North Carolina, Michigan, and the Commonwealth of Kentucky are now using an enterprise approach - coupled with SAS analytics to model aberrant behavior - for a pre-payment fraud prevention approach, as opposed to the ineffective “pay and chase” strategies. For example:

• The North Carolina Financial Accountability and Compliance Technology System (NC FACTS) program was launched in 2012.  It is intended to develop and implement an enterprise fraud, waste, and improper payments detection program.
• Michigan’s Enterprise Fraud Detection System (EFDS) will initially integrate and analyze data from the Michigan Unemployment Insurance Agency and the state’s Departments of Human Services and Community Health.  Additional data sources will be added over time.
• In December, The Commonwealth of Kentucky licensed a SAS-hosted enterprise fraud solution to address fraud, waste and abuse around eligibility and claims for Medicaid; Supplemental Nutrition Assistance Program (SNAP); and Temporary Assistance for Needy Families (TANF).  It is anticipated that additional government programs will be added in the future.

Want to know more?  Be sure to read the white paper:  An Enterprise Approach to Fraud Detection and Prevention in Government Programs.

Some people handle these setbacks well. Others not so well. In my work, I’ve observed several common themes among those leaders who tend to cope particularly effectively with the inescapable.

Acknowledge the failure and put it in perspective. You can’t begin to bounce back from a mistake if you don’t admit you’ve made it. As obvious as it sounds, it’s clearly not always easy to do. Research shows that owning up to their mistakes is the key factor separating those who handle failure well from those who don’t. Those who were derailed perseverated and didn’t talk to others about it. They made little attempt to rectify the consequences. Those who weren’t derailed did the opposite: they admitted their mistakes, accepted responsibility, and then took steps to fix the problem. And afterward they proceeded to forget about it and move on.

One: Look for causes, not blame

If you’ve caused a problem, the good news is that you have control over that cause. By focusing on finding the cause(s) rather than assigning blame (with all the value judgments that go with that), you take control and move to prevent similar failures from happening again. Thinking in terms of causes rather than blame is similar to adopting what Carol Dweck describes as a “growth-oriented” rather than a “fixed” mindset. A fixed mindset tends to leave us helpless and ready to wilt in the face of a challenge. A growth mindset puts us in a position to press on toward success.

Two: Take a break

Before you wrack your brain to think up an appropriate response, take a break. Get away from the task at hand for a while and let your brain refocus. None of us is designed to work 24/7, but in the wake of failure, it’s often hard to stop thinking about what’s happened. As counterintuitive as it sounds, this is probably the last thing you should do. Engage in other pursuits. Spend time with loved ones, read, or simply get some rest. Physical activity is a plus (we’re all familiar with the effects of endorphins on brain activity). It doesn’t matter how long the break: five minutes, five hours, five days. The point is to let your mind wander. You’ll be amazed at what you come up with.

Three: Get some help

Feeling down is normal. Prolonged periods of depression and despair are not. If you find you can’t get into that growth-oriented mindset no matter how much of a break you take, find some way to express your feelings in the company of someone you trust. That could be a friend, a colleague, a mentor, or a therapist. There’s no shame in seeking help when you’ve suffered a setback. And therapy no longer carries the stigma of being damaged. To prove that, I’ll admit here that I’ve gone to therapy at times in my life when I’ve felt particularly down, and it has helped immensely. See, no stigma.

Four: Refocus, take action

Nothing will make you feel quite as good as taking action and finding even a modicum of success in that action. It may take some time to reach that success, but you certainly won’t have any until you start trying. One of the ways we feel better is to exert influence and control over a situation, and creating a plan of the actions we intend to take is a surefire way to start feeling that control. Create your plan and get specific about what you’ll do to reach your new goals. While you can’t change what’s happened, you have options for the future, and as you refocus your efforts, think about what would be best from this point forward.

No matter how you dice it, failing is a drag, and none of us likes it. Yet we all have to face it sometime. If you prepare yourself, and know how you will deal with it when you do fail, you’ll be able to bounce back that much faster.

Do you have tips that you can share that may help others recover from a setback? What is the risk you take when you don’t handle failure appropriately?

NOTE: Originally published by Harvard Business Review in 2012.  Copyright 2012 Harvard Business Review.  All rights reserved.  Reprinted by permission.

