Getting change management right

 With the rapid pace of change and speed of digital transformation in the post Covid world, banks need to ensure that change management processes are robust and address all aspects need to bring about the change.Consider the following from a McKinsey survey:Only 14% said they had realized significant performance improvements with these efforts.Only 3% said they had successfully sustained any changesNo wonder executives are sick of death by a...

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Can Banks connect emotionally?

 Where and how can banks connect emotionally with customers and why should they? The why is easy--connected customers are the most profitable customers who need the complete portfolio of services a bank can provide.With the shift to digital , the pandemic and the rise of challenger banks, its table stakes to have a digital presence offering checking accounts to receive money and make disbursements. The challenge is how do you differentiate such...

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Barriers to Data Mindset

 It is very hard for a bank to develop a data mindset.  Traditionally, regulated banks have been trained to deliver accuracy as they are managing money. The focus is on getting it right without errors and making sure all compliance requirements are met. This culture does not reward any creative inputs. Legacy systems on which banks have spent decades managing are also inflexible. In addition the process of completing a transaction has to...

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What is likely to happen? The journey of Prescriptive Analytics

 This is the final frontier in data analytics-- the ability to respond in real time to event data in a way that allows you to back the instincts of the decision maker with data. If your data is telling you what your instincts are saying, the chances of making an informed decision to influence outcomes increases.However, the right questions have to asked of the data otherwise the outcome will not be what was desired.Some examples in banks where...

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What can happen? The story of Predictive Analytics

Predictive Analytics is the process of using a combination of data analysis, statistics and machine learning to make predictions on possible outcomes.Examples of these can be:-predicting when a turbine in a power plant fail operating --this can help schedule maintenance activities  -predicting customer behaviour based on time of our marketing promotions-predicting capital required to meet regulatory requirements based on the volume of loans...

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Why did it happen? The Story of Diagnostic Analytics

 Diagnostic Analytics tries to answer the why something happened in the past  from our data sets- for example why did sales rise this month though we didn't have any marketing campaigns, why did patients in a sample have the same symptoms,why did our bank's customers choose the 5 year fixed mortgage product.Frequently this side of data analytics looks at both internal and external data sets to draw inferences . The process of drawing out...

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What happened? The story of Descriptive Analytics

 The oldest know data analysis consists of two things-aggregating or summarizing data and  data mining.The majority of a company's investment in data analytics is focused on aggregating data-- what was the sales, by month, by region for example.Comparing to previous time periods gives an understanding of where the company is going for instance the sales have increase 20% compared to previous quarter. It is an important tool for analysis...

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