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As regulations proliferate and big data explodes, financial institutions are trying to figure out how they can use data to comply with new regulations. In my last post, I talked about the challenges and opportunities with data in the banking sector specifically. Here, we'll explore the regulatory compliance landscape as it exists today, as well as the modern solutions companies are using to thrive in that landscape.
In the aftermath of the 2008 financial crisis, both compliance and regulation have become significantly more robust. While the first changes were driven out of Europe and the U.S., this reform appeal has now reached a global scale.
As a result, we are seeing more stringent capital requirements, heightened consumer protection, greater market transparency, tightened risk controls and advanced operational risk management.
Connecting the dots across a global financial institution is a daunting task, and presents a costly and massive data challenge. To achieve compliance, financial institutions are examining ways to appease regulators, keep their tech debt under control, adhere and report in real time and improve their data and IT infrastructures. This means that data aggregation, transparency, lineage and security are all vitally important.
At the same time, unprecedented requirements have strained the ability of many institutions' existing systems. Legacy systems are too slow and expensive for performing deeper and faster compliance analysis. Instead of focusing on innovation, companies in this sector often find themselves funding defensive efforts in the name of compliance.
On a global level, large banks with more than $50 billion in assets have been classified as global and domestic systemically important banks (G-SIBs), which are banks or financial institutions whose failure might trigger a financial crisis. G-SIBs are determined by the Basel Committee on Banking Supervision (BCBS), an international supervisory group. The BCBS also created Basel III, an international regulatory framework which aims to strengthen the regulation, supervision and risk management of banks.
In the U.S., The 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act greatly expanded government power over banking and markets. The bill created the Financial Stability Oversight Council (FSOC) to monitor individual banks and identify and respond to emerging risks in the financial system. The Volcker Rule prohibits proprietary trading and sets new limits on how banks can invest in hedge funds and private equity funds.
In Europe, the General Data Protection Regulations (GDPR) will be imposed in May 2018. In Japan, the newly amended Act on the Protection of Personal Information (APPI) took full effect in May 2017. These statutes force financial services firms to treat personal data in entirely different ways. Whether such regulations will also open up new opportunities to better serve customers remains to be seen.
Regardless of the political climate, global compliance activity has increased substantially across all financial segments. Just as the private financial sector looks to leverage data, so do regulators.
Regulators are demanding greater transparency, detail and response from financial institutions. The following graphic gives a sense of some of the current regulations' central overlapping themes.
Risk and compliance have always been an integral part of the financial services industry. The current environment is hyper-focused on getting the data and infrastructure that's already in place to bring standards and transparency to the data that makes up the underpinnings of the world's view into the markets.
For example, banks typically apply point solutions and a large amount of manual reconciliation to manage risks. To address the inefficiencies in the process, many financial institutions are exploring a modern data platform that allows them to capture, store, and process all their data in one place.
These organizations are using a new data platform that interoperates with existing systems for retaining current applications and standard models while simultaneously adding new data advanced analytics such as machine learning to the mix to develop new applications for process automation.
Risk management is a central topic of the financial services industry. Essentially, risk is a range of possible outcomes that firms attempt to manage with oversight that is fed with data. Risk falls into three major segments:
In order to improve data, analytical and process approaches, companies must manage all three risk segments. And, to effectively manage those segments, companies must meet four fundamental needs:
A converged data platform allows financial institutions to tap into a pool of new data to analyze all types of risks, including credit risk, counter or third-party risk and even geopolitical risk. The data platform does this by running analytics on huge volumes of data, which requires massive parallel computing power. This results in faster, informed decisions.
So, while today's regulatory landscape may seem to harbor nearly insurmountable challenges, it's clear that converged data platforms offer companies a streamlined solution.
To learn more about how big data is changing the game for financial institutions, download our "MapR Industry Guide to Big Data in Financial Services" ebook now. And check out the our posts in this series here:
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