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alternative data in finance

Alternative data presents multiple opportunities but comes with challenges

by Mike Jones in Other Cat 19/05/2020

Alternative data, when verified as reliable and trustworthy, can be a significant tool for financial organisations when collecting information.

With competition rising and an increased reliance on data, financial organisations must be capable of making the changes. Inaccurate data or a lack of a range of information sources can result in poorly informed plans and ultimately reduce business performance. With the goal of gaining a wider perspective of customers and investments means businesses are actively looking for a wider range of data points. Alternative data has become a valuable tool for businesses, but it does involve some risks.

What exactly is alternative data?

Alternative data includes non-standard data points and offers a wider overview of the industry. Rather than being reliant on conventional information and using this in the decision-making process, financial businesses are actively looking for other measures to generate more insights. Take the example of a customer applying for a mortgage. Traditionally the process is based on a credit score and your previous payment history. Alternative data, including information on income, assets and financial behaviour can create a clearer picture of whether the customer is worthy of securing a mortgage. In this scenario, alternative data generate a more complete picture of the financial health of a customer.

Alternative data incorporate a wider range of information, going beyond the traditional data sources used by many companies. With the implications of COVID-19 and the rise of restrictive measures, the need to generate an advantage has become essential to many businesses.

Alternative data can generate a deeper understanding of certain variables, enabling organisations to gain more insight into customer and industry behaviours. The data can be very valuable in enabling the accurate delivery of financial and business impact analysis. Widening the amount of range of data can enable financial businesses to generate information that traditional systems cannot provide.

Alternative data is based on delivering better returns and generating smarter investments. This, however, is only possible if the information gathered is analysed properly and translated into clear actionable strategies. As with all data management, alternative data generation requires the right technology and skills and without this available alternative data will generate little benefit to a business. Only when data is properly analysed can financial businesses be in a position to accurately assess and measure risk as well as the opportunities available.

The need for collecting data and information from customers continues but for how, where and who in regards to sourcing the data will continue to transform in the future. Standard data collection is tried and tested processes in which businesses understand and know what to expect in terms of accuracy and reliability. Diverging your approach towards the alternative will likely generate deeper results yet it needs to be supported by further assessment. Businesses need to ensure any additional data insights are clearly evaluated at the source, to ensure validity and effectiveness.

Data reliability is a challenge for financial organisation. If alternative data used for business processes is found to be unreliable, it can result in significant implications for a business. Key considerations with data evolution are due diligence, ensuring data comes from reliable sources, data and privacy are secure and all information is compliant with the latest regulations.