Data should be one of your strongest assets, not a confusing uncertainty or a burden to work with. Alastair Luff of global information services group Experian here talks about how you can make the most of the data you gather and use it for e key decision making in your operations.
Big Data has become a buzzword in the Financial Services industry. Put simply, it’s about businesses having an amount of data so large, it becomes difficult to digest and define a clear strategy.
Information is created every second of the day, and its complexity is advancing as new data comes onto the scene. The volume of data is growing significantly, presenting a notable challenge to businesses. On its own, data isn’t valuable – it’s the business insights it provides which makes it a vital asset. The more information, the greater the insight, and the bigger the opportunity to drive optimum outcomes.
Data – a confusion or a complement?
Data can seem daunting. It needs to be controlled, understood and used to avoid hindering compliance, and to create real value. It can also confuse the customer – with less than 8% understanding how their data is being used within organisations.
But it can also complement. Organisations are not only faced with external data sources, but also first party data generated internally. But two data streams doesn’t result in a complete customer profile, and in some situations, information captured over an extended period of time may become outdated. Overlaying current and validated data, such as credit bureau data, can add a layer of insight that fills gaps and helps complete a fuller picture.
The more comprehensive view available, the better lenders can tailor credit risk policies to ensure financially inclusive lending strategies that consider all relevant data assets, e.g. within credit scoring.
Scoring with the customer
Credit scoring is nothing new, but it’s not just about banks and lenders. Industries outside of finance are beginning to recognise its benefits and scoring is offering enhanced outcomes for customer engagement and enhanced credit risk provisioning. In Africa, for example, data from mobile phone usage is helping with credit scoring where no financial services data exists, giving more people access to credit.
While scoring itself is well established, the process behind it has evolved. Organisations, lenders especially, are approaching scoring differently, considering individual risk strategies, profiling and in some instances different data assets. All of these factors, whether standard or bespoke, can provide an automated risk assessment that identifies the credit strategy of an individual.
Simplifying complex information
The ability to make responsible lending decisions comes down to how well information is interpreted. This is where scorecards come in to their own. They can help rationalise complex insights and automate decision making. Businesses who overlay internal insight into scoring, with enriched external insight achieve a more comprehensive view of each customer’s credit history.
In an era confused by a mass of information, a more demanding customer and pressure on minimising loss, businesses need to understand the value and opportunity – but balance both. This extends beyond scoring as an action, and therefore it would be prudent businesses automate this area – using available insight to free up resource to support developments across other business areas which aren’t so easily resolved.
Using comprehensive scoring can provide advanced data feeds that contain varying benefits for the organisation, for example:
- Understanding affordability. What does the future financial health of an individual look like? Are they likely to experience problems?
- Geographical insight. Some people have little or no bureau data. Using geographical analysis can provide a view of how the region and area is trending to support any credit review.
- Considering circumstance. Data for those with limited data, for example people living at home with their parents, can have their profile enhanced by overlaying relevant data. In addition lenders can consider the financial status of an individual, or an associate who they are linked to financially. This can provide a rounded view of any associations and identify any causes for concern.
- Ensuring the person is genuine. Fraud is on the rise and using data to assess and identify the genuine intent of a person can be critical to losses and also protect customers.
- Understanding how a person behaves. Behavioural data can provide rich insight into a person’s financial behaviours. From cash advances on credit, to limit vs. spend assessments. This can be particularly helpful in understanding a person’s financial trends and providing a prediction into their probable future trends.
Differing and advanced data assets can be used to on-board, and when a customer is on-boarded. It can be particularly useful during the lifetime of a loan in order to understand better any potential alignment to a business’s growth strategy.
In a world of Big Data, organisations have the opportunity to translate information into a currency. Understanding what insight it can bring, embedding it within credit risk and scoring policies can ensure accurate assessments and appropriate lending. Businesses just need to understand what data provides what – and why.