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Defend the threat of data outliers with visual analytics
Published by Gbaf News
Posted on May 3, 2018
11 min readLast updated: January 21, 2026
Global Banking and Finance Review
Company
Published by Gbaf News
Posted on May 3, 2018
11 min readLast updated: January 21, 2026
By Kim Minor, Global Director for Financial Services at Tableau Software
Overlooking one data outlier or experiencing a lapse in monitoring can expose you to risk. We all know that risk is inherent to the industry, but there are so many areas of exposure which hinders a bank’s ability to monitor and track with 100 percent confidence. A fraudulent payment could be processed or a loan decision could expose the bank to too much risk. These factors considered, speed to insight is more critical now than ever given how quickly businesses must operate. Adjusting in real time as business conditions change, allows banks that use robust visual analytics to catch the risk in flight.
Risks are inherent to a bank – credit, counterparty, liquidity, trade, payments and more. The number of teams also responsible for managing risks are many. From compliance and fraud management to lines of business leaders and product teams, none are immune to risk exposure. But self-service analytics puts the capability to monitor risk in the hands of everyone and it’s imperative that everyone uses the right platform to manage it. The good news is risk can also be proactively managed so that time and energy can be focused on the data outliers; the data points that could expose the organisation to tremendous risk. Those data outliers worry executives across the globe.
A March 2017 “Global Risk Management Survey” by Deloitte Insights reinforces that staying ahead of changing business needs and addressing threats from increasingly more sophisticated actors are top challenges for banking executives. The unfortunate truth is the one transaction that hasn’t been monitored or understood poses threat to brand reputation, customer loyalty and the bottom line. Layer on top of that a very low tolerance from consumers toward data breaches, and banks feel constantly on their toes trying to mitigate risk.
Unfortunately, fraud networks continue to get more sophisticated. Their ability to take advantage of the smallest opportunity has made headline names of many industry leaders. So, by accidentally overlooking a data set or getting too comfortable with metrics that are only based on subsets of the data, you chance being vulnerable to their attacks. And when those attacks are successful, customers and regulators will be close behind with increased scrutiny.
Modern business intelligence platforms that leverage the power of visual analytics to stress test for risk increases confidence in decision making and helps to lower costs. In fact, several financial institutions are recognising the importance of a visual analytics solution to increase confidence and responsiveness with risk assessment. For example, Jack Jia, Partner at EY, Hong Kong has benefitted from using such a solution to enable fraud detection and risk avoidance for clients: “In my day-to-day work, I use data. I need to visualise it so that I can identify the outliers and potential anomalies to identify fraud patterns for clients. And our clients use a lot of different data sources so having a solution to connect all these sources and predict fraud before it goes big, is very important.” In addition, E&Y uses visual analytics to identify outliers in trading patterns that may signal fraudulent behavior.
Robust visual analytics is also critical to running effective “what-if” scenarios to understand risk tolerances prior to decisions being made. For example, a bank should know at any point in time, the geographical dispersion of loans, the impact a natural disaster can have on loan repayment, the implications to counterparty risk, and the potential impact to liquidity. Visual analytics identifies the risk and can help form an offer that the bank provides their customer to minimise write-offs. Interactive dashboards provide the comprehensive, enterprise-wide view of risks that banks need to explore any data point–the needle in a haystack–while simultaneously providing the ability to run scenarios that analyse risk tolerance.
Once an exposed hole in risk monitoring is on the radar, and leadership addresses its impact, attention shifts to “how do I address this”. To help ensure minimal disruption, it’s important for top management to commit sufficient resources to advanced analytics and remove roadblocks like organisational silos or disconnected data sets that come with business divide. A McKinsey & Company article from June 2017, “Risk analytics enters its prime,[1]” also recommends that bank leaders keep teams focused on the value of high-priority risk use cases and encourage cross-functional expertise and cross-pollination of advanced analytic techniques. That’s where the flexibility and agility of a visual analytics solution proves invaluable–to generate insights for key stakeholders so they all can collaborate, understand and then take action.
New threats are bound to surface, and it’s anticipated that our accumulated digital universe of data sources will only grow with an expected increase from 4.4 to 44 trillion gigabytes by 2020, according to Banking Tech’s report on “Deriving Value from Big Data.” However, Alexander Graham Bell once said: “Before anything else, preparation is the key to success.” By wisely investing in a solution that optimises all of your data sources and accounts for the “what-if” situations, the looming threats of risk fade and you’ll find there is increased confidence in processes that have embedded risk. Analytically enhanced credit models, for instance, will improve your banks’ returns by lowering sales and operating costs, reducing relative risk costs and improving capital efficiency. Specific outputs include: more efficient underwriting, improved risk monitoring and early warning across product categories, and reduction of risk-weighted assets.
Like so many banks, you can also experience the power of advanced analytics to transform your business processes as needs change–whether that’s increasing collections recoveries, identifying and reviewing high-risk payments or capturing high-risk traders. When you put analytics in the hands of everyone, the opportunities are limitless as people see and better understand data.
Author bio:
Kim Minor is the Global Director for Financial Services at Tableau Software. She is responsible for strategic development of industry solutions across financial services. Prior to joining Tableau, Kim spent over 15 years in the industry, most recently working at IBM.
