Digital Sensing enables you to continuously listen to your customers across channels, discover the context and trigger processes for appropriate real-time action or response


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Banks have been good at incremental innovation and improvement, building upon existing capabilities with every wave of technological evolution. Digital, however, mandates a transformative approach. SMAC (Social, Mobile, Analytics, and Cloud) technologies have provided the underlying formative capabilities, and so have the foundational operating blocks of BPM and ECM. Organizations need to understand how best to create a transformative strategy over and above these foundational blocks.

Let’s look at some of the new age technological capabilities that banks can leverage to accomplish digital transformation, towards a connected, expansive, and ecosystem-driven banking.

Secure, Transparent, and Expansive Banking with Blockchain

Blockchain is at the forefront of the promising technologies for a connected, ecosystem-driven, banking. Payments form a large chunk of the financial services pie. Blockchain and distributed ledgers can help banks and drastically reduce payments processing costs. Not only that, blockchain can enable highly efficient cross-border payments – whether intra-bank, inter-bank, or remittance.

According to an Accenture report2, 90per cent of banks surveyed reported that they are at least exploring blockchain in payments. As many as 30per cent claimed to have some production implementation in place, while another 30per cent said they are involved in POCs (proofs-of-concept). Financial institutions are also exploring several other use cases with the potential to transform their business models, such as crypto-wallets, or cryptocurrency, albeit some of these are at a nascent stage.

Blockchain use cases for banks:

–          Cross-border payments

–          Crowdfunding and Crypto-wallets

–      Hyperledger based KYC (know-your-customer)

–      ICO (Initial Coin Offering)

–          Cryptocurrency fundraising platforms

–          Decentralized Applications (dApps)

Customer-Centric Approach with Artificial Intelligence (AI), Machine Learning (ML), and Cognitive Technologies

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The traditional methods of segmenting and targeting customers are becoming passé in natively digital ecosystems. Customers do not like being treated as ‘one of the segments’, they want to be treated as ‘one – an individual’. Hyper-personalization, driven by AI and cognitive technologies, can enable banks to treat customers in an individual context.

Having said that, contextual treatment is only one part of the customer-centricity equation. Speed is also critical. Financial institutions can automate transactions, through accurate and real-time decisions, by augmenting their processes with AI and machine learning.

AI, ML, and cognitive technologies use cases for banks:

–      Secure, customer-friendly, transactions through voice recognition

–      Linguistic analysis for monitoring and compliance

–      Real-time fraud detection

–      Pattern matching for personal finance management

Sense and Respond in Real-Time with Digital Sensing

Banks have several opportunities to tap customers, but these opportunities get swamped in the social media noise. Digital Sensing enables you to continuously listen to your customers across channels, discover the context and trigger processes for appropriate real-time action or response. Digital sensing combines omnichannel, mobility, analytics, business process management, and customer communication management capabilities to accomplish this.

Digital sensing use cases for banks:

–      Customer service and complaint management

–      Customer sentiment analysis

–      Engagement through contextual and targeted customer communication

–      Lead generation and nurture campaigns

–      Digital account opening with minimized application abandonment

Last Mile Process Automation with Robotic Process Automation

Most banks are still supported by an enormous amount of routine, mundane human tasks, particularly in high-volume transactional processes. Robotic process automation (RPA) automates these repetitive tasks to free up the bandwidth of knowledge workers and improves overall business performance. In effect, RPA ensures the last mile automation of human tasks in process automation.

Banks can leverage RPA in conjunction with BPM to accomplish responsive and accurate customer-centric operations. On one hand, RPA can help free up the bandwidth of credit analysts and loan officers, enabling them to focus on tasks requiring their expertise and experience. On the other hand, automation directly yields real-time speed and accuracy through straight-through processing (STP).

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Robotic process automation use cases for banks:

–      Transaction lodgement and data verification in trade finance

–          Straight-through application processing for consumer loans

–          High-volume, high-speed, high-accuracy transactions

–      Dispute resolution management

–      Real-time fraud and anomaly detection

–      Real-time customer complaint resolution

Faster, Smarter Decisions with Advanced Analytics

Data flowing into organizations is more complex than it might seem. Broadly, only 20per cent of the data flowing into organizations is structured. Traditionally, banks have already categorized this structured data into schemas and processable form to make actionable sense out of it. However, the remaining 80per cent data, that is unstructured, is a different ball game altogether. Information contained within emails, documents, social platforms, blogs, conversation threads, news sites, CRMs, contracts, social network discussions, maps, text, video, images, audio files, multimedia resources – all constitute unstructured data. This unstructured data is a key obstacle to truly digital banking.

Content analytics can be leveraged to convert this unstructured content into structured data and to further enrich content. The ability to translate data into actionable information directly lends speed and contextual accuracy to processes. Process analytics can lend speed and responsiveness to processes through straight-through and automated guidance. Implemented well, a combination of process and content analytics helps banks drive customer interactions in context for superior customer experience.

Advanced analytics use cases for banks:

–      Spreading and forecasting

–      Stress testing and scenario analysis

–      Scoring and risk rating models

–      Risk exposure tracking

–      Early warning signal (EWS)

–      Automated content ingestion and intelligence

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Anytime-Anywhere Banking with Advanced Mobile Capabilities

Mobility allows banks to offer services at customers’ fingertips and accomplish superior customer experience. However, in the process of going mobile, organizations risk building another silo. Smart process apps help organizations move beyond traditional mobile apps or transactional processes to become more collaborative and customer-centric with a process foundation.

Smart process apps accomplish this by acting as an organic endpoint for underlying processes while leveraging the unique capabilities of mobile devices. These mobile capabilities include geolocation enablement, biometric technologies, rich media content capture & consumption, anytime-anywhere access, multi-factor authentication, sync-and-share, offline processing and so on. A combination of BPM and a mobility framework enables you to create these powerful smart process apps.

 Advanced mobility use cases for banks:

–      Real-time eKYC (know your customer) through biometric identification

–          Mobile-based inspections and collateral e-signature with geotagging

–          Mobile-based dedupe and eligibility check

–      Real-time application and transaction tracking

–      On-the-go real-time case handling

–      Omnichannel and cross-channel loan origination process

Epilogue

Banks need to adopt a transformative strategy to tackle digital challenges. New age technologies, such as blockchain, artificial intelligence, machine learning, advanced analytics, robotic process automation and digital sensing can help them accomplish this transformative banking enterprise.

However, it is critical to understand that the effectiveness of technologies is subject to the use cases and their applicability therein. A well laid foundational stack of technologies (such as BPM, ECM, and CCM) is still a mandatory component of such transformation – to tie in and connect the processes, people and systems of the organization. Banks must create a blueprint for transformative banking, with consideration to the impact of these technologies in their functional areas of lending, account opening, trade finance, and payments. After all, it is not transformative, if it does not yield divergently greater capability to create disruptive business models and products.



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