowledge mined from the data with the domain awareness of the business experts.
The views and opinions expressed in this paper are those of the authors and do not necessarily reflect the official policy or position of Banca d’Italia.
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Acknowledgements
The work on this paper was supported by EPSRC programme grant EP/M025268/1, the EU H2020 grant 809965, and the Vienna Science and Technology (WWTF) grant VRG18-013.
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Bellomarini, L., Magnanimi, D., Nissl, M., Sallinger, E. (2021). Neither in the Programs Nor in the Data: Mining the Hidden Financial Knowledge with Knowledge Graphs and Reasoning. In: Bitetta, V., Bordino, I., Ferretti, A., Gullo, F., Ponti, G., Severini, L. (eds) Mining Data for Financial Applications. MIDAS 2020. Lecture Notes in Computer Science(), vol 12591. Springer, Cham. https://doi.org/10.1007/978-3-030-66981-2_10
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