Enhancing Compliance & Oprisk Management through Analytics

Post the financial crisis, banks in the US have faced increased regulatory scrutiny that has resulted in broader and tougher regulations. Bankers are fully aware of the investments and efforts they have to put in to comply with these regulations. Consequently, compliance function in banks is evolving towards a broader risk canvas that is now seeking tighter coordination between the first and second lines of defense. This poses new challenges to banks – from being compliant to getting the optimal returns from their investments.  The million dollar question on everybody’s minds is  - How are banks rising up to this challenge?

Recent studies have highlighted the enormity of the challenge this has created for banks. For example one study by Accenture shows that 92% of banks will be compelled to increase their compliance spend in 2014. In another report by Continuity Control, the new regulations have imposed an additional financial burden for just the last quarter (Q4) of 2014 is $241 million.

Enhanced regulatory scrutiny may be a necessary evil to watch over the much-maligned banking sector, but has spawned its own unintended consequences.  The huge anxiety of banks to be compliant and avoid penalties and the resulting hike in compliance spend has and will continue to impact ROE and profitability of US banks for years to come.

How are banks responding? A whole ecosystem of changes is taking place in this area.  Banks are deploying analytics to help them meet the challenge and enable them to make the right data driven decisions. Three important changes are on their way.

 First, bulk of the new spend has gone towards upgrading technology platforms. Banks are integrating extant analytical and compliance platforms so they can deploy data mining and analytics to get the right insights.  For example, analytical models are being deployed to proactively identify and monitor UDAAP compliance in customer engagements / acquisition.

Second, Banks are bringing new structural alignment between first and second lines of defense.  Compliance is now a broad based enterprise activity that will report to the Board or CEO and will include operational and business risk professionals. This is a significant change because in my view, it facilitates wider & deeper use of analytics to help banks stay compliant and out of regulatory trouble.

Third, data silos – the usual suspects - are posing roadblocks for banks in their new quest to be compliant. Incorporating structured and unstructured data for analytics is also an urgent initiative at banks. Banks are aware of these challenges - these are known devils anyway for some time now; but a renewed urgency backed by fat budget approvals is evident.

Banks need to keep a watchful eye on the expanding compliance management function. Technology upgrade and structural changes, while necessary, are only part of the solution and not a panacea by themselves. Banks need to look at compliance as an enterprise wide culture that every associate lives by 24/7. In an era where changes are swift, where disruptive innovations are continuous and almost a way of life, the best insurance for the banks is an open mind to change and adapt to win the customers’ heart. In a way, it is the same old wine, but in a new fancy carboy.

Analytics Revolution - Why the struggle for growth?

IT majors have been excited about the convergence of Social, Cloud, Analytics and Mobility (SCAM).  It is widely believed that these will be the engines of growth in the future. Rightly so. N Chandrasekaran, CEO of TCS, India’s largest technology services provider, recently referred to the SCAM as "digital forces" and estimates that these digital forces would be a $3-5 billion opportunity in the next few years.  A Gartner study has reported that the SCAM market will be worth $107 billion by 2017.

It is true that Analytics - has generated excitement all around. Everyone can see and experience the impact that this convergence – that engenders Disruptive Innovations  - has on everyone’s life. I personally think that the hype is real and the huge revenue opportunity projected for this market space is based on solid grounds.

What the TCS Chief has not mentioned is that there are significant white spaces – industry-speak for critical gaps and blind spots in the effort to get this revenue. And the fumble, too, is very real. For example, if these projections and forecasts can be translated into revenue, why are we not seeing a Google or a Facebook or even their dwarfs in pure play Analytics?  There appear to be several reasons why IT majors have not been able to take advantage of the opportunities. The revenue is for them to lose unless they learn and take corrective action quickly.

Analytics business is a domain specific, hands-on and a devilish details game where domain expertise is all supreme. However, most global players have not been able to get the right folks to lead the practice. This has proved to be a disastrous non-starter. The problem is also compounded by lack of right skills in the marketplace. The analytics practices at the majors continue to be led by professionals who either have consulting or technology background but weak in hands-on analytics. This has blissfully insulated the practice from the analytic humdrum that businesses are experiencing. This is also reflected in the inability to identify or devise the right vehicle to exploit the surging analytic opportunities. In my view, the lack of appropriate leadership is a major roadblock to growth.

