Technology is Turning the Way Finance Companies Work

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finance

Technology has become synonymous with progress. Despite this being a dangerous idea (as not all progress is good), tech has had an extremely strong impact within the financial service industry. So much so that we had to have a name for it: fintech.

It’s not just cryptocurrencies and e-wallets that are reaping these benefits though, the business loans industry has also been souped up. The biggest improvement has been the efficiency of approving applications. In fact, you don’t have to look far to see what the “past” was like — banks continue to operate in such inefficient ways.

It takes around 4 weeks, often longer, to receive back a final decision on your business loan application at a traditional high street bank. Not to mention that you must attend physical meetings, speak to staff and fill in an extraordinarily long application form that usually entails a comprehensive business plan.


The whole process may be too long if your company is in need of financing. And just because you’re in immediate need of financing, it doesn’t automatically mean you should be ruled out because you’re struggling. In fact, it’s often a sign of growth. Startups have arguably faster growth potential now than ever before due to social media, technology, improvement in logistics and so on. This means that many growth opportunities might need to be put on hold until you hear back.

After all of this, you might be rejected on the grounds of not having a strong enough credit score. This alone is enough to infuriate, as it’s such a one-dimensional way of assessing a potential loan recipient. Risk assessment should reach much broader than this, yet banks continue to reason it for most rejections.

Lastly, if you get approved, you may have to wait another 2 months until you actually receive the cash. Again, the process is medieval.

New age lenders

Thankfully, there are alternatives banks for financing a small business. This has always been the case, but the competition and market as a whole has grown exponentially. In fact, it’s grown as a direct result of democratising information, decentralising the financial services industry and a growth in technological and Big Data capabilities.

The result, by general consensus among most of the SME lending companies, is that the process takes all of 24 hours, or 48 if you’re “unlucky”. You may even hear from the decision within 5 minutes. In fact, many will supply you with the resources necessary to figure out if you’re eligible, or how much you will repay. Business loan calculators help you do that.

Of course, the big difference here is that there’s no (or at least, very little), human input here. It’s all algorithms using your data, and historical data, to decide whether or not you’re an appropriate candidate for a loan. This predictive power becomes stronger and stronger as their database of records grows, thus leading to even faster times of approval.

Calculating borrowing risk from your current financial situation is much more-fair too than credit history. Not only is it unfair to completely write off a business due to their historical performance (it’s understandable that it would play some function in the decision), but it just isn’t very accurate. We’re all aware of the strange, non-business ways our credit can be negatively affected, such as merely applying for bank loans and getting rejected.

Many innovative lending companies are processing transactions from a business and using machine learning to classify each and every one. This risk data can then be used to automatically create simplified financial statements, financial ratios, affordability ratios, investability ratios, customer-supplier analysis and many more metrics. Once you have these, you can begin to make an informed-yet-instant decision over the financial health of a company. If you couple this with the repayment success of other previous companies, you may also be able to weight each ratio, KPI or metric in terms of importance.


Aggressive data aggregation and a strengthening in predictive power is perfect in finance, because ultimately risk comes at a price. Likewise, asymmetric information is the ultimate inefficiency which leads to short-term losses of the insurer/lender, but then the price rises due to the assumed increase in unforeseeable risk for everyone.

As these risk assessments get clearer and information becomes more symmetrical, suddenly you’re paying closer to the exact price of your real risk. This rewards businesses with honest intentions to grow with a more reasonable interest rate, meanwhile the technology has allowed them to receive the funds within a day.


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