Customer Bank Transaction Data Analysis
Lenders face a growing challenge from heightened competition in the industry. This is particularly evident in light of consolidation among major lenders and the rise of fintech companies disrupting the space. The move has left many community banks scrambling as they often lack the technology resources to properly keep up with the big lenders, but also face regulatory pressures that limit their ability to follow the lead of fintechs.
The Growing Challenge facing Smaller Lenders
Investments in risk analytics can help community and regional lenders stay afloat in these circumstances. However, there is a key limitation: Reaching the breadth of audiences that are increasingly served by non-traditional lenders. The invisible consumers – individuals without a credit history – can use alternative lenders that don’t base decisions on credit history to avoid using banks altogether. Borrowers with poor credit also tend to flock to alternative lenders that use cash flow analysis instead of credit histories to determine risk.
On top of all this, the cost and time devoted to loan application processing means most community and regional banks are only able to realise value from larger loans. This has led to a gradual decline in longstanding areas of value, such as small business lending, where more companies are turning to alternative lenders due to their quick turnaround time and higher acceptance rates.
Community and regional lenders face a crisis in expanding their customer base. They can use risk analytics technologies to accelerate and streamline loan application processes. Analytics solutions that leverage bank transaction data (BTD) can take these benefits to another level and position lenders to reach the widest audience possible.
Using BTD to Reach New Borrowers
Banks and credit societies have a great deal of transactional data at their disposal. Bank accounts track every transaction a person makes with the bank, and in today’s world where credit cards and digital purchasing dominate the payment space, bank account histories show the vast majority of purchases people make, and the income and outflow of cash can be similarly revelatory. If lenders can tap into this information, they can gain a more granular understanding of what a loan applicant can actually afford. What’s more, with this data consolidated into centralised databases covering accounts from multiple banks and credit societies, lenders can gain deep insights into the full scope a borrower’s financial health.
Bank Transaction Data & Machine Learning
Instead of having to depend solely on credit scores, lenders that have access to BTD can deepen their perspective on a borrower. BTD systems make this possible by:
- Categorising purchases logically, using machine learning to identify when the same company uses multiple naming strategies, such as a retailer that uses a slightly different variant of its name in different point-of-sale systems.
- Identifying trends in the BTD to automatically deliver actionable takeaways to employees.
- Filling in data gaps that aren’t covered by credit scores or may be unnoticeable at first due to credit score inflation.
These capabilities add up to empower lenders to identify opportunities that would otherwise be impossible to take advantage of. The transaction data lets you reach new customers in a few key ways, including:
- Offering loans to customers with bad or no credit by using BTD to perform cash flow analysis.
- Accelerating loan application processes by automating key decisioning tasks and incorporating a broader data set into analysis to eliminate areas where credit score alone isn’t enough to support rapid decision-making.
- Expanding the number of loan products you can realistically support. Faster, more cost-efficient approval processes means being able to get value from smaller loans. This empowers you to reach customers that would otherwise not provide enough revenue to justify the costs of working with them.
This last point particularly stands out for community and regional lenders trying to keep up with fintech companies or large lenders. If you can’t compete seriously on small business loans, for example, you can use risk analytics solutions that leverage BTD data to broaden your reach in the market. The cash flow analytics can let you lend to businesses with a strong income to expense ratio, but bad credit history. The technology can also help you process applications fast enough to keep up with alternative lenders that often deliver funding in just a few days. This lets you provide the same kind of speed and convenience that alternative lenders offer. At the same time, as a local or regional institution, you can offer valuable perspective and relationship services that larger banks can’t necessarily offer.
This is only one market where the BTD analytics pay off, but the benefits can extend to a variety of products and services. GDS Link can help you take full advantage of this potential. We blend advisory and analytics services to empower lenders to achieve their full potential and keep pace with the increasingly competitive market they are facing. Download our whitepaper, “The Evolution of Bank Transaction Data” to learn more about how the analytics technology works.
About the Author
Carl Spilker, Vice President of Analytics
Carl is an accomplished executive within Global Consumer Lending, boasting over 20 years of industry experience. Carl has a proven track record in delivering consumer lending products and utilising complex analytical instruments such as AI, Machine Learning and traditional multivariate models.