[1] McKinsey & Company, Risk Analytics Enters Its Prime, June 2017: https://www.mckinsey.com/business-functions/risk/our-insights/risk-analytics-enters-its-prime
By Kim Minor, Global Director for Financial Services at Tableau Software
Overlooking one data outlier or experiencing a lapse in monitoring can expose you to risk. We all know that risk is inherent to the industry, but there are so many areas of exposure which hinders a bank’s ability to monitor and track with 100 percent confidence. A fraudulent payment could be processed or a loan decision could expose the bank to too much risk. These factors considered, speed to insight is more critical now than ever given how quickly businesses must operate. Adjusting in real time as business conditions change, allows banks that use robust visual analytics to catch the risk in flight.
Risks are inherent to a bank – credit, counterparty, liquidity, trade, payments and more. The number of teams also responsible for managing risks are many. From compliance and fraud management to lines of business leaders and product teams, none are immune to risk exposure. But self-service analytics puts the capability to monitor risk in the hands of everyone and it’s imperative that everyone uses the right platform to manage it. The good news is risk can also be proactively managed so that time and energy can be focused on the data outliers; the data points that could expose the organisation to tremendous risk. Those data outliers worry executives across the globe.
A March 2017 “Global Risk Management Survey” by Deloitte Insights reinforces that staying ahead of changing business needs and addressing threats from increasingly more sophisticated actors are top challenges for banking executives. The unfortunate truth is the one transaction that hasn’t been monitored or understood poses threat to brand reputation, customer loyalty and the bottom line. Layer on top of that a very low tolerance from consumers toward data breaches, and banks feel constantly on their toes trying to mitigate risk.
Unfortunately, fraud networks continue to get more sophisticated. Their ability to take advantage of the smallest opportunity has made headline names of many industry leaders. So, by accidentally overlooking a data set or getting too comfortable with metrics that are only based on subsets of the data, you chance being vulnerable to their attacks. And when those attacks are successful, customers and regulators will be close behind with increased scrutiny.
Modern business intelligence platforms that leverage the power of visual analytics to stress test for risk increases confidence in decision making and helps to lower costs. In fact, several financial institutions are recognising the importance of a visual analytics solution to increase confidence and responsiveness with risk assessment. For example, Jack Jia, Partner at EY, Hong Kong has benefitted from using such a solution to enable fraud detection and risk avoidance for clients: “In my day-to-day work, I use data. I need to visualise it so that I can identify the outliers and potential anomalies to identify fraud patterns for clients. And our clients use a lot of different data sources so having a solution to connect all these sources and predict fraud before it goes big, is very important.” In addition, E&Y uses visual analytics to identify outliers in trading patterns that may signal fraudulent behavior.
Robust visual analytics is also critical to running effective “what-if” scenarios to understand risk tolerances prior to decisions being made. For example, a bank should know at any point in time, the geographical dispersion of loans, the impact a natural disaster can have on loan repayment, the implications to counterparty risk, and the potential impact to liquidity. Visual analytics identifies the risk and can help form an offer that the bank provides their customer to minimise write-offs. Interactive dashboards provide the comprehensive, enterprise-wide view of risks that banks need to explore any data point–the needle in a haystack–while simultaneously providing the ability to run scenarios that analyse risk tolerance.
Once an exposed hole in risk monitoring is on the radar, and leadership addresses its impact, attention shifts to “how do I address this”. To help ensure minimal disruption, it’s important for top management to commit sufficient resources to advanced analytics and remove roadblocks like organisational silos or disconnected data sets that come with business divide. A McKinsey & Company article from June 2017, “Risk analytics enters its prime,[1]” also recommends that bank leaders keep teams focused on the value of high-priority risk use cases and encourage cross-functional expertise and cross-pollination of advanced analytic techniques. That’s where the flexibility and agility of a visual analytics solution proves invaluable–to generate insights for key stakeholders so they all can collaborate, understand and then take action.
New threats are bound to surface, and it’s anticipated that our accumulated digital universe of data sources will only grow with an expected increase from 4.4 to 44 trillion gigabytes by 2020, according to Banking Tech’s report on “Deriving Value from Big Data.” However, Alexander Graham Bell once said: “Before anything else, preparation is the key to success.” By wisely investing in a solution that optimises all of your data sources and accounts for the “what-if” situations, the looming threats of risk fade and you’ll find there is increased confidence in processes that have embedded risk. Analytically enhanced credit models, for instance, will improve your banks’ returns by lowering sales and operating costs, reducing relative risk costs and improving capital efficiency. Specific outputs include: more efficient underwriting, improved risk monitoring and early warning across product categories, and reduction of risk-weighted assets.
Like so many banks, you can also experience the power of advanced analytics to transform your business processes as needs change–whether that’s increasing collections recoveries, identifying and reviewing high-risk payments or capturing high-risk traders. When you put analytics in the hands of everyone, the opportunities are limitless as people see and better understand data.
Author bio:
Kim Minor is the Global Director for Financial Services at Tableau Software. She is responsible for strategic development of industry solutions across financial services. Prior to joining Tableau, Kim spent over 15 years in the industry, most recently working at IBM.
[1] McKinsey & Company, Risk Analytics Enters Its Prime, June 2017: https://www.mckinsey.com/business-functions/risk/our-insights/risk-analytics-enters-its-prime
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