Financial Inclusion

Oct 26, 2023

6 Ways To Utilise credolab's Behavioural Solutions to Drive Financial Inclusion

Explore how credolab's behavioural data analytics enhances financial inclusion, risk assessment, fraud detection, and marketing.

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The ever-growing financial inclusion has taken centre stage in this ever-evolving financial landscape. Financial inclusion from the 2030 Sustainable Development Agenda, also mentioned in our blog, 2023 Expert Guide: The Importance of Financial Inclusion Strategies and Policies, is meant to facilitate eight Sustainable Development Goals primarily in health, education and mobility. This global phenomenon aims to ensure that everyone receives equal access to financial services and opportunities. 

Historically, traditional systems assessing creditworthiness often exclude individuals with little or no credit history, leaving them on the fringes of the financial landscape. These individuals range from thin-file applicants like students, young adults, gig-economy workers, those underserved, underbanked or unbanked, and those from marginalised communities. Financial inclusion initiatives give these individuals the opportunity to avoid extreme poverty, boost shared prosperity, and improve their lives. However, the emergence and unprecedented growth of financial inclusion have increased the need to go beyond basic access and pushed the focus onto creating more affordable and reliable financial products and services, enabling these excluded individuals of varied economic status and financial backgrounds to connect with formal financial systems. 

Boosting financial inclusion with credolab

Many global initiatives are being implemented to boost financial inclusion. One includes increasing involvement and collaboration with financial technology companies and businesses. For example, a bank in the Philippines teamed up with a B2B SaaS fintech company specialising in behavioural data analytics - credolab. Offering a range of innovative solutions, credolab aims to change the financial narrative and close the financial gap by harnessing the power of behavioural data through analysing smartphone and web metadata. With credolab, any financial institution can empower their business to make more informed decisions, detect fraud, and optimise marketing strategies, ultimately driving financial inclusion. 

This comprehensive exploration will delve into various ways credolab reshapes finance. We also explore how its solutions enhance financial inclusion through innovative behavioural data analytics and leveraging advanced technologies like Machine Learning (ML) algorithms.

1. Advanced behavioural data analytics

At the core of credolab is a powerful behavioural data analytics platform that leverages proprietary ML algorithms to analyse smartphone and web metadata. 

Using credolab, businesses can extract and better understand the intricacies of user behaviour. Some factors include identifying behavioural patterns and extracting valuable insights from a combination of existing traditional data and alternative data, specifically behavioural data through smartphone and web metadata. Credolab collects and analyses over 10 million behavioural features or data signals, allowing its proprietary data modelling pipeline rooted in ML algorithms to detect micro-behavioural patterns from over 70,000 privacy-consented and permissioned data points. This behavioural analysis provides businesses rich, real-time, granular insights into users’ mobile and web behaviours and converts users' digital footprint into highly predictive scores tailor-made to each client. Therefore, businesses are equipped with a more robust set of learnings and information, enabling more informed decision-making and increased accessibility to financial services globally, ultimately enhancing global financial inclusion.

Utilising behavioural data provides a new key element to enhancing financial inclusion. As with most traditional credit assessment methods, decisions often rely on static financial data such as credit scores and income history. However, these methods can exclude a significant portion of the population, especially those with no conventional credit history. By incorporating behavioural data, credolab’s solution bridges this gap, allowing businesses to expand their reach to include more individuals regardless of their financial backgrounds by complementing and supplementing the existing underwriting policies with insights and scores from real-time behavioural patterns from their digital footprint data. 

This shift towards advanced behavioural data analytics modenises how financial institutions evaluate applicants. It opens up new avenues for financial inclusion by considering a broader range of factors reflecting an individual's financial capability and willingness to repay.

2. Mitigating Risk

One of credolab's solutions offers the ability to assess every applicant more accurately with behaviour-based alternative risk scores. Tailored for credit risk management teams, credolab’s risk solution seamlessly complements traditional data with behavioural insights and scores to assess risky applicants and their probability of defaulting in real-time. 

