Two years ago, McKinsey reported that of the top 50 banks worldwide, 90 percent were already using advanced analytics to gain deeper insights into their processes, current customers, and potential markets.
Advanced analytics involves going beyond traditional business intelligence (BI) and applying technologies such as pattern matching, mining data from disparate sources, behavioral analysis, sentiment analysis, predictive and prescriptive analytics, use of machine learning, natural language processing, and forecasting. The insights generated help financial institutions reduce risk and cost by optimizing internal processes, preempting fraudulent transactions, identifying profitable customers and credit risks, and highlighting growth areas.
As the Financial Times neatly summarized, "Advanced analytics enables financial institutions to lend more and lose less."
Widening the Field of View
Machine learning enables vast amounts of data to be rapidly analyzed – not only traditional financial figures, but also customer interactions via text, touch screens, and voice and social media. This can be applied in the financial sector to identify anomalous behavior, which will expedite fraud detection, anti-money laundering, and anti-terror checks. It can also be used to improve customer engagement and satisfaction by increasing the accuracy and granularity of segmentation so that customers are offered financial products and services that suit their needs.
From the customer’s perspective, advanced analytics can be applied to reduce the time taken to make lending decisions and assist them in forecasting how much interest they are likely to receive from their savings and investments over the longer term. Every touch point on the customer journey generates data, which can be used to inform financial institutions about the customer’s current activity and probable financial requirements.
Data visualization is an essential part of advanced analytics, allowing financial decision-makers to quickly identify patterns and trends and take action. A great example of this is ExecView. Developed by First Rate Investments using our 3i data and analytics platform, ExecView helps to identify anomalies and brings underperforming portfolios into line, in compliance with MiFID II.
Digital Banking Depends on Analytics
A key factor in augmented analytics is the ability to handle data at scale. Information Builders’ 3i platform is built for scale and offers the best of both worlds: modern, cloud-based analytics technology backed by four decades of proven, mission-critical enterprise deployments. This is analogous to the position of our customers in the financial sector, where legacy IT infrastructure containing decades of transactional data works in tandem with new apps and interfaces. Whether they use virtual assistants or conversational AI, our customers are tapping into a whole new world of structured and unstructured data, and are identifying fresh trends, risks, and opportunities.
This is why nine of the ten largest US banks, five of the largest Canadian banks, and 83 percent of the largest financial institutions rely on Information Builders for data integration, data quality, BI, and advanced analytics.
Want to learn more? Download the Mastering Analytics webinar to see a demonstration of ExecView by Debra Detweiler, who is the product manager for reporting and analytics at First Rate. Listen as Debra, Jon M. Deutsch, vice president and global head of Financial Services at Information Builders, and Peter Walker, editor of FSTech, discuss how to use analytics to actively monitor accounts, spot anomalies, and comply with MiFID II.