This article was originally published on Grit Daily and is reproduced with permission.
The financial crisis of 2007 – 2008 resulted in marked changes to the institutional financial sector landscape. Weaknesses were brought to light and financial institutions were forced to reevaluate how they were managing data and restructure as a result. Then 2020 brought with it a global pandemic, which further spurred the need for digital transformation.
As the business of financial intermediation enters the post-internet era, shifts in the business models and strategies of large financial institutions continue to take place.
Recognizing the need to streamline processes in order to drive efficiencies and accuracies at some of the world’s largest financial services institutions, AI-powered data control platform like EZOPS, where I am the CEO and co-founder, provide a solution that leverages Machine Learning and AI to automate validation, compliance, and reconciliation. The result: accelerated productivity, optimized resources, and heightened efficiency.
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The Need for Change
Driven by the global pandemic, regulation, technology, and changing demographics, the capital markets business has morphed to balance capital constraints, risk exposure, product mix, and delivery mechanisms.
The operational and technical infrastructures that were built to support pre-crisis business complexity, volumes, and regulatory reporting are proving to be costly to maintain and yield unfavorable business value.
Smart Software Offers Data Control Solutions
AI allows large financial institutions to manage data across business functions by harnessing the power of Machine Learning. In addition to intelligent process automation to revolutionize data control and drive transformative efficiency gains.
Source: Image by ipopba on Adobe Stock
Automation and Accuracy
AI-enabled software, like EZOPS, intelligently automates repeatable actions, checks for errors, and offers insights that users might miss on their own. It can detect, predict root cause, and resolve data anomalies without the need for manual research and remediation. Data can be easily aggregated and analyzed to create sharable reports and insights.
AI Ahead of the Curve
Some of the world’s top tier banks are already tapping into AI-enabled data control to reconcile complex assets like Total Equity, CFDs, Futures, Options, and Bank Loans. BNY Mellon utilizes AI to identify opportunities for automation within break identification/classification, break research and validation, and break resolution. Additionally, Wells Fargo depends on AI to automate and improve efficiencies in the credit card and mortgage reconciliation space.
The Future of Data Control
The future is smart software that is modular, adaptable, and tailor-fit for financial services. AI-enabled data control platforms offer comprehensive functionality that businesses of large scale and complexity need in order to manage the four pillars of operational data control – reconciliation, research, remediation, and reporting – all powered by Machine Learning and smart workflow management.
As financial institutions continue to reassess, restructure, and digitize, AI delivers an intelligent solution that maximizes data control.