Globalisation has helped drive the growth of human trafficking by accelerating the speed of rural to urban migration and increasing the ease of global travel and communication.

Today human trafficking is big business, in many cases driven by far-reaching international criminal networks. Despite this, most countries have not deployed the kinds of large scale coordinated response efforts typically used to address terrorism or cybercrime, for example.

Unfortunately, while it is increasingly high-profile in the media and widely condemned in all civilised countries, human trafficking is a difficult problem to combat. So, how can crime fighting agencies, both within countries and on an international basis, be more proactive in gathering the necessary information and intelligence to investigate these crimes and bring the guilty to justice?

The first and most important priority is capturing relevant data in the most efficient and effective way possible.  Crime-fighting and investigative agencies will need access to systems that can help deliver information-sharing, information-gathering and intelligence management. They can then put in place analytics to detect suspicious patterns of behaviour while ensuring relevant data held by different agencies is widely available to all as actionable intelligence.

Their modelling and predictive analytics capabilities will need to help them build models that outline what unusual behaviour looks like and track the activities of suspects against that, making decisions about which individuals they decide to stop and search as a direct consequence.

Such is the complexity and scale of human trafficking networks. Taking a holistic approach is critical here. Often, arresting one individual or uncovering one location where people trafficking is taking place will be just a tiny part of the process. People trafficking is big business and agencies investigating it will need to understand the entire interconnected network of people to truly crack the problem. Ultimately, working together closely across national borders and delivering a joined-up approach to intelligence will be vital if this serious and rapidly growing criminal activity is to be effectively tackled.

Rather than requiring analysts to know precisely what to look for at any given moment, advanced analytics with built-in alert systems can be set up to proactively identify, prioritize and present information based on pattern identification and quantification of risk. Download this white paper for more information on how to tackle human trafficking with advanced analytics.

How much control do you have over the risks of your business?

Your answer to that question is very closely linked to the culture in which you grew up. If you’re an American or European, you’ll tend to feel (in varying degrees) that you have quite a lot of control. Risk is a specific “thing” capable of being sold to those who wish to carry it. The greater the control you have, the more finely you can judge the risk, and the more money you can make.

In consequence, your approach to managing risk will be very much inner-directed. You’ll rely as much as possible on decisions made internally, and you’ll feel most vulnerable to the decisions that competitors make. The risk calculus essentially revolves around the simple question: Who’s in charge here?

There’s a lot of literature about this, much of it dating back to the 1960s. A great deal of it was predicated on an assumption that American social norms and values were strongly correlated with modernization and economic growth. Risk events that could not be influenced by one’s choice of values and norms were simply random and could be managed through mathematical modeling. Good risk management, therefore, was about being American and having good math — at least until the Great Recession.

There is, however, a different school of thought. Asian cultures, in particular, assume they have a far lower degree of control over risk than do Americans and Europeans. In this alternative worldview, our fates are settled by outside forces, our knowledge of these forces is limited, and we expect to be surprised by patterns that are not in our personal control. These cultures tend to socialize risk by sharing hazards with as many other people as they can: customers, suppliers, employees, investors, the government, and the community. The parties involved do this because they believe that it is possible to sidestep the impact of unfavorable events provided that members of the ecosystem warn each other in time. Risk, in this environment, is outer-directed.

Both approaches have their strengths. In the early stages of an industrial revolution, it pays to be inner-directed. A pioneer could not do otherwise. Outer-direction in this context would be a form of fatalism. But as the world economy fills up with more competitors and more events move beyond our control, being part of a large industrial ecosystem starts becoming a competitive advantage. Partners who share your risks are unlikely to exploit or betray you.

It’s possible to measure quite precisely the degree to which a culture is inner- or outer-directed. Our firm has been tracking cultural differences among a sample of 100,000 managers in 100 countries over the last 25 years. In a recent survey, we asked them to rate their level of agreement with the following proposition: “What happens to me is my own responsibility.

The degree of agreement with this proposition for the 19 countries represented is shown in the following table:

There’s a big range — from an 89 percent agreement rate from New Zealand managers down to a mere 51 percent from Chinese managers. But it’s when you correlate these numbers with other data that you start to see interesting implications. Using forecasted levels of growth for 2012 published by The Economist, we can see that the nine most inner-directed nations average 0.8 percent growth, while the outer-directed nations average 3.2 percent growth — more than three times faster.

