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How Data-Sharing Is Making Roads Safer And Cities Smarter

November 2, 2015 at 8:30 AM

It seems to be a topic of conversation everywhere you go, and now the Internet of things (IoT) and a growing data-sharing culture is helping make the world a safer place - one missing drain cover and pothole at a time.

Luxury vehicle manufacturer, Jaguar, announced earlier this year that future releases of their Land Rover off-road vehicle fleet are to be equipped with sensors that detect and warn drivers of potholes or missing drain covers ahead. The motoring company is also working with local UK municipalities to understand how IoT technology can help address road safety more efficiently. According to Coventry City Councillor, Rachel Lancaster,

“As part of our ‘Smart Cities’ strategy, we will be investigating how Jaguar Land Rover’s Pothole Alert system could supply us with data in real-time from thousands of connected cars right across our road network. This could give us a very accurate, minute-by-minute picture of damage to road surfaces, manholes and drains in real time.”

Fixing potholes and mending fences through data-sharing

The Johannesburg Road Agency’s (JRA) Find and Fix app  is helping to eradicate problems relating to potholes, missing drain covers and faulty traffic signals by reporting road hazards instantly via mobile users’ geolocations. Developed in partnership with Microsoft, the app also facilitates image attachments to help assess the extent of reported hazards more efficiently. Moving beyond road safety, the Erkhuleni Municipality has fostered a much-needed sense of inclusion with a community with whom its relationship has at times been somewhat strained. Improving service delivery by leveraging the power of IoT has paid dividends with residents buying into the concept of data-sharing as a means of empowerment. With +5000 downloads on the Windows, Android and iOS platforms, Find and Fix is helping the municipality not only reduce road accidents, but also build a stronger relationship with the community it serves.

How data-sharing is making cities safer

In the city of New York, USA, police departments are moving from reactive to proactive patrolling thanks to predictive data modelling that identifies areas, events and other scenarios that require higher levels of crime prevention to keep residents safe. Police officers also receive real-time updates on their way to crime scenes that inform them on the surrounding area, its inhabitants and the propensity for further criminal activity. The Domain Awareness System, also developed in partnership with Microsoft, was launched in 2012 to help curb crime in the world’s second biggest city and has done so with considerable results. In the year following its inception, the New York Police Department (NYPD) reported 35% fewer murders, a 17% drop in car break-ins and a 16% decrease in person-to-person robberies.

Imagining a new world with data at its centre

IoT’s omnipresence might seem a little scary to those with a more Orwellian slant to their worldview, but for the more pragmatic, the opportunities couldn’t be more exciting. With Moore’s Law in full effect regarding the evolution of computing capacity and much of the foundational infrastructure in place, we’re inching closer to a reality that involves the animation of once static devices into truly smart devices. With this internet-driven revolution in full swing, pioneering companies are well-positioned to pick the low hanging fruits of our interconnected society and move on to break new ground as they venture further into the possibilities of the digital unknown.

At Principa, we believe in data’s ability to help us push past perceived boundaries to discover new possibilities. We partner with our clients to help them realise the potential in their information assets and deliver results consistently. 

how to use predictive business analytics

Julian Diaz
Julian Diaz
Julian Diaz was Head of Marketing for Principa until 2017, after which he became Head of Marketing for Honeybee CRM. American born and raised, Julian has worked in the IT industry for over 20 years. Having begun his career at a major software company in Germany, Julian made the move to South Africa in 1998 when he joined Dimension Data and later MWEB (leading South African ISP). Since then, Julian has helped launch various South African technology brands into international markets, including Principa.

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The 7 types of credit risk in SME lending

