With AI continuing to be a significantly disruptive force in various industries, there is an emerging trend in making use of alternative data sources when making strategic decisions in areas such as customer profiling and marketing.

Alternative Data – What is it?
Alternative data falls outside of conventional, well-established data sources. In terms of finance and lending, this would be anything aside from the usual data points collected to make credit assessments for potential borrowers (e.g., bank account history, credit accounts, loan history). The International Committee on Credit Reporting (ICCR) have broadly defined the data as:

•  Structured data; e.g., utilities usage, cellphone activity, rental payment history and tax records,
• Unstructured data; e.g., internet and social media use, voice and text files, digital photos and images.

Other sources of alternative data are also reportedly being explored, such as personality and intelligence. These are less susceptible to manipulation, however, having the right regulation and policies in place will be important to ensure ethical use. Generally, a good source should be easy to obtain, specific to an individual, accurate and timely, have good predictive power, and be compliant with any relevant regulations.

Alternative Data – Sources for Credit Scoring
Within the financial sector, there has been a move towards incorporating new sources of data in addition to the metrics traditionally used in credit scorecard models (e.g., bureau credit scores, income, and expense data, payment history) to improve predictive power.

Consumer groups that may not necessarily have the credit history or background that meet certain criteria when using well-established credit risk models, can often be overlooked. Take the US, for example, where first-time borrowers need to build credit history to gain creditworthiness yet obtaining credit without credit history can be challenging.

So far, the most active areas adopting alternative data into their credit risk assessments has been seen in the FinTech space and some developing markets.

Use Cases in Credit Analysis
Some FinTech companies and digital financial service providers have taken it upon themselves to find innovative alternative data sources. A UK PropTech firm has developed a tool allowing credit agencies, such as Experian, to incorporate rent payment history into their credit scoring models. In Singapore, a software company has implemented the use of social media and mobile phone data to determine an individual’s creditworthiness. A US-based agency use a “passporting” process to form a profile for international students and professionals by gathering data from international credit bureaus.

In the micro-finance space, small companies have implemented credit scoring via smartphone activity, including call and SMS logs, GPS data and contacts information. Over time, as machine learning and AI technology process increasing amounts of data the output from predictive models is likely to improve and become more dependable.

Alternative Data – Sources for Marketing
Achieving sustained growth for businesses is becoming increasingly challenging in today’s economic environment, not least as consumer needs and preferences are constantly changing. When looking at decision-making in key areas such as marketing, making appropriate use of data can make or break a company’s ability to gain a competitive edge.

Census data can provide the most common sources of alternative data for marketing and is the most widely available. Information such as changes in demographics and consumer interests can prove valuable when analysing segments. National statistics bureaus may also provide useful data. For example, the Bureau of Labor in the US have records of expenditure, which can be assessed to see how consumer expenditure has changed over time.

AI tools can be used to automatically track data, e.g., how many visits a website receives and which areas are more popular than others. It is also important to be aware and know who a company’s competitors are in the market. Competitor reviews can be monitored across several platforms on a regular basis.

Another useful function to look into are automating pricing strategies. Efficient tools will be able to adjust pricing according to various attributes, including market competition and set levels that are still profitable.

Regulation and data protection
Whilst very useful, the main objective in the use of alternative data is to be able to extend credit and increase financial inclusion for the benefit of the end-consumer. It is therefore imperative that consumers feel their data is being protected and used appropriately. In addition, consumers should not be treated unfairly as a result of unintended bias inherent in the use of alternative data.

Policy-making needs to cover the collection and processing of data being carried out in a lawful way, as well as stipulating transparency for customers. Customers should also have the right to object to their information being used in a certain manner, including sharing of data with third-party providers. For example, the recent roll-out of open banking in the UK is closely scrutinised by government and is regulated by the Financial Conduct Authority (FCA).

One of the most prominent and relevant legislation currently in place around data privacy is the EU’s General Data Protection Regulation (GDPR), effective since May 2018. GDPR seeks to protect consumers’ data and give provide them with transparency, at a time where vast amounts of data is becoming widely available. Any global bodies trading internationally will already be impacted by GDPR.

In the UAE, The Dubai International Finance Centre (DIFC) has recently implemented the Data Protection Law DIFC Law No. 5 of 2020, much of which is comparable to the GDPR framework.

Although not all countries in the GCC have specific laws around privacy and data protection, some are reportedly in the process of following suit and reviewing legislation around privacy to ensure compliance with global standards.

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