Using this risk solution, credolab delves into behavioural patterns and pinpoints potential risks that might not be apparent through traditional risk assessments, elevating credit risk assessment with this innovative scorecard solution. This comprehensive risk assessment helps businesses make more informed lending decisions and effective management at scale while expanding access to credit for individuals who may not have a conventional credit history.

Credolab’s risk solutions offer various modules targeting different needs to modernise risk assessment with privacy-consented, permissioned, anonymous smartphone and web metadata. This solution offers an Alternative Risk Module, an Insurance Risk Module and a Collections Module. It is also ideal for digital lenders, banks, neobanks, BNPLs, and consumer finance companies looking to reduce the cost of risk, improve acceptance rates and enter new market segments. 

Risk Solutions

Current or traditional credit scoring methods have limitations and often lack agility and precise risk assessment, leading to conservative lending practices, high rejection rates, and suboptimal decisions. Using outdated models and isolated data also hinders adapting to dynamic markets, heightening exposure to risks and missed growth. With alternative credit scoring methods leveraging alternative data like behavioural data, businesses and lenders can gain a dynamic and real-time view of an applicant’s financial behaviour and improve their bottom line. 

3. Enhancing Fraud Detection

Fraud remains a significant concern in the financial industry. Detecting and preventing fraudulent activities is paramount for the security of both businesses and consumers. Credolab’s fraud solutions play a crucial role in enhancing fraud detection, particularly during the onboarding process. 

Using this fraud solution, credolab conducts frictionless fraud detection checks and scores, harnessing first-party, privacy-consented, and permissioned smartphone and web behavioural metadata to modernise fraud detection strategies with seamless, cutting-edge API integration. Using frictionless fraud detection checks and scores, credolab identifies unusual patterns and activities that indicate suspicious or fraudulent behaviours, applications, transactions and usage. As a result, businesses can reduce fraud costs and empower teams to optimise decision-making, transform data into actionable plans, and improve the quality of the portfolio.

Credolab’s fraud solutions offer various modules that target different needs, including an Anti-Fraud Insights Module, Account Takeovers (ATO) Module and Fraud Scores Module. These modules are ideal for any digital lender, bank, neobank, BNPL and consumer finance company looking to reduce the cost of fraud, detect fraudulent applications and reduce manual verifications. 

Fraud Solutions

Traditional rule-based systems that rely only on traditional data struggle to keep pace with evolving fraud tactics, leaving vulnerabilities unaddressed. With this solution, businesses can enhance traditional methods and reduce the likelihood of fraudulent applications going through, resulting in increased financial security and revenue protection. Furthermore, a robust and adaptive approach to tackling fraud and enhancing fraud detection contributes to building security and trust, accelerating the acceptance of new customers, especially those who were once excluded - the underserved, unbanked and marginalised communities.

4. Optimising Marketing Strategies

Credolab's solutions are not solely focused on risk assessment and fraud detection, they also offer substantial value in marketing optimisation. Using outcome-based and personality-based behavioural insights, credolab’s marketing solution improves customer segmentation, targeting, activation, conversions and engagement rates. After all, understanding customer behaviours is paramount in tailoring effective marketing strategies. 

Using this marketing solution, credolab redefines marketing insights with privacy-compliant behavioural metadata, offering personality-based and outcome-driven behavioural insights and scores for advanced customer lifecycle management. Furthermore, leveraging behavioural insights and scores for marketing strategies creates an innovative way to transform customer segments into personas built on a deeper understanding of users’ personalities and intent. 

Credolab’s marketing solutions offer various modules that target different needs, including a Marketing Insights Module and a Marketing Scores Module. These modules are ideal for any app publisher interested in increasing the understanding of their users, boosting activation rates, and improving ROMI. By redefining marketing insights, businesses can elevate marketing efficacy across segments, activations, conversions, and engagement rates among app users. Furthermore, by utilising real-time insights, businesses can steer campaigns towards unmatched marketing performance.