  It is common knowledge in the industry that the credit risk assessment of a consumer applying for credit is far less complex than that of a business that is applying for credit. Why is this the case? Simply put, consumers are usually very similar in their requirements and risks (homogenous) whilst businesses have far more varying risk elements (heterogenous). In this blog we will look at all the different risk elements within a business (here SME) credit application. These are: Risk of proprietors Risk of business Reason for loan Financial ratios Size of loan Risk industry Risk of region Before we delve into this list, it is worth noting that all of these factors need to be deployable as assessment tools within your originations system so it is key that you ensure your system can manage them. If you are on the look out for a loans origination system, then look no further than Principa’s AppSmart. If you are looking for a decision engine to manage your scorecards, policy rules and terms of business then take a look at our DecisionSmart business rules engine. AppSmart and DecisionSmart are part of Principa’s FinSmart Universe allowing for effective credit management across the customer life-cycle.   The different risk elements within a business credit application 1) Risk of proprietors For smaller organisations the risk of the business is inextricably linked to the financial well-being of the proprietors. How small is small? The rule of thumb is companies with up to two to three proprietors should have their proprietors assessed for risk too. This fits in with the SME segment. What data should be looked at? Generally in countries with mature credit bureaux, credit data is looked at including the score (there is normally a score cut-off) and then negative information such as the existence of judgements or defaults; these are typically used within policy rules. Those businesses with proprietors with excessive numbers of “negatives” may be disqualified from the loan application. Some credit bureaux offer a score of an individual based on the performance of all the businesses with which they are associated. This can also be useful in the credit risk assessment process. Another innovation being adopted internationally is the use of psychometrics in credit evaluation of the proprietors. To find out more about adopting credit scoring, read our blog on how to adopt credit scoring.   2) Risk of business The risk of the business should be managed through both scores and policy rules. Lenders will look at information such as the age of company, the experience of directors and the size of company etc. within a score. Alternatively, many lenders utilise the business score offered by credit bureaux. These scores are typically not as strong as consumer scores as the underlying data is limited and sometimes problematic. For example, large successful organisations may have judgements registered against their name which, unlike for consumers, is not necessarily a direct indication of the inability to service debt.   3) Reason for loan The reason for a loan is used more widely in business lending as opposed to unsecured consumer lending. Venture capital, working capital, invoice discounting and bridging finance are just some of many types of loan/facilities available and lenders need to equip themselves with the ability to manage each of these customer types whether it is within originations or collections. Prudent lenders venturing into the SME space for the first time often focus on one or two of these loan types and then expand later – as the operational implication for each type of loan is complex.   4) Financial ratios Financial ratios are core to commercial credit risk assessment. The main challenge here is to ensure that reliable financials are available from the customer. Small businesses may not be audited and thus the financials may be less trustworthy. Financial ratios can be divided into four categories: Profitability Leverage Coverage Liquidity Profitability can be further divided into margin ratios and return ratios. Lenders are frequently interested in gross profit margins; this is normally explicit on the income statement. The EBIDTA margin and operating profit margins are also used as well as return ratios such as return on assets, return on equity and risk-adjusted-returns. Leverage ratios are useful to lenders as they reflect the portion of the business that is financed by debt. Lower leverage ratios indicate stability. Leverage ratios assessed often incorporate debt-to-asset, debt-to-equity and asset-to-equity. Coverage ratios indicate the coverage that income or assets provide for the servicing of debt or interest expenses. The higher the coverage ratio the better it is for the lender. Coverage ratios are worked out considering the loan/facility that is being applied for. Finally, liquidity ratios indicate the ability for a company to convert its assets into cash. There are a variety of ratios used here. The current ratio is simply the ratio of assets to liabilities. The quick ratio is the ability for the business to pay its current debts off with readily available assets. The higher the liquidity ratios the better. Ratios are used both within credit scorecards as well as within policy rules. You can read more about these ratios here.   5) Size of loan When assessing credit risk for a consumer, the risk of the consumer does not normally change with the change of loan amount or facility (subject to the consumer passing affordability criteria). With business loans, loan amounts can range quite dramatically, and the risk of the applicant is normally tied to the loan amount requested. The loan/facility amount will of course change the ratios (mentioned in the last section) which could affect a positive/negative outcome. The outcome of the loan application is usually directly linked to a loan amount and any marked change to this loan amount would change the risk profile of the application.   6) Risk of industry The risk of an industry in which the SME operates can have a strong deterministic relationship with the entity being able to service the debt. Some lenders use this and those who do not normally identify this as a missing element in their risk assessment process. The identification of industry is always important. If you are in manufacturing, but your clients are the mines, then you are perhaps better identified as operating in mining as opposed to manufacturing. Most lenders who assess industry, will periodically rule out certain industries and perhaps also incorporate industry within their scorecard. Others take a more scientific approach. In the graph below the performance of an industry is tracked for two years and then projected over the next 6 months; this is then compared to the country’s GDP. As the industry appears to track above the projected GDP, a positive outlook is given to this applicant and this may affect them favourably in the credit application.                   7) Risk of Region   The last area of assessment is risk of region. Of the seven, this one is used the least. Here businesses,  either on book or on the bureau, are assessed against their geo-code. Each geo-code is clustered, and the projected outlook is given as positive, static or negative. As with industry this can be used within the assessment process as a policy rule or within a scorecard.   Bringing the seven risk categories together in a risk assessment These seven risk assessment categories are all important in the risk assessment process. How you bring it all together is critical. If you would like to discuss your SME evaluation challenges or find out more about what we offer in credit management software (like AppSmart and DecisionSmart), get in touch with us here.

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