On the face of it, this is hardly a ringing endorsement for the risk culture of traditional Western capitalism, especially at a time when the global economy has become so interconnected and in view of the global environmental challenges already coming around the corner.

Download the white paper, The Art of Balancing Risk and Reward. This paper outlines the board’s role in setting, implementing and monitoring risk appetite – developing a risk culture from the top down.

NOTE: Originally published by Harvard Business Review in 2012.  Copyright 2012 Harvard Business Review.  All rights reserved.  Reprinted by permission.

In recent years, cyber threats have evolved beyond small-time hackers into coordinated attacks by organized cyber criminals. According to The Sydney Morning Herald, “cyber attacks and cyber espionage have for the first time supplanted terrorism as the top security threat facing the United States”.

According to the Herald, Army General Keith Alexander, head of the US military’s Cyber Command, predicts “the intensity and number of attacks will grow significantly throughout the year.” He said that cyber-attacks – particularly on the US banking sector – are getting worse. In fact, several major banks were recently targeted with coordinated Denial of Service (DoS) attacks.

Because of the increase in the number and severity of these attacks, many organizations have begun using advanced analytics and data visualization technologies to find cyber-crime activity and predict future attacks. These technologies help employees who aren’t data scientists or analysts to ask questions of the data – based on their own business expertise – to quickly and easily find patterns, spot inconsistencies, even get answers to questions they haven’t yet thought to ask.

The Navy Cyber Defense Operations Command is using data visualization to help defend the safety and security of the US Navy’s computer networks. These same capabilities are available for banks. Enormous amounts of network traffic data can be aggregated, manipulated, fused, visualized, processed and analyzed in a drag-and-drop interface. Sophisti­cated analyses can be performed quickly – even immediately – by people across all levels of your organization.

Using multiple types of analysis, alerts and other valuable intelligence can be created for anomaly detection and predictive analytics, and to investigate slow and low network intrusion. And the analytic models get smarter over time with learning and improvement cycles.

Analytics and data visualization gives a more complete picture of a bank’s systems and networks so that you can take a strategic approach to prioritizing resources and efforts instead of just plugging holes and fighting fires. These technological capabilities go well beyond business intelligence to provide data-driven information and analysis that is future directed, so decision makers can be proactive.  To make the data even more accessible, results can be delivered through multiple channels, including smart phones and iPads.

This new age of information overload might have caused a temporary setback for some, but others are now getting meaningful results – very quickly.

Left to right: Martha Jane Avstreih-Ross; Ann Woloszynski; James Miller

Big data is not about the velocity and variety of data; it’s about how you use the data to push your organization forward. When IT execs talk about big data, they say they have to start with baby steps; they have to get buy in from many areas of the organization. Martha Jane Avstreih-Ross, Ann Woloszynski and James Miller give some tips for getting both IT and executives on board with analytics implementations and data governance policies that will help the organization make the most of data – big or otherwise.

Avstreih-Ross is Vice President of Enterprise Decision Support Systems at RBS Citizens Financial Group. She heads the Enterprise Data Initiative for the Citizens. The initiative aims to establish core infrastructure and capabilities that will allow RBS Citizens to do analytics reporting and modeling in a consistent way.

She says to start at the beginning. Avstreih-Ross says that her team spends a lot of time on education before they even begin writing code. “We visualize what success looks like to us in order to implement: What are we going to do with the analytics?” She says, “This helped define our needs. At Citizens, we aligned around revenue expansion.”

Miller says that getting buy in “starts with the mission. IT is super aware of the mission and this is making them very successful.” Miller is Vice President of Enterprise Decision Support Systems at USAA. He says much of their success lies in their approach. IT used to be very disciplined about requesting requirements from the business units before starting the project. Now there is a business unit representative sitting alongside the IT representatives.”

In some cases, though, outside powers help get stakeholders on board. Woloszynski, Administrative Vice President of Enterprise Risk Management at M&T, says that getting buy in was very difficult before CCAR Comprehensive Capital Analysis and Review). “The requirements of the regulation meant that M&T needed to move quickly. So executives were no longer questioning why we were interested in analytics.”

She says that it can often be good to show results from the “fire drills” as examples of how analytics can help master other big data issues in the organization.

