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One of the most challenging and complex elements of operating a financial services institution is compliance. Managing risk, security and privacy to earn customers’ trust has long been at the core of financial services, but this foundation has been shaken over recent years. A series of major incidences of fraud and compliance violations – such as the Nordic Laundromat scandal, which exposed several Nordic banks as part of billion-dollar Russian money laundering schemes – have eroded trust in the industry.
The cost of non-compliance is steep, both literally and figuratively. In the first six months of 2020 alone, banks were hit with $5.6 billion in fines globally, but institutions exposed for failing to comply to regulations also gamble with an even more valuable asset – their reputation. With the list of regulations growing longer and the stakes getting higher, the industry must change the way it goes about compliance by adopting an intelligent, data-driven approach.
Regulators today expect quantifiable evidence demonstrating that a bank can effectively manage financial crime risk. They’re not just looking for assurances, they’re demanding data as proof. While compliance issues are, to an extent, inevitable, and regulators acknowledge this, they expect institutions to not only demonstrate that they can quickly identify risks but that they can also tackle them swiftly and effectively. Data is a bank’s most powerful asset, but only if it can be accessed and analysed quickly or in real time, and transformed into actionable insights. Herein lies their first challenge.
Banks are swimming in data, or perhaps drowning is more of an apt metaphor because unfortunately many are so overwhelmed by it that they struggle to derive value. One reason for this is the very nature of the organisations themselves. With different departments and teams working in siloes across the company, each creating and running their own applications, companies end up with data growing stagnant. Crucial to enabling data-driven compliance is breaking down these siloes to enable one single pane of view where all data from across the business can be collected, cleaned, integrated and accessed in real-time.
So, how can this be done? Well first of all, it’s vital to make sure an organisation has full control over their data. That means looking at internal and external data - structured, unstructured and semi-structured. While this may sound straightforward enough in principle, in practice this is where most organisations are still missing out. According to Harvard Business Review, less than 50% of structured data is used for decision-making, while only an even more shocking 1% of unstructured data is used at all, which is concerning when we consider that around 80% of the data landscape today consists of unstructured data. So organisations must get control over their unstructured data and the key to doing that is transforming it into metadata.
Take a voice recording as a classic example of unstructured data. While a recording file could be named and perhaps have certain limited attributes assigned to it, such as the date it was created or when it was last accessed, the actual contents of the recording are a mystery. But if we were to translate that voice recording into cleartext and attach this to the file, suddenly you have metadata that can be easily searched for.
Collect, connect and integrate
Our financial services customers often tell us they have disconnected data sources that make it hard to understand their risk position. These customers often use manual labour to search for and find data, clean it and prepare it for the compliance team but a centralised, self-service portal presents a far more efficient, and cost-effective, approach.
That’s why Hitachi partnered with FTI Consulting to help customers shift their approach towards data-driven compliance. We’ve created a blueprint that customers can apply to their existing environments, leveraging their own tools, as well as additional ones we recommend, to create their own complete solution.
Our approach starts with looking at the way the company collects, connects and integrates data from all over the business. We can work with them to build a custom user interface for their internal migration team, which they can then use to set business rules and control who can access data before it is migrated into the platform.
But to do this at both speed and scale, our process leverages AI. Imagine a banking customer with multiple different applications linked to them – a bank account application, a loan application and maybe an insurance application, for example. Their personal details will appear in each of these different applications and because they were likely created in different departments each will have a different data structure. To unify this data and avoid duplications, AI should be implemented to qualify the data, merge it together and feed it back into the system as one unified data set without slowing down performance. This speed is critical to generate real-time insights.
Make money, save money and earn trust
A few years ago, we had a global customer who told us they spent around $250,000 a month to have an external team come in and search for their data, clean it and put into a report documenting their MiFID II compliance. All that was spent on compliance for just one regulation, but imagine if that bank had hundreds of regulations to follow. Once a self-service system is up and running, all of this labour can be done internally, eliminating the need for a whole team to do the manual work while also removing human-error.
But more than just saving on time and costs, bringing automation into the compliance process and more effectively harnessing data is crucial to mitigate many of the issues that enabled crises like the Nordic Laundromat scandal to occur. It’s no wonder why, this year, compliance accounts for 17.5% of IT spending in the Nordics. To remain competitive and earn the trust of customers and regulators alike, the financial services industry must finally master its data and transform modern compliance.