From legacy to leverage: why Data Modernisation is the next competitive edge in Financial Services

65% of British and Irish insurers have begun modernising the infrastructure of their core data systems. The other 35% are doing so within the year. (Insurance Times)

It is not a surprise that the entire industry is engaged in Data Modernisation. The threat of not doing so is as great as the opportunity that Modernisation offers.

Regulation and customer expectations are only getting more demanding. Meeting them keeps you competitive, and missing them will see you fall behind. Success depends on the agility, decision-making, and proactivity that only data can enable.

Making decisions and taking action

Modernised Data unlocks commercial opportunities in two segments - spotting opportunities and taking them.

Effective Analytics reveals patterns in data, like customer behaviour, that suggest potential for new products or services. Given that the foundation of the financial product itself will be in data, effective data management will allow you to bring the offering to market much more quickly and inexpensively.

Data-driven decision making is only truly effective and sustainable with Data Democratisation. If a team member needs to request help from a data team in order to access the information that they need, it will be frustrating for everyone involved, and may become a productivity drain for all. Levelling the data playing field with accessible data can solve that. Levels of data literacy will vary across teams and departments. Raising the floor of data literacy, and making tools more intuitive to use, will create a level of self-sufficiency with data, since everyone has programmes and methods they are comfortable using.

That means data specialists aren’t tied up with requests, and wider teams a can have and use data quicker. That means more time for work that adds value, and quicker, more effective decisions across departments.

Modernised Data reduces regulatory risk

The Financial Services sector handles considerably more sensitive data than most. Of course, with that comes the responsibility to know where it all is, what it is all used for, and who has access to it.

Failure to have that information means that data is less secure, and possibly non-compliant with data protection, FCA regulations, or other legal requirements. The answer is Data Governance — the practice of ensuring every piece of data is secure, accurate, available, and usable, wherever it is stored and however it is used. That takes a strategy encompassing people, process, data, and technology to instil a sense of data ownership of data, as well as formal responsibilities.

Modernised Data is fundamental to safe and successful AI

55% of AI use cases in Financial Services involve some automated decision-making. This is not a sector that can afford AI mishaps. If a chatbot offers some misleading or incorrect advice, if an automated application screener rejects a customer for the wrong reasons, or if an AI programme acts in a way that breaks financial rules, then the consequences are disastrous.

For example, imagine a retail bank has an automated screener for loan applications. The bank is keen to train its system as thoroughly as possible, and feeds it all data from all historical applications, successful and unsuccessful. If there is a pattern in that data, the system will notice it. For example, it could be that more often, successful applicants are a particular sex, or from a specific region. The system could then decide to automatically exclude applicants who don’t fit those criteria. It goes without saying that that is a regulatory disaster.

If the training data lacks completeness, or includes data that it shouldn’t, that bias is inevitable, and will eclipse the legitimate bias that the bank should use, like bias against poor credit scores.

Using data to build and protect the customer relationship

With the wealth of data and the digitalisation of customer relationships comes a level of expectation. Customer Services teams are expected to know the relevant details about an individual in a phone call. People expect that marketing will be relevant, and certainly they expect things like their name and title to be correct in any correspondence. If you cannot meet those expectations, then customers may very quickly become disillusioned. To them, those things are basics, and if you can’t get them right, then they may feel less inclined to trust you with their money.

Customer Master Data Management (MDM) is a strategic combination of culture, processes, and technology, to create and preserves a single, trustworthy data source for your teams. It is how you maintain a clear, accurate and up-to-date view of every customer, so that they feel treated like a person, not a number, and so that you can focus resources, messaging, and strategy around the opportunities that present themselves.

There are so many technologies, processes and platforms that promise to turn your organisation’s Data into gold, but in truth, it’s not that simple. Data is a valuable asset, and extracting that value is a journey, not a single step. To start turning your data and platforms into tools that make your teams’ lives easier, and that help rather than hinder initiatives and projects, download your copy of ‘Modernise, Manage, Monetise’, and get actions that you can take right now to unlock data’s power.

GUIDE | ‘Modernise, Manage, Monetise’: How to drive value from your data