Big data helping drive insurance innovation

Research shows that insurance executives are recognising the opportunities associated with big data. Of course, they are no stranger to the importance of data analysis given how the industry is built around understanding market requirements and developing solutions accordingly. With the help of technological advances, says Kelly Preston, data analytics manager at SilverBridge, it has now become easier to transform big data into actionable insights.

“The growth of insurtechs, in not only the local, but the global market, is adding to the momentum and drive towards big data transformation. Consumers are now spoilt for choice when it comes to their insurance needs. Big data therefore becomes an enabler for incumbents providing them with opportunities to transform and become more adaptable to the requirements of the digital age. This will assist in helping create the differentiation required to be more competitive,” says Preston.

An example of how big data can be used in this regard is pricing and underwriting. The ability to accurately price a policy based on complex risk procedures is critical for insurers. By making use of the big data available and incorporating artificial intelligence, this process can only become more effective and precise.

“The high-performance computing capabilities of the cloud mean insurers are no longer limited to on-premise solutions but can integrate the sophisticated insights derived from these online offerings. More efficient big data analysis can also expedite the claims process – a known challenge that frustrates many clients. More modern systems ensure vast amounts of data on claims are processed faster than ever to accelerate the process and potentially reduce premiums due to more effective pricing models.”

Customer environment

Unsurprisingly, IBM has found that customer analytics is driving big data initiatives at insurers. According to the company, this is consistent with the pressure insurers are under to transform from product-centric to customer-centric organisations. In this environment, the customer is the centrepiece around which data insights, operations, technology, and systems evolve.

“Most executives understand that big data can lead to real business advantages. It enables the capture and analysis of external data sources. Combining this with existing internal data allows the insurer to become more innovative with the development of customised and segmented service offerings,” adds Preston.

Again, think about the claims process. With the sheer number of claims to manage, insurers do not have time to closely evaluate each submission. Instead, approvals and rejections are made based on a combination of experience, the information readily at hand, and tacit knowledge of the person processing the claim.

“But machine learning throws this model on its head. The technology makes it possible to combine the human insights with a more effective and real-time analysis of data across all business units. This means claims are not only processed faster, but more accurately as well as with fewer false positives. As a result, instances of fraud are greatly reduced, customers are happier due to a smoother process and the business can grow due to increased loyalty.

About SilverBridge

SilverBridge has over 24 years’ experience as a leading provider of insurance software solutions in the African financial services industry. Our experience includes working with over 60 customers across 16 African countries. SilverBridge’s digital insurance suite allows financial services companies the opportunity to respond quickly to changing markets. With customers throughout Africa, SilverBridge has the knowledge, experience, and technology capabilities to help its clients do better business.

AI helps unlock data potential of banks

Artificial intelligence (AI) provides banks with the means to make better use of the massive amount of data at their disposal. In doing so, they can identify opportunities for growth faster and gain significant competitive advantage at a time when more agile digital counterparts are emerging. Patrick Ashton, a managing executive at SilverBridge Holdings, believes that without this insight, it is difficult to modernise processes or to understand how best to introduce new technologies into back-end systems.

“When it comes to product development, the offerings of banks typically evolve slowly over time. Part of the problem is that legacy mainframe systems are expensive and slow to update whilst people resources for these systems are scarce (and becoming more so). This creates a bottleneck in the process as the mainframe systems are typically the central record for all data. This means they must form part of any new solution developed. Front-end applications are relatively quick to develop but back-end integration or changes to core systems become the stumbling block.”

Banks must therefore work with experienced and trusted partners to extract data from mainframes into modern database architectures that can use the data more effectively. In most instances, curated data extracts taken from the mainframe are very large, making it difficult for individuals to work with. These are typically put into a spreadsheet format for users to work with. However, this is inefficient, prone to error and carries significant risk due to human involvement.

“Instead, banks need the ability to extract their data and present this to users in a modern application interface for task processing. Risks are managed better, and operational efficiencies are dramatically improved when simple rule-based actions and decisions are removed from the human function.  People can then be empowered to add higher levels of value into processes through the analysis of data insights gained, a better customer-centric service model, and re-imagining of traditional processes. AI-led technologies enable this transformation. Of course, all of this must be done within a strong governance framework. It is about building robust solutions that involve risk officers from early in the process to ensure all the necessary requirements are taken care of.”

Transforming insights

Getting insights from data is the first step to understanding where efficiency can be built into the internal processes of banks. In many instances, banks have been relying on the same data processes put in place decades ago. These have gradually been tweaked over time without major overhaul. Adoption of new technologies tends to be slow resulting in toolsets, like traditional spreadsheets, remaining the primary environment used to analyse datasets. However, this is neither efficient nor secure.

Even so, one of the most significant challenges revolves around exception handling. Most banking transactions require little human intervention. However, in cases where items are flagged (for example, AML/Fraud/Screening checks), this requires human intervention. Given the high volumes involved this comes at significant cost to the organisation.

“It is therefore an excellent place to deploy new AI technologies such as Intelligent Process Automation (IPA). This streamlines processes and automates steps usually performed by people. Think of AI virtualising the human experience. It is about building technology solutions that consider the exception handling process and automate as much of this as possible, introducing efficiencies and mitigating risk simultaneously.”

Furthermore, in many instances, banks require multiple levels of human approval for transactions to be cleared. This is another time-consuming process that can be transformed through AI. Instead of having two or three people view each transaction, the AI process can deliver the same level of expertise consistently in real time to improve SLA management and improve service to customers.

“It is not about reinventing the wheel but optimising the robust processes banks already have in place when it comes to managing their data and processes. Through refining and automation of processes a significant amount of human activity can be taken out of the system and this can be repurposed to give the bank more capacity to focus on areas such as improved customer service or the design of new offerings.