Marketing Solutions

Sticking with only traditional marketing strategies can often create generic results and be less effective. These existing or traditional methods often need more actionable intelligence, leading to ineffective campaigns and missed opportunities. These methods leave marketing efforts fragmented and disconnected from audience preferences without a streamlined approach to analysing and interpreting data. However, utilising behavioural data and insights provides a treasure trove of new information - customer preferences, online behaviours and engagement patterns. As a result, with these comprehensive insights derived from non-intrusive and privacy-compliant behavioural metadata, businesses can ensure strategic decision-making and optimal marketing performance that creates highly targeted and personalised marketing campaigns and increases conversion rates.

5. Deepening customer understanding with data enrichment

A fundamental aspect of sustainable financial inclusion is developing a deep understanding of customers. Credolab’s data enrichment solution unlocks valuable insights based on real-time smartphone and web behavioural metadata. It allows businesses to gain a unique window into their customers' preferences beyond traditional demographics and credit histories, allowing them to connect more deeply with each user. 

By leveraging this all-in-one solution, modern businesses can unlock valuable insights using more comprehensive and accurate data and better understand their customers with real-time behavioural insights. After all, understanding customer behaviour enables businesses to provide more tailored products and services. 

Credolab’s Data Enrichment Insights Module is ideal for businesses looking to better understand their customers, especially mobile app and website users. By focusing on granular, real-time and user-level insights, credolab fosters a deeper comprehension of all users and empowers businesses to cultivate a profound understanding of their customers. 

Data Enrichment Solutions

Traditional or existing data sources often lack depth, are incomplete and sometimes outdated, leading to restrictions in crafting targeted strategies and limitations in understanding customer needs. Using contextual and real-time smartphone and web metadata, businesses can unlock the full potential of any operations and make more informed choices. As a result, businesses can facilitate better customer support and engagement strategies, ultimately leading to stronger customer relationships and enhancing overall growth and efficiency.

6. Collaborating with multiple partners

Partnering with multiple partners globally has been a monumental step forward for credolab towards modernising fraud prevention and credit risk assessment and advancing financial inclusion.

The EY FinTech Adoption Index highlights how the adoption of fintech services has increased globally from 15% in 2015 to 64% in 2019. However, despite this increase, some fintechs still need help to form a solid client base. According to Ernst and Young, fintech companies and banks are eager to cooperate. Fintech companies have four main reasons to collaborate with banks:

  1. Banks generally have a more well-defined and stable client base.
  2. A partnership or collaboration with a bank shows a stamp of trust that confirms these fintech’s credibility to customers.
  3. Banks tend to have bigger investment budgets and can provide a capital flow to develop fintech services further. 
  4. Banks hold a wealth of internal know-how and knowledge in areas that fintech firms can benefit from, including legal and regulatory compliance and risk management.

Banks also have two main driving forces to collaborate with fintech companies:

  1. Customers have become increasingly used to a seamless digital experience and expect the same from their bank but are yet able to provide these services.
  2. Fintech companies emerging as one-stop shops have moved from being just a single service provider to providing a whole suite of services that banks can fully use. 

For example, in credolab’s case, one such partnership collaboration is with TransUnion, a prominent credit information and information management service provider. This partnership has led to modernising fraud prevention and credit risk assessment processes, leveraging behavioural data, among other sources. TransUnion's integration of credolab's technology into its Digital Onboarding solution offers a seamless end-to-end solution for credit risk assessment and ID verification. This integration utilises behavioural data from smartphones to enhance the accuracy and efficiency of these critical processes.

