Amanjeet Saluja, Director Analytics Services

1. Rising Analytics Requirements
Analytics awareness and requirements in the banking sector have increased manifold in recent years. Banks are striving to deploy analytics to varying extent within their businesses to make better business decisions using data and fact-based approach.

At the bare minimum, banks are looking at achieving ability to generate custom / ad-hoc reports without having significant time and resource overheads. Banks that are advanced on their “analytical maturity” are also asking for predictive capabilities using internal / external data.

2. Banks Not Fully Geared to Become “Analytics Driven” Organizations
There appear to be significant gaps in the bank’s ability to implement the above-mentioned strategic intent. I believe these gaps are primarily due to the following:

3. Outsourced Analytics Arrangements - A Good Alternative
Given these constraints, what are the options available to banks? One option that is emerging in recent times, that addresses all above-mentioned constraints, is utilizing 3rd party vendors for building analytics capabilities through outsourced analytics arrangements. Let’s see how it happens:

Vendors provide seamless remote analytics team (with onsite support as needed) on a dedicated basis for a pre-defined time period. These teams typically comprise of data analysts, statisticians and team leads who start working with the client managers directly with needed oversight from vendor senior management. In the beginning, team works closely with bank to lay down protocols of working together and to transfer knowledge related to data / business issues etc. from bank. In addition, during this stage, mechanisms of data access and extraction for the team are evaluated, discussed and laid out by technology groups of vendor and bank.

The team extracts data from multiple sources of bank’s environment (Alternatively, it accesses data within banks environment) and uploads on vendor’s existing analytics infrastructure. Typically, vendor’s infrastructure is capable of handling several terabytes of data to meet any kind of analytics needs. Further, the infrastructure allows the team to deploy wide array of analytics technologies / software for managing and mining data effectively.

The vendor team deploys proprietary methodologies to merge / purge, clean and append data to create integrated views of customer across timeframes and across multiple data sources. This is a critical step which consumes significant energies and time of the team upfront. However, once done effectively, this enables the team to perform any kind of ad-hoc analysis in the future without significant overheads. Post the initial, as we call, “data asset” creation, team keeps extracting/receiving fresh feeds of data with regular frequency which it diligently cleans and appends to existing integrated data.

As the relationship matures, vendor works more like a partner with the bank. Vendor brings in appropriate level of domain expertise as the bank requirements graduate from simpler reporting analysis to more complex business problems solving. Vendor also provides appropriate “swing capacity” to meet any short term surge requirements of the bank. Bank thus gets access to appropriate talent without significantly investing in the same (through hiring, training, staffing and retaining efforts).

With time, bank expands the scale and scope of this arrangement to cover multiple geographies or additional departments. This arrangement becomes like a virtual “shared service” organization for the bank without any overheads of managing the same. It enables every bank employee to assess data and analysis with the confidence that what she is seeing is the single and only version of information available in the organization. It thus enables more symmetrical distribution of real picture across the organization. Further, the larger scale of operations allows vendor to bring in appropriate discounting in the arrangement thus making it all the more cost-effective for the bank.

4. Significant Value Addition Through Outsourced Analytics Constructs
One can thus see how outsourced analytics construct addresses the earlier defined constraints of the bank. It is interesting to note that while enabling banks to manage those constraints, this construct adds significant tangible value on multiple dimensions viz.

My rough assessment shows that for a 100 people outsourced arrangement; the bank is likely to generate $11-12 Mn savings on an annualized basis as per the following:

Click to view Value Creation through Outsourced Analytics Construct

With such a significant value-add, it is not difficult to envisage outsourcing of analytics becoming a major priority for several banks in the near future. There will definitely be some speed breakers along the way when vendors find demand outstripping talent supply (it will interesting to see how they cope with the situation!) but the long term sustainability and the graduation of these contracts to larger scale is beyond any doubt in my mind. We will just have to wait and see it unfold for ourselves.