How Ablera’s ABACUS Helps Insurance Companies Save Time and Boost Revenues

Bulgarian company Ablera recently enhanced its AI-powered ABACUS solution in order to bring next level speed and accuracy in insurance tech processes, minimizing the error-prone, cumbersome manual efforts and allowing a wider range of users to work with applied mathematics.

By working together with technology provider ALSO Bulgaria, Ablera has now added ML algorithms to the commonly used generalized linear models (GLM), which allows ABACUS to use a wider range of risk factors.

To infuse AI in their solution Ablera used the ALSO-provided IBM Watson Studio, a leading data science and machine learning solution that helps enterprises accelerate AI-powered digital transformation.

The Bulgarian company will discuss its collaboration with IBM and the work on the ABACUS product at the ALSO’s Tech2Scale event on December 12 at Flex-R lounge at the Sofia Airport Center. The event aims to help companies utilize the tech provider’s expert guidance in how to scale their B2B startups, while learning how to build and market their solutions.

Additionally, ALSO will share how IBM’s integrated technologies and services can give startups the tools to build a stronger and more innovative business, and hear experts opinion on the topic from special guests and household names such as Filip Genov, Svilena Stoyanova, Mila Taneva and Georgi Sidjimkov.

So far, ABACUS has been leveraging IBM Watson Studio to bring game-changing technological innovations in redefining and optimizing insurance companies’ pricing and rating processes, highly adaptive to any legacy system and easy to integrate with any external one.

Improved personalization and instant implementation for insurance companies

The IBM Watson Studio has also enabled companies to build, run, and manage AI models on any cloud through an automated end-to-end AI lifecycle – simplifying experimentation and deployment, speeding up data exploration and preparation, and improving model development and training.

A key benefit for ABACUS users is the improved personalization due to the increased number of risk segments, as well as the reduced time for completion of both pricing and rating processes, from three months to just 5 days.

An additional key advancement is that customers using ABACUS can now receive an increased net profit, 60% less actuarial effort and 100% less IT effort for Rating setup and configuration. It also allows the governance and monitoring of models to mitigate drift and bias and manage model risk, thus driving trust across the AI lifecycle.

Fostering synergy between industry leaders

Ablera recently partnered up with the IBM Client Engineering team in Central and Eastern Europe to co-create a Minimum Viable Product (MVP) for ABACUS in four weeks. The team brought a deeply skilled multi-disciplinary squad, technical accelerators and proven methodology to co-create ABACUS that insurance companies could implement instantly after the MVP completion.

The IBM Client Engineering is an investment by IBM to jointly innovate and rapidly prove solutions to clients’ and partners’ business opportunities by leveraging IBM hybrid cloud and AI technologies.

Ablera has already won the prestigious award for Technology at the International forum in Dubai for their outstanding work on creating ABACUS. In addition, the Bulgarian company also won the Start-up Technology Award for their innovative solution transforming the processes in insurance companies, at the 5th edition of the prestigious Golden Shield Excellence Awards.

Ablera’s core team has more than 25 years of experience in developing Insurtech solutions and its team is currently enriched with a strong group of AI/ML engineers.

The ALSO Holding is one of the leading technology providers for the ICT industry, currently active in 28 countries in Europe and in a total of 143 countries worldwide via PaaS partners, with its ecosystem offering around 120.000 resellers hardware, software and IT services from more than 700 vendors in over 1450 product categories.