Another more recent partnership collaboration is with Círculo de Crédito, a Credit Information Society (Credit Bureau) that provides strategic data, decision, and digital solutions to empower any company to run profitable financial services in Mexico. This partnership aims to enhance financial inclusion with innovative credit, risk, and fraud scoring solutions by introducing an exclusive Digital Behavioural Analysis Solution, 'BRAVE' – a Behaviour, Risk, Authentication, & Validation Engine. BRAVE offers a groundbreaking solution that harnesses the power of Behavioural Analytics. It analyses metadata from applicants' digital behaviours and uncovers invaluable behavioural insights to enhance risk and fraud assessments.

Credolab and Circulo de Credito Partnership

“Traditional lending processes and credit assessments exclude many individuals since they are mostly based on pre-existing credit histories. The lack of data, especially in emerging markets, leads to a high rate of rejections. Credolab's mission is to make credit available to all. We do this by providing financial institutions and credit bureaus with highly accurate risk scores that empower better credit risk decisions. By utilising a previously untapped, highly predictive source of new data - behavioural metadata from the smartphone and web, we aim to play our part in reducing financial exclusion.”
Peter Barcak, CEO and Founder of credolab


Credolab’s pioneering use of behavioural data analytics and advanced technologies like ML algorithms offers a comprehensive and innovative approach to financial inclusion, making it more inclusive and efficient, transforming the financial industry. Utilising credolab's insights and scores, businesses can make more informed risk decisions, enhance fraud detection, optimise marketing strategies, and deepen their understanding of customers. 

Credolab’s proactive approach to driving financial inclusion through behavioural data paves the way for a brighter and more inclusive future for finance. Businesses can fully utilise the power of credolab’s behavioural data without having to compromise on data protection and customers' privacy. Smartphone and web behavioural metadata processed the "credolab way" are instrumental in expanding their reach to include more individuals and increasing financial opportunities, regardless of their financial backgrounds.

Instead of evaluating creditworthiness solely based on traditional means, credolab shares a reimagined financial landscape where financial services are not confined by preconceived and set notions using the potential and unique behaviour of each individual. As a result, we see innovation and a profound commitment to creating a more inclusive and equitable financial landscape for all.  


  • Alternative data: The set of information on behaviours, habits, interests and transactions carried out by a person and obtained from non-traditional sources.
  • Behavioural data: Information derived from an individual's online and smartphone behaviour, used to understand customer preferences and trends.
  • Credit assessment: A lender's process to determine one’s ability to repay the loan and how risky it is for them.
  • Credit history: A record of an individual's borrowing and repayment behaviour, often used by lenders to assess creditworthiness.
  • Credit risk assessment: The process of evaluating an individual's or business's creditworthiness to determine their eligibility for loans or credit.
  • Data enrichment: The process of enhancing existing data with additional information to gain more comprehensive insights.
  • Financial inclusion: The provision of affordable and accessible financial services to all individuals and businesses regardless of their financial situation or geographical location.
  • Fraud Detection: The process of identifying and preventing fraudulent activities, such as identity theft or financial fraud.
  • Marketing Segmentation: The process of dividing a target market into smaller, more manageable segments based on common characteristics.
  • Risk Portrait: A comprehensive view of an individual's or business's risk factors and creditworthiness, often provided by alternative data sources like behavioural metadata.
  • Smartphone and web metadata: A set of data that describes and gives information about other data and key facts about an individual's data file from smartphone and web data, used for various analytical purposes.
  • Traditional credit data: Focuses on existing data already being used, such as credit scores, payment behaviour, and basic financial information, commonly used for credit assessment and risk analysis.
  • Thin-file applicants: Individuals with limited or no credit history, making it challenging for traditional credit assessment methods to evaluate their creditworthiness.
  • Unbanked: People who do not have access to financial services.
  • Underbanked: People with limited access, often in the form of informal financial services (e.g. illegal loans, relatives/family member loans and more).
  • Underserved: People with a bank account but often rely on alternative financial services such as money orders, check-cashing services, and payday loans rather than traditional loans and credit cards to manage their finances and fund purchases.

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