The IT majors also urgently need to revisit the internal business structure. The bunching of analytics catering to different industry segments or verticals under a single business unit may be convenient for administrative and bureaucratic reasons, but has not produced optimal results. This agglutination has come in the way of insight dominance since successful thought leadership in one vertical often has not passed muster at another. I think the analytics practice catering to each industry vertical must be a separate business unit by itself.

The outsourcing industry has mastered the art of building the business via the IT organizations of client companies. However this tested path has not helped build the Analytics business because the key players are not on the IT organization of clients. Outsources need to have a game plan for directly engaging the business side of the house.

Further the majors they are selling software products and tools that are often peripheral and non-core to generating analytical insights. Aided by an expanded definition of analytics, this may help generate revenue in the short run, but this has taken the focus off the insights business.  For example, a hypothetical solution that can build and deliver fraud detection models using large attribute set – including social media attributes – and look-up more than 10,000 datasets and yet instantly deliver accurate detections will be immensely popular.

Big data or new modeling techniques by themselves would not produce a disruptive innovation. The marriage of cutting edge technology and the resulting new innovative analytical techniques that can scale is the winning recipe. This is a keystone for success in analytics practice, yet conspicuous by its absence.

This success recipe has to be combined with a smart go to market strategy. I call it winning-with-a-thousand-cuts strategy. Instead of waiting for the dream multi-million, multi-year project, the focus must shift to building volumes through a huge portfolio of mid-sized projects. Execute several small to medium sized projects that will provide insights to the businesses in short to medium term - 6 to 12 month time frame. This paradigm has the potential for depth - to open up opportunities in every line of business, business unit or team level at clients and hence build scale in the analytics business.

Power of Analytics

I was reading this book “Competing on Analytics –The new science of winning”; It is a must-read for number crunchers and ambitious bankers in particular. The authors (Davenport & Harris) have delightfully brought out how analytics can turn a company into a winner. According to the authors (Davenport & Harris) the following four factors are vital for successful “analytical companies”

Supports a strategic capability

Enterprise wide

Commitment of senior management

Company makes a strategic bet on analytics

Analytics – as any number-cruncher knows – has always played a key role in decision making in banks and financial services. It is not something new. However, more and more companies are leveraging this today to propel themselves into big league.

The obvious example of use of analytics in banks and financial services is in the development of custom scorecards to predict default. The larger banks have dedicated “decision sciences” teams to handle this. While smaller banks buy credit scores from the credit bureaus, the larger banks develop and deploy a  wide array of  score cards that are designed to serve specific business purposes.

But the larger more prevalent deployment of analytics is in performing ad-hoc analytics to find answers to specific business problems. These vary in complexity and the type of problems they are trying to address.

For example credit risk departments in retail banks have used the power of analytics in approving/providing lines of credit to customers.  In making these loan decisions, banks usually compute debt to income ratios, number of other loans, regularity of repayments, any unpaid and past due loans,  membership on rewards databases, loyalty to the bank etc.  to help make prudent credit decisions.

Marketing also is a key user of analytics. An example is how banks monitor existing customers who shop to refinance their mortgage or auto loans. This is helped by “triggers” from credit bureaus. So if you have your home mortgage financed by bank A but would like to shop for better rates, Bank A will get a trigger from the credit bureaus that your credit was pulled by Bank B;  Now Bank A , using analytics can and provide a counter offer to you.

Technology impact on analytics

Analytics is now helped in a big way by new developments in IT and Business Intelligence. The new buzz words in technology - Big Data, Cloud, Social media & Mobility have greatly impacted analytics.  For example new BI tools that leverage the 64-bit architecture can help process huge volumes of data in-memory that has not been possible earlier. This enhances the speed and depth of analytics.  

Mobility adds a key dimension to delivery of analytics. It can now reach top management 24/7. The iPad is rapidly changing board meetings by providing depth and ease to business leaders. New visual analytical tools can help managers perform scenario analysis during meeting and provide useful insights almost instantaneously.

Social media analytics is now emerging as a new discipline by itself. For example bankers are finding out that people with similar credit risk “like” similar friends on Facebook.  While this definitely needs more empirical data to be broadly accepted, it is making significant inroads and will be closely watched in the coming months.

The US economy is slowly emerging from recession.  I think analytics will be a key player in helping Banks to find their way back to profitability.