Blog

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Business

We’re incredibly proud to share that we have been listed as a leading solution provider in the 2021 RegTech Buyers Guide! The RegTech 100 list identifies ‘the world’s most innovative tech solution providers that address the challenges of ever-increasing regulatory pressures within financial services.’ Each listed company was selected by panel of analysts and industry experts who voted from a longlist of over 1,000 companies produced by RegTech Analyst. This is the second year running that we have been featured as a leading vendor in the cybersecurity & data security category. A full list of the RegTech100 can be found at www.RegTech100.com.

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Business, Data insights, Large corporates, Use case

In the nine years since we started Think Evolve Solve, we've assisted enterprises across a variety of industries. Our team of engineers, mathematicians, developers and entrepreneurs has implemented a broad spectrum of solutions, from data strategy implementation to standing up advanced ML initiatives. No matter the solution, there has typically been one overarching reason why each organisation is looking to improve their data processes: digital transformation. The first step on our journey with a client is to share our unique perspective on how to put data at the core of this transformation. Most organisations looking at digital transformation start with the typical methodology of people, process, technology - by listing their assets in each area to understand how they need to transform. This method has one flaw - it's missing a view of the data assets. In today's world, an organisation's data is

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gather360, Use case

We've released a software! It's called gather360, and it offers a unique solution to a very familiar problem - ensuring good data quality. We started developing the tool after working on data quality solutions for clients in a range of industries over the past seven years. In each company we worked with, we saw data analysts doing repetitive and time-consuming work to clean and consolidate datasets they'd sourced from various systems, departments and external stakeholders. They were working with data they had already received, in the state that it had been sent to them, and doing much of the leg work to prepare it for use manually. We realised that if we sourced data differently, in a standardised, system managed way, we could drive huge efficiencies in this process and allow the data analysts to focus on data insights, not data preparation.