Diasoft Offers Banks Machine Learning Technologies for Everyday Operations
November 24, 2020
Digital Q Intelligence Platform is a new Diasoft AI/ML platform based on low code principles. The low-code approach facilitates the design of machine learning models that are used to streamline functions of existing banking solutions and support digital transformation of the business. To implement artificial intelligence (AI) technologies, bank experts need to know only general principles of neuron networks, since all parameters can be set up through the system interface without coding.
The Diasoft team has been working on development of robotic process automation services (RPA) for quite a long time, and this work has resulted in creation of the AI / ML platform.
“First we embarked on creation of the infrastructure for robotic process automation services. We implemented robotized processes into our solutions. Using RPA, we streamlined the launch of everyday operations at several large banks. The creation of the AI/ML platform has become a logical next step in development of this business at Diasoft”, said Anton Shebalkin, Architect of the AI/ML Platform at Diasoft.
In comparison with RPA, the machine learning platform provides more advanced approaches to processing of information. For example, machine learning services allow grouping objects by specific non-rigid attributes which cannot be used in robotic processes.
Diasoft developed a smart framework for creation of neural network models and ready-to-use microservices that can be integrated into any business process of a bank.
“We have created a mechanism for support of the whole lifecycle of neural network models. These networks can be built into bank business processes and used without integration with other systems. Significantly, they work without involvement of users. Such approach to implementation of the AI at banks make these technologies more accessible. We hope that the AI will become an integral part of the bank infrastructure, since they provide really impressive capabilities”, commented Sergey Ripplinger, Head of Money Transfers and Teller Solutions at Diasoft.
Diasoft offers its customers to use machine learning to analyze customer behavior, define their loyalty and predict customer churn. Using precise AI/ML tools, the bank can classify, track, analyze and organize information, for example to define the purpose of payments to treat them in compliance with regulatory requirements.
“The use of AI-based tools helps streamlining solutions based on static algorithm, such as classification of documents. It also facilitates processing of Big Data. Most IT solutions run on rigid algorithms, that is why the positive effect of AI technologies for development of banking software is obvious”, summarized Anton Shebalkin.
According to Diasoft’s experts, the use of AI-based tools can help banks to solve a wide range of important tasks. They can significantly accelerate processing of large amounts of data without losing their quality, support quick business growth and scaling, etc. Each service based on Diasoft’s AI/ML platform can be seamlessly integrated into any IT landscape and with any existing bank system.