Other tips:

• Promote the idea that data governance is a responsibility.
• Be careful that you don’t push too hard; this can turn data governance into a dirty word.
• Find a champion who can generate some awareness from the top.
• Present tangible  results from other implementations, such as regulatory reporting, to help execs see the need in other areas of the organization.

Final advice from Miller: Business cycles are shorter now, so IT is trying to deliver within a couple of days. He suggests setting up a business intelligence lab to allow executives to experiment. This lab can help gather future requirements and create a sense of inclusion, ownership.

IT has the opportunity to not only drive business value but truly lead the organization. Read more about how you can help your organization can use data to be more competitive.

Can you predict the future? Or more accurately, can you predict a likely tax fraud or evasion before it is committed? As governments across the world seek to boost and protect their revenue streams, predictive analytics is proving a huge business asset.

Predictive analytics is helping tax agencies find ways to get individuals and businesses to pay the tax they owe and to minimise welfare fraud and error. It’s about using statistical analysis to identify and understand new methods of fraud. It helps to spot connections, such as between a tax professional and taxpayers using the same avoidance vehicles. And it matches data in order to look at the complete view of a taxpayer’s position, linking multiple tax data and external data sources.

Predictive analytics is clever stuff. It is already being used by a number of agencies worldwide to identify and stop common activities that transcend borders and boundaries. These include: under-declared income, abuse of company status, false information by welfare claimants, identity theft and VAT repayment fraud.

Using analytics-based solutions, agencies can quickly turn billions of data points into powerful insights. It’s an approach we’ve taken at Capgemini in our technology partnership with SAS. We’ve developed analytics-based solutions enabling agencies to understand the characteristics of a fraud and automate vast amounts of complex analysis, using data from different internal systems linked to external sources.

Our clients are embedding predictive analytics in their risk profiling. They’re using sophisticated analytical techniques, such as social network analysis. Using analytics to assess risk, unearth evidence of possible non- compliance or fraud, and select cases for investigation allows resources to be focused on the cases that bring the highest return.

Predictive analytics is already flagging and stopping high-risk transactions at the point of interaction with the taxpayer or welfare recipient for a number of our clients. This is what success looks like in today’s tax and welfare agency.

For more information about reducing tax fraud and evasion and increasing tax revenue, read my blog or contact me directly with your questions.

While the constant talk about budget cuts might have the feel of a scratched record, we can’t escape the reality of today’s straitened economic circumstances. But there is something that tax and welfare agencies can do to lessen the impact. A bold statement perhaps, but nonetheless accurate.

With an increasing need to fund the welfare state in G20 countries, we know that cutting costs is no longer enough. Governments must protect their revenue streams. Tax avoidance and error costs 145 countries, representing over 98 percent of world GDP, more than US$3.1 trillion annually.

We’re already seeing a number of tax agencies getting a grip on this. How? By using data to help identify tax evaders and tell the difference between genuine error and criminal intent.

At its simplest level, let’s consider a taxpayer who declares an income of $40,000 a year. With the right technology and processes in place, it’s possible to match his tax return against data from other government agencies, credit reference agencies, or publicly available registries. These might provide us with lifestyle indicators suggesting that he possesses properties abroad and a high-spec car – way beyond the reach of a $40,000 salary.

This has become a reality in the UK where tax agency HM Revenue & Customs (HMRC) is among those already using analytics to get tax yield success.

Capgemini delivered HMRC’s award-winning strategic risking system “Connect”, which takes information from 30 different data sources, cross-matches one billion internal and third party data items, and uncovers hidden relationships across organisations, customers and their associated data links (bank interest, lifestyle indicators and stated tax liability). The solution, which includes data analysis and data mining products and tools from SAS, underpins HMRC’s ability to focus skilled resources on businesses, individuals and sectors that pose the highest risk of error, fraud and criminal activity.

The result? HMRC has already recovered over £1.4bn in additional tax yield. That’s surely an eye opener for other agencies seeking to deliver new capabilities that protect tax yield and reduce welfare benefit evasion.

For more information about reducing tax fraud and evasion and increasing tax revenue, read my blog or contact me directly with your questions.

Social media has proved a driving force behind these revolutions and has had a key role to play in stirring entire nations to action. It is far from certain that the events in Tunisia, Egypt and Bahrain would have occurred without the presence of Facebook and Twitter. Equally, it is likely that if the undemocratic governments in place in those countries had appreciated the power of these sites, they would have tried to censor and control them as the communist regime in China has done.

