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Financial institutions are engaged in a constant battle to fight money laundering, bribery, fraud, terrorist financing and corruption and adhere to sanctions levied against countries and individuals. And financial crime takes a massive toll – it puts global financial systems at risk, it negatively impacts economic growth and causes massive losses to companies and people. It’s been estimated that annually, it costs the global economy as much as $2.1 trillion.
With the incidence of financial crime continuing to escalate, it’s vital the focus remains on putting the right solutions and processes in place to fight it. After all, anti-financial crime processes are not only necessary from a business and reputational perspective – they are a regulatory imperative. Financial institutions – and in some cases, individuals – can be held criminally accountable for not adhering to financial crime regulations.
The regulatory environment and the complexity of the financial system means that vast quantities of data are produced, but manual processes and legacy banking systems mean many organisations often struggle to cope with these large data volumes.
But the answer to mitigating the risks of financial crime lies in being able to manage and use this data in the right way. Data engineering, data science and cloud engineering all have an important role to play in optimising the way organisations use data.
With global spend on financial crime prevention expected to exceed $28bn by 2027, these are three vital components of a successful financial crime approach:
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Roman Eloshvili Founder and CEO at XData Group
02 August
Konstantin Rabin Head of Marketing at Kontomatik
Denys Boiko Founder at Erglis
01 August
Michael Zetser CEO at Flyfish
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