Analytics skills essential for business survival in ‘data decade’ – say business leaders

Professionals will need to learn data science skills to do their jobs and help their companies thrive in the next decade, say business leaders.

Most managers believe data analytics, automation and AI will be essential for business survival in the coming years yet lack the necessary knowledge that underpins it, according to MHR Analytics research.

“We wanted to explore the levels to which organisations across all sectors are developing their data strategies, as businesses get ready to enter a new decade that promises unprecedented digital acceleration,” said Laura Timms, MHR Analytics product strategy manager.

“Without the crucial component of a good data foundation, it is impossible to implement advanced analytics, automation or AI,” she said. “Despite a widespread appetite for adopting these technologies, the study showed that a better understanding of data strategy basics will be vital for companies to launch the data-driven projects they know they need to compete.”

The Data Decade survey, which polled 500 senior technology and finance managers in large UK organisations, found that:

1. More than half (55%), believe data analytics will be essential for business survival in the next ten years, 53% say automation will be essential, and 42% believe AI will be essential
2. A fifth (21%) of UK companies plan to implement AI yet they do not have a data strategy to support it, suggesting a better understanding will be necessary
3. Skills gaps are delaying AI adoption, with 40% reporting this as a barrier to advanced analytics
4. Data science skills will increase in importance, with 43% of senior professionals saying they will need to learn data science or analytics skills to progress their role in the next five years
5. 43% say their role will become more strategic as traditional tasks become automated, with 91% saying their department will become more efficient due to automation.

“The research results demonstrate the positive aspirations that senior leaders have about data-driven technology, and how it will evolve and advance their roles and keep their organisations competitive in the next decade,” said Timms. “But delivering any AI-based system relies on getting the basics right with every aspect of your data quality, and on taking a step-by-step approach to data maturity.”

In the MHR Analytics report, Advancing with Analytics: Spreadsheets to AI, AI expert Bernard Marr reveals how different organisations are establishing data strategies to underpin their AI aspirations.

For example, Marr explains how Royal Shell is using AI to solve the problem facing the company’s drive to roll out electric vehicle-charging terminals.

Motorists weren’t keen to make the switch to electric vehicles while the number of terminals were so limited and while forecourt operators weren’t offering charging terminals because demand was so low.

A focused data strategy underpinning AI techniques offered a solution to this chicken and egg issue. Royal Shell’s RechargePlus programme uses AI to monitor and predict demand for charging terminals throughout the day. By better understanding customer charging needs, power can be supplied more efficiently – which, in turn, saves motorists money and will potentially encourage more motorists to make the switch to electric cars.

More information about progressing along the data journey is available via the MHR Analytics data maturity quiz.

Graydon and Cifas work together to analyse and detect corporate fraud

Graydon, one of Europe’s leading providers of business data, insights, analytics and solutions, and Cifas, the UK fraud prevention service, announced today they have completed data matching analysis to understand synergies between the Graydon cases of suspicious corporate activity and the Cifas national database of known fraud.

The results of the matching exercise demonstrated two key points:

1. Fraudsters will target any high-value sectors with soft targets, the corporate world needs to boost information sharing if they are to tackle fraud head-on.
2. Fraudulent behaviour by directors isn’t isolated to their work – supplementary data from public bodies and organisations enables earlier identification of behaviour and/or modus operandi.

There is a wealth of data not available in the public domain, which exists on the Cifas National Fraud Database – the only UK database detailing confirmed fraudulent activity.

Cifas members share information securely across 14 different sectors including banking, insurance, asset finance and telecommunications., so the information contained on the Cifas National Fraud Database details confirmed fraudulent activity across the UK economy.

The live database holds approximately 1,800,000 cases from the previous six years and requires all Cifas members to submit identified fraud behaviour within 24 hours following identification. It receives around 800 new reports every hour. All cases submitted to the Cifas database contain appropriate evidence to submit a formal report to the police, with sufficient grounds to press criminal charges. Members save a combined £1.4bn last year from using this information in their risk decisions.

The matching exercise showed a high correlation between suspected fraud activity identified by Graydon and confirmed fraudulent activity reported to Cifas specifically it identified the activity of the people behind the business with significant control.:

• Cases are being reported by more need to come forward: 43% of cases where Graydon had withdrawn a credit rating due to suspicious activity were matched with reports on the Cifas database.
• This is not isolated behaviour, 5.3 cases were returned for each company match, and 8.3 cases for each director matched on the national fraud database, on averageFraudsters hang out at the same old haunts.
• Suspected fraud on both databases had been carried out from the same address – 90% match rate in multiple cases at the same address.

The analysis indicated two areas of disproportionately high match rates – application fraud (21%) and misuse of facility (67%). Both these types of fraud were much higher in corporates than an average view of the National Fraud Database would normally expect.

The following definitions were used:

Application Fraud
When an application for a product or service is made with ‘material falsehoods’, or by purposefully omitting important information. Cases such as these usually have false supporting documents or false employment or income details, concealed addresses or concealed adverse credit history.

The most common reason for filing a case of Application Fraud was ‘Undisclosed Adverse Address History’. In the data matching exercise, there was a 90% match-rate on multiple cases of fraud being carried out from the same addresses.

Misuse of Facility
The misuse of an account, policy or product; for example paying in an altered cheque to an individual or commercial current account, or taking the facility with no attention to pay it back.

The most common reason for filing a case of Misuse of Facility was ‘the paying in of false instruments, wrongfully retained credit and multiple encashment fraud’. Typically, these three reasons for filing are symptomatic of money laundering.

The prevalence of these two types of fraud demonstrates the significant value of Cifas data to B2B businesses fighting commercial fraud and is indicative of how corporate entities are increasingly attractive to individuals committing these types of fraud as they provide effective vehicles to hide behind.

Graydon is a B2B credit reference agency with a long-standing expertise in helping business manage their commercial risk and avoid corporate fraud. Models of suspicious corporate activity have been developed over the years, based on the filing behaviours of fraudulent businesses and information supplied by users. These models are used to generate alerts to Graydon users or suspend the credit ratings of suspect businesses.

Chris Oatts, operations director, Graydon UK:

“Matching the suspected frauds identified by Graydon against the confirmed fraud on Cifas’ National Fraud Database has once again demonstrated Graydon’s capability to spot potential frauds. There is a strong overlap between fraudulent businesses and the individuals behind them, and as a result, it demonstrates that businesses cannot afford to take shortcuts in their due diligence processor they will be stung. This study absolutely shows the benefits of organisations sharing their data in the fight against fraud.”

Lee D’Arcy, commercial director, Cifas:

“Many of our members often see fraudulent behaviour from small businesses and sole traders and the cases they file give us a great deal of insight into the people behind them. Our mission to prevent fraud isn’t limited to consumer activities and working in this space with Graydon offers a wider opportunity to highlight the offenders, share information and work to stop fraud that costs UK businesses billions of pounds a year.

Dun & Bradstreet partner with big data company Quantexa to tackle financial crime

Dun & Bradstreet and Quantexa have announced a new partnership that aims to empower businesses to make better, context driven decisions using innovative data and analytics to provide a detailed picture of connected relationships.

Global commercial data & analytics firm Dun & Bradstreet, and Quantexa, the contextual decision intelligence software and solutions company, have joined forces to help identify and tackle financial crime by providing market-leading data and network analytics to help firms stay compliant in today’s regulatory environment.

By connecting Dun & Bradstreet’s rich corporate insights data with Quantexa’s contextual decision intelligence platform, the partnership will enable an enhanced view of business relationships using machine learning and artificial intelligence to identify potential corrupt or fraudulent activity. This will unlock deeper insights for decision-making through next generation entity resolution and network analytics, increasing the effectiveness of customer due diligence and compliance with ‘Know Your Customer’ regulations.

Having a complete and transparent view of linkages between individuals and business entities is critical to help detect and prevent illicit activity, such as money laundering. Combining the power of data and network analytics will deliver more detailed context on business relationships to highlight potential risk and drive more accurate, cost effective and faster business decisions.

CEO of Quantexa, Vishal Marria said: “We are delighted to be partnering with Dun & Bradstreet, where our contextual decision intelligence technology combined with its commercial data solutions offers firms an unparalleled insight into their customer and supplier data. This is key to reducing risk in a world where unstructured data growth in businesses is unprecedented.”

Brian Alster, general manager of Third-Party Risk Management at Dun & Bradstreet, said: “The world is more inter-connected than ever and having a full and transparent picture of business relationships is critical to manage risk, identify opportunity and make better decisions. Bringing together our data and Quantexa’s network analytics provides a powerful tool to support compliance activities and accelerate growth.”

SME-focussed FinTech appoints head of product to help build SME finance marketplace

The digital finance platform, BIZL, has recently unveiled its intentions to lead innovation in the SME lending journey by appointing Ravi Ambasana as head of product. Brought in from RVU Group (owners of Uswitch, Zoopla and Money.co.uk), the strategic hire shows that BIZL has its sights set on bringing much-needed innovation to SMEs who are looking for finance.

The London-based company is part of a revolution in financial technology, having ambitious plans to transform the way businesses borrow money. BIZL’s proprietary platform matches small businesses who need finance to grow with the right lenders via their marketplace. Pulling in data from credit reference agencies, Companies House and bank feeds, businesses are able to streamline their application to lenders, while lenders receive data-rich applications matched to their underwriting criteria.

With live data feeds from Companies House in place, and using blended business and personal credit search insights, Ambasana is already moving BIZL onto more ambitious projects:

“Last week we started piloting open banking, which will mean that when we match a user to a lender, the user can give us access to their live bank transaction feeds. This creates massive efficiencies for the user, us and the lender, and is very exciting. This week we go live with a direct feed to one of our lenders, meaning we can get instant approvals for requests up to £15,000. That’s pretty cool”, says Ambasana. “Next year is going to be big. It will all be about automation, building a 360’ financial picture of the user in real time, powerful insights for business owners and lenders, as well as getting our platform ready to scale into different markets.”

While ground-breaking technologies have transformed many areas within personal finance, business finance has, until recently, been left largely untouched. With the advent of open banking, and with fewer barriers to data-sharing, more FinTech companies are turning their attention to the SME market.

Josh Greenway, founder and CEO of BIZL, commented: “SMEs have been unloved for too long by the banks. Over many years investment into lending processes and underwriting has been lacking, and that’s because banks have become apathetic to their customers. BIZL is on a mission to revolutionise the way businesses borrow money, which is pretty ambitious. Ravi will play a pivotal role in helping us achieve our goals.”