The riots that broke out in the UK during Summer 2011 also clearly demonstrated the power of social media as a force for mass action even if this time it was to organize looting, arson and criminal damage rather than to fight for social and political freedom. Social media played a key role in helping to incite the violence and to coordinate the activities of the rioters. BlackBerry Messenger became the rioters’ most powerful weapon, helping them to target, move and attack ‘en masse’, leaving the Police trailing behind for three nights in a row.

Looking for the right response

What all of these events have illustrated is the power of social media to co-ordinate and drive large groups of people into action and the difficulties that governments, police and intelligence services often have in combating these social media driven movements.

So, in the battle to maintain law and order is the only answer government control of social media channels? No. Public security professionals around the world need to stop seeing social media as the problem and start tapping into it as part of the solution. In the fight against antisocial criminals, organised crime and terrorists alike, social media can be law enforcement’s most powerful weapon.

Initially their efforts were focused on tracking criminals and terrorist suspects directly; on monitoring known sites used by criminals to communicate with and educate one another (the so-called Black Web). This type of tactic has an important role to play in police investigations. However, police also need to be tracking social media activity more widely to pick up on trends and shifts in sentiment, for example.

As we learned after the terrible events of the July 2011 massacre in Norway, Anders Behring Breivik was an avid social media user. He used the Web to propagate his abhorrent beliefs and gave very clear indications as to his intended actions. Breivik was known to authorities as a potential threat and was active in extremist circles. So why wasn’t he being monitored? The painful truth is that he is only one of thousands, perhaps millions, of individuals across the globe who pose a potential threat to the world’s law-abiding citizens and police often don’t have sufficient resources to monitor them all

A clearer picture

This is where technology has a key role to play. Analytics technology can help with these processes. Text analytics technologies can now pore over huge amounts of social media information to uncover patterns and analyse content. Social media analytics can continuously monitor online data to identify important topics and content categories and build links to understand certain networks of individuals. Finally sentiment analytics can assess and monitor the sentiment of text to flag changing attitudes that may signal a shift from words to action. Allowing the technology to do the monitoring frees resources to intervene when an increased threat is identified.

Ultimately, in times of financial austerity, public service agencies can’t just increase their resources to ensure social media is being appropriately monitored for threats. They need to use those resources more smartly and free them up to act on intelligence – not be bogged down by sifting through information. Most importantly they need to use technology wisely to extract actionable intelligence from mass social media data.

A lot of what Solvency II addresses is improving transparency across the firm, between the firm and its regulators, and with the customer. For instance, very often, the business has no continuous, organization-wide view of risk and struggles to clearly and consistently explain the source and reliability of its data. For example, if a business user changes the data, the process of transparently sharing information breaks down no matter how effective the IT control.

There is little to no traceability of data flows to reassure IT and provide automatic documentation. And data quality is not always embedded into data management processes, meaning there is limited monitoring and reporting of data quality. And even with access to reporting, there is no clear ownership of specific data or a process to resolve identified issues. Most organizations have minimal data governance, almost no focus on data quality and very little collaboration between IT and business units. This can reduce the firm’s view of its true exposure. 

Clear path to data quality

There are six data quality process steps that SAS recommends to support Solvency II initiatives, increase transparency and establish reliable data governance and monitoring. Run the steps iteratively (in a full cycle) and often. The steps are broken into three stages – plan, act and monitor.

Plan:

Step 1 – Define the Solvency II business terms and define the data sources you will use.

Step 2 – Conduct data profiling to discover what your current data contains.

Act:

Step 3 – Design business rules for checking your data to ensure it is valid and complete.

Step 4 – Execute your business rules by embedding the services and rules they use into your operational systems and data integration processes. .

Monitor:

Step 5 – Measure and monitor the actual state of your data against what is expected and how it trends over time. Trigger tasks to improve your data as needed.

Step 6 – Make the required updates and improvements to your data, systems and processes to make things better.

There will be many resources at work on this process from both the IT and business side – oftentimes a recipe for stress and friction. To take advantage of the array of skills, knowledge and responsibility of each, understand where your barriers are so that all can work to remove them. This will ensure a seamless handover of responsibility and a more collaborative environment.

You can find more information about how data management impacts your organization and its Solvency II implementation in this free white paper: Download Data Management and Solvency II: A Critical Partnership.