CredoLab: Revolutionising Credit Scoring Methods Through Mobile User Behaviour
CredoLab's Chief Data Scientist on How Banks and Consumer Lenders Can Leverage Data Analytics for Business and Social Impact
Mobile phones have become ubiquitous across the globe. Not only that, but smartphones are in the hands of a large majority of users and leave an enormous digital footprint, with tens of thousands of data points that can be used to predict user behaviour. The sheer amount of Big Data is exactly why CredoLab’s statistical models are so impressively predictive and stable.
Each of these mobile phone accounts provides a particularly rich source of data: almost every detail about each call, text and information request is captured and stored by the mobile device and can be utilised. It’s not hard to see why many industries are looking to tap into such a valuable data source. The insights into customer behaviour are unparalleled, incredibly predictive and instantly available, and CredoLab’s digital credit risk management is evolving rapidly as a result.
Mobiles as a data source
Traditionally, credit reports and salary history provide the data that lenders require to make a risk assessment in developed markets. Credit bureaus utilize this limited data with few data points to establish a credit score. While this method has been reliably used in the past 50 years, it simply inadequate in the present day since it cannot serve thin file customers, forming the majority of under and unbanked potential borrowers in emerging markets. Lenders want to establish three key factors: the customer’s identity, ability to repay, and willingness to repay. In emerging economies, however, these methods aren’t as effective. Today, there are over 2.5 billion people globally without formal financial services access, and lenders therefore have no access to previous borrowing behaviour.
A lack of regular, fixed wages and formal savings adds to the financial inconsistency. Existing credit models do not serve the needs of economically active lower-income households and enterprises, which is why many lenders are seeking out an alternative approach. CredoLab’s easy-to-use, instant, and amazingly predictive alternative credit scoring solution aims at serving exactly these people.
CredoLab’s significanly more inclusive risk models can be obtained using mobile phone data, with algorithms consistently developing highly accurate scorecards for consumer lenders. The digital scorecard can be used separately or in conjunction with traditional methods, to create a unique metadata footprint with incredible predictive power.
Credolab allows lenders to gain greater control over their lending decisions, vastly expand their pool of qualified borrowers with little or no credit history, and reduce the overall risk. Lending has historically been, and remains, the bank’s main source of revenue. So digital credit scoring is sure to benefit the bank, whilst providing a more efficient and fairer service to the customer. The data collected from a customer’s mobile phone can help banks make better credit decisions and smarter loan evaluations.
Despite being a promising resource, mobile phone data acquisition draws scepticism from customers with regards to security and authenticity. Data privacy is at the forefront of every customer’s mind, so how do credit scoring organisations reassure them that digital credit risk management is a friend rather than foe?
Rules and regulations
Regulatory requirements and privacy laws can stand in the way of organisations looking to gain access to digital data. Often, the data sets that lenders need are owned by, for example, telecoms companies, utilities, or retailers, which may themselves be prohibited from sharing information. Similarly, governments will be particularly cautious about sharing details about citizens.
Two solutions to these problems are to either pay for access, or to build partnerships with companies in a way which benefits both parties: on one side, there are organisations without financial services which can benefit from such arrangements and on the other, lenders can obtain consented access to valuable data.
CredoLab collects data directly from the customer’s phone with their consent. What differentiates our product from all other solutions is that the collected data is completely anonymous metadata. This approach easily convinces customer to willingly share their data without worrying about potential exposure of personal and sensitive data, or any improbable but possible security breaches.
Gaining credit insights
Converting metadata into credit insights poses a huge challenge to lenders. Risk and marketing teams will need to optimize their collaborations, and lenders will need to learn new skills to create evolved risk models. CredoLab’s know how, expertise and experience does that for lenders. Insights can be gained from the most unlikely sources: for example, the number of contacts, how much storage is utilized, and the time of day that phone calls are made – these “features” can be entered into models to determine credit scores. These emerging financial technologies are drawing the attention of a number of lenders, many of which are interested in CredoLab’s new algorithms, models and data sources.
Once lenders have got hold of the necessary data, they have to know what to do with it. By its nature, non-traditional data is high in volume and often comes from disparate sources. For example, each mobile account can generate thousands of calls and texts per month, each with a diverse array of insight potential. Risk modellers therefore need to familiarise themselves with the new technologies enabling them to aggregate and analyse such metadata. If software isn’t up to date, huge volumes of data can overwhelm the system and make statistical analysis challenging. Recent developments, such as cloud computing, have improved the processing power available to lenders, bringing down costs as well as enabling actionable credit risk insights.
How can CredoLab help?
CredoLab is a digital risk management start-up, headquartered in Singapore, which has developed a credit scoring mobile SDK. The software tracks the “anonymised digital footprints” of consumers and leverages predictive analytics to generate incredibly predictive digital credit scorecards. CredoLab aims to fill the void and provide financial inclusion to the under-banked population, and is able to improve both the availability of credit to those with no or limited banking history, as well as allowing a lender to reduce their cost of risk and increase their approval rate.
We don’t obtain any personal or sensitive data from the customer for their credit analysis: at a time when stakes are high on data privacy, this is sure to give customers peace of mind.
If you want to expand you business, lower your risk and serve the huge under-banked and unbanked population, and are keen to learn more about how our solution can write to us at email@example.com or drop in a word here.