Our work at DataTick is relevant to most industries, but we focus on a few sectors whose challenges are aligned with our data and analytics services: 

Private Equity

If you have invested in a business with a goal of increasing its value over time before eventually selling the company at a profit, private equity data analytics is a critical tool.

Your due diligence process can be enhanced by analysing customer data, financial data, and product data by looking at history and trends, identifying issues through outliers, and identifying opportunities to scale. Rapid analysis of the underlying data can give you essential insights before investing.

Data and analytics create opportunities to maximise margins and release capital to pay off debt can be achieved through, such as through the analysis of employee productivity or supply-chain inefficiencies. Private equity data science is critical for identifying opportunities for where these savings can be made.

Optimisation of revenues can be achieved through the analysis of up-sell and cross-sell opportunities as well as customer profitability analysis, potentially using a single view of the customer, which in turn, improves customer satisfaction.

Automation of low value, repetitive tasks through the use of Private Equity AI can provide you with the opportunity to reduce your cost base.

These are the areas in which DataTick can provide expertise to help you scale your business. We specialise in quick wins to rapidly develop value and create impact so that the business being acquired understands what is expected. Want to learn more? Visit our recent blog on Quick Wins for more information.

Investment Banking

In investment banking, your work is dominated by regulation – the majority of which is data driven. BCBS 239 and Pillar 3 require firms to focus on the collection, management, and utilization of data to provide better reporting with a focus on transparency and accuracy. The pressure to build accurate models and the increase in data requirements only lead to greater challenges to business operations and risk management.

As regulation becomes more complex, businesses must reduce their cost base. Transformational cost initiatives must deliver results and data is critical to help identify where these opportunities lie.

The ability to cross sell products has become increasingly important to enable you to remain competitive. This strategy should be underpinned by a data modelling activity to identify cross-sell opportunities.

FinTech companies have disrupted the marketplace, so businesses must adapt quickly and efficiently to stay ahead. Data is one of the key ingredients of your digital solutions that enable you to deliver innovative products and services to your clients and that outcompete set you apart from competitor FinTech firms.

You will be under pressure to improve your adherence to AML and KYC and to remediate and streamline your procedures. The use of external data sets and AI can help significantly by ensuring greater success and efficiency of checking. 

Customer profitability is more critical than ever, and the use of data models will help you understand the short term and lifetime value of clients across geographies, products and complex client hierarchies.

The use of better, richer external data sources blended with internal data will provide you with a more detailed view of the marketplace and risks. In turn, this will provide new business opportunities and better client relationships.

 DataTick can help you across all data intensive areas, with significant experience in investment banking and relevant data and analytic techniques.

Retail banking

Even within the retail banking industry you will experience increasing competition from FinTech companies because they are data driven, offer innovative services, and adapt to changing market conditions fast.

As a result, retail banking customers can easily switch which makes it more difficult to retain customers. Customer retention is an area in which data modelling (data science) has been very successful in predicting which customers are most likely to churn.

Different customer data sets will reside across your business for different products (such as loans, current accounts, credit cards, mortgages, etc.), brands, and geographies. Combining these to create a single view of your customer will enable you to make better customer decisions for cross-selling, up-selling, and understanding customer profitability.

By having a single view of your customer (SCV), you automatically have better insights that enable you to sell the right products, target offers and innovate your products to suit their needs.

An SCV supports an omnichannel approach to customer communication. You will be able to provide a consistent, personalised service across all customer touchpoints,

Employee retention is more of a challenge with the Fintech firms that are hiring top talent – especially post-Covid where people are looking for new opportunities. Data and analytics play a major role in helping you retain these high-value employees.

DataTick can help you to leverage your data and analytics with all of these challenges and more.


Speciality insurance firms must evolve to remain competitive in the industry and meet shifting customer demands by ensuring their ability to process information through pricing, identifying risks, back-office processing, regulatory reporting, and claims. This requires better quality data, common data standards, and more accessible data. Most firms are limited in their ability to do this by their legacy systems, but the field of insurance data science is changing.

In the Lloyds marketplace, the advent of the Data Council set up by the LMG and the creation of a Core Data Record (CDR) also recognizes the value of data in this market led transformation. However, this creates a significant challenge for the brokers, underwriters, syndicates, and other firms, as they need to build out their own data capabilities. One of the key data components being developed is a data model.

The insurance industry is looking to develop new and relevant products, whether these are related to Covid, climate change, cybersecurity, or sustainability, and these all require new data sets for pricing and risk modelling. We expect to observe an increase in these insurance data models, allowing customers to integrate their own data to help them make decisions.

We’re seeing a move towards ‘open insurance,’ in which a customer can offer permission for the secure sharing of their financial information between organisations via application programming interfaces (APIs) – this open communication would allow for better, simpler, and more convenient services for the customer.

DataTick can help you to leverage your data and analytics with all these challenges and more.


Software firms are facing accelerated demands from customers, requiring faster responses to changes in market conditions, especially in relation to the proper processing, storage, and management of customer data. Partly driven by regulations such as the GDPR for personal data in the UK, software firms are certainly experiencing increased demands.

Organisations must consider data privacy laws during the development process rather than treating them as an afterthought. While data privacy has always been important, the regulatory landscape is becoming more complex as the issue is becoming more well-known and customers are starting to pay close attention to how companies use their information — and profit from it.

Data ethics is becoming a bigger issue as customers want to understand how information is being processed and how data decisions are made. Within a platform, is there always a debate about who owns the data? Does it belong to the customer or to the platform, and can the platform share data or not?

Business customers are demanding greater integration between platforms in their market ecosystems as well as within their own internal platforms. This leads to several challenges, including the development of APIs to exchange the data between platforms that require a standard data definition so that the platforms are speaking the same ‘language’.

As a software firm, you’ll also need to understand the chief data officer’s needs as a key stakeholder. They will have specific data demands relating to all things data that often require a different way of selling the product than what may have previously been purely functionality led.

Embedding AI capabilities in software have become common practice. This presents some challenges for software firms due to the ethics and explainability of AI activities.

DataTick can help you understand a CDOs perspective and ensure that your software solution is strategic data wise and for your customers..

Get in touch

If you need help understanding how to get the most value out of your data, get in touch with our experts by email or give us a call. We’re happy to help!