Modern practices

Using modern applications that can integrate with existing data and processes, banks are able to generate insights from start to finish. For example, look at the typical ATM infrastructure that must be managed daily. Transactions and GL account balances must be reconciled to ensure machines are working correctly, that no fraud is taking place, and there is always the right amount of cash available for banking customers without over exposure of capital reserves. Using people to reconcile and investigate discrepancies is slow and inefficient. But using AI toolsets mean these tasks can be managed consistently, at high speed, and with full auditability. Volume or capacity constraints are then no longer an issue. This extends into customer service as well, improving the customer experience when queries or complaints arise as there can be immediate action taken rather than waiting for a human to perform analysis and then take a decision.

“An AI layer can be implemented to sit on top of existing processes while integrating into back-end legacy systems to deliver the value banks require. Banks have high quality data, but it is not always accessible. Using AI to help manage the high data volumes can bring about significant improvements in operational efficiency which will ultimately deliver a better customer experience,” concludes Ashton.

About SilverBridge

SilverBridge has over 24 years’ experience as a leading provider of insurance software solutions in the African financial services industry. Our experience includes working with over 60 customers across 16 African countries. SilverBridge’s digital insurance suite allows financial services companies the opportunity to respond quickly to changing markets. With customers throughout Africa, SilverBridge has the knowledge, experience, and technology capabilities to help its clients do better business.

Insurers protect yourselves

Given the migration of insurers to digital channels and the large amount of sensitive personal information they store, it should come as no surprise that cyberattacks are becoming increasingly prevalent. Yunus Scheepers, CTO at SilverBridge Holdings, examines the importance of cyber security.

“Providing some element of protection in the policies themselves as well as safeguarding their own databases are integral components to protecting clients’ interests. Fortunately, as insurers embrace more innovative technology solutions, this is resulting in increased investment in their traditional core IT systems to support the changing environment. And while much of this is done with the aim of finding better ways to analyse data, shoring up cyber defences are equally critical,” Scheepers notes.

Identity thieves and fraudsters are using more sophisticated malware and social engineering techniques to compromise data. The sheer amount of personal data stored in insurance databases is simply too good a target for those with malicious intent to ignore. Research indicates that most reported breaches are characterised by short attacks – criminals target a system, steal specific information, and then move on. Of course, this is not to say that the risk of more long-term activities is not something to take note of. The fact that long-term intrusions have not been detected should probably be a cause for concern – it could mean that these attacks are so stealthy that they are not able to be detected by conventional cyber security tools and activities.

Constant vigilance

“Even though the percentage of successful security breaches showed a decrease in 2018 when compared with the previous year, that does not mean insurers can rest on their laurels. Even if only one in five attempts are successful, that still represents significant risk. And when one considers that almost half of breaches are not detected for more than a week, insurers have no choice but to become more proactive around their cyber security.”

Insurers deal with risk daily. That is the nature of their business. Everything comes down to risk management. The same thinking therefore needs to apply to cyber security policies and systems. Even if the statistics do not give insurers enough reason for caution, the regulatory environment will. Protecting personal information is a critical aspect of business. Those not taking the necessary steps to do so, risk significant financial fines, reputational damage, and the potential for customer legal action.

“Insurers have a number of data points that cover all aspects of people’s lives – from their identity numbers to bank account details, their home contents to the identities of their loved ones. To this end, attackers will always target the point of least resistance. This means having a firewall and anti-virus are not effective strategies. Like the approach taken by banks, insurers must adapt a more pervasive cyber security approach, one that factors in all the entry points into the back-end systems.”

Given the extreme rate at which cyber security threats are evolving, insurers cannot dismiss the concept of artificial intelligence (AI)-based security platforms. Unlike traditional cyber security systems that focus on known attack vectors, AI-based platforms actively look for anomalous or suspicious patterns and behaviours. Some of these platforms are even capable of responding intelligently to potential threats with mechanisms such as file quarantines, allowing administrators to conduct more thorough investigations in a controlled environment. There is already undeniable evidence that AI-based malware is emerging as a more prevalent threat. As a result, it makes sense that AI-based protection must be deployed to combat this threat.

“To this end, I believe that AI-based cyber security platforms will become the norm in the near future,” says Scheepers.

Embrace security

Insurers are constantly looking to become more pro-active in the digital environment and this includes ways to more effectively address their cyber security needs. Given that it has become a case of when and not if a breach occurs, this is a vital area to focus on. Cyber-attacks are no longer initiated as a targeted, human-driven activity but rather driven by malware randomly probing any system that is exposed on the internet. The risk of business interruption and the costs for policyholders have become too significant in this connected market.

“An integrated approach to cyber security is therefore essential if the insurer is to keep attackers out while mitigating the exposure when a breach does occur. Just ticking the regulatory boxes is not adequate. Insurers in the digital market must take cyber security seriously if they are to continue harnessing business opportunities,” adds Scheepers.

And this is not only limited to the technical aspects of cyber security. To be truly effective, the insurer must link protection to the broader business strategy. In this way, it becomes part of the business continuity and disaster recovery policies of the organisation.

“Cyber security must permeate every facet of the business if the company has any hope of safeguarding its data. In this way, the insurer can take a much more proactive stance towards the protection needed, with all processes aligning to this common vision,” he concludes.

About SilverBridge

SilverBridge has over 24 years’ experience as a leading provider of insurance software solutions in the African financial services industry. Our footprint extends to 14 African countries. SilverBridge’s digital insurance suite allows financial services companies the opportunity to respond quickly to changing markets. With customers throughout Africa, SilverBridge has the knowledge, experience, and technology capabilities to